TWI912230B - Electronic fence processing method and server and vessel management information system thereof - Google Patents

Abstract

An electronic fence processing method, comprising: receiving a position report of a vessel; determining whether the position report of the vessel is corresponding to an electronic fence; when the position report of the vessel is determined corresponding to the electronic fence, determining whether a warning message corresponding to the electronic fence is triggered; and when it is determined that the warning message corresponding to the electronic fence is triggered, transmitting the warning message corresponding to the electronic fence to a client computer of an person related to the vessel.

Description

Electronic fencing processing methods and their server-side and vehicle management information systems

This application relates to information systems, and in particular to an integrated vehicle management information system.

Large transportation vehicles such as ships and airplanes are becoming increasingly complex, sophisticated, and expensive, carrying more and more instruments and equipment, and subject to more environmental, transportation, and personnel regulations. Since each instrument and equipment system has its own management system and interface, a unified vehicle management information system is needed to efficiently and in real-time manage a large number of diverse transportation vehicles. This system would aggregate fragmented information from various management systems, integrating it into an interface that managers can quickly understand, enabling timely responses and reducing the chances of hazards. This would further reduce the risks and costs of operating transportation vehicles and improve transportation efficiency.

This application provides an integrated vehicle management information system that can aggregate fragmented information from various management systems into a user-friendly interface that managers can quickly understand and respond to, reducing the chance of hazards. This can further reduce the risks and costs of transport vehicles during operation and improve transport efficiency.

According to one embodiment of this application, a method for generating a virtual clone of a vehicle is provided, comprising: receiving a read request for a virtual clone of a first vehicle from a client; reading the vehicle information and three-dimensional model of the first vehicle at that time, and generating a three-dimensional model of the virtual clone based on the vehicle information and three-dimensional model of the first vehicle at that time; and outputting the three-dimensional model of the virtual clone to the client.

Furthermore, in order to depict the apparent state of the first vehicle at that time, the three-dimensional model of the virtual clone is used to represent the apparent state of the vehicle information, wherein the vehicle information includes one or any combination of the following: the on-state of the rotating radar; the pointing angle of the dish communication antenna; the on-state of the external cabin door; the state of the anchor chain; the configuration state of the lifeboat; and the state of the crane.

Furthermore, in order to depict the weather conditions at the time of the first vehicle, the method for generating the virtual clone of the vehicle further includes: receiving weather information corresponding to the location and time of the first vehicle from an external system server; and correcting the three-dimensional model of the virtual clone based on the corresponding weather information of the first vehicle.

Furthermore, in order to depict the cargo loaded by the first vehicle at that time, the method for generating the virtual clone of the vehicle further includes: reading the cargo loading data of the first vehicle at that time; and correcting the three-dimensional model of the virtual clone based on the cargo loading data.

Furthermore, in order to depict the types of goods carried by the first vehicle at that time, the multiple goods carried by the first vehicle were of different colors according to their types.

Furthermore, in order to depict the unloading destination of the cargo carried by the first vehicle at that time, the multiple cargoes carried by the first vehicle are different colors according to their different unloading destinations.

Furthermore, in order to depict the terrain and features near the first vehicle, the method for generating the virtual clone of the vehicle further includes: reading the three-dimensional model of the terrain and features at the current location of the first vehicle, and correcting the three-dimensional model of the virtual clone.

Furthermore, in order to depict other vehicles near the first vehicle, the method for generating the virtual clone of the vehicle further includes: determining whether the first vehicle is adjacent to other vehicles; and when the first vehicle is adjacent to a second vehicle, reading the three-dimensional model of the second vehicle, and correcting the three-dimensional model of the virtual clone based on the three-dimensional model of the second vehicle.

Furthermore, in order to depict the state of the second vehicle, the method for generating a virtual clone of the vehicle further includes: reading the vehicle state of the at least one second vehicle, and modifying the three-dimensional model of the virtual clone according to the vehicle state of the at least one second vehicle, wherein the three-dimensional model of the virtual clone is used to represent the explicit state of the vehicle information of the second vehicle.

Furthermore, in order to depict the virtual clone of the first vehicle in real time, the method for generating the virtual clone of the vehicle further includes: after receiving the read request of the virtual clone, receiving the vehicle information of the first vehicle at that time from the first vehicle.

Furthermore, in order to receive information from a remote first vehicle, wherein the aforementioned vehicle information received from the first vehicle at the time of receipt is transmitted through a satellite network.

Furthermore, in order to support clients that lack the ability to draw 3D models, the method for generating a virtual clone of a vehicle further includes: drawing a 3D model of the virtual clone to generate an image; and outputting the image to the client.

Furthermore, to support the client's ability to adjust the viewpoint, the image is drawn based on viewpoint information transmitted by the client.

According to one embodiment of this application, a server is provided for implementing the above-described vehicle virtual clone generation method, comprising: a network device for connecting to the client; and a processor connected to the network device for executing a plurality of instructions stored in non-volatile memory to implement the above-described vehicle virtual clone generation method.

According to one embodiment of this application, a vehicle management information system is provided that implements the above-described method for generating virtual vehicle clones, comprising: the server; the client; and the first vehicle.

Through the above embodiments, the vehicle virtual clone generation method provided in this application can be used for education and training, allowing novice drivers to remotely observe the navigating conditions of experienced drivers and learn from their experience. This is particularly useful in busy port areas and choke points. After an accident or emergency, replaying the virtual clone image of the vehicle involved in the accident can quickly reconstruct the situation at the time and clarify responsibility as soon as possible. The virtual clone function can also be used for remote monitoring and teaching. When novice drivers are operating the vehicle, experienced drivers can remotely monitor the novice drivers' operations to prevent danger. The virtual clone function can also allow drivers in vehicles to quickly gain situational awareness in bad weather, so as to avoid collisions with other vehicles or terrain features.

According to one embodiment of this application, a method for determining route deviation using a thermal trajectory map is provided, comprising: generating a thermal trajectory map of a class for a segment based on multiple historical position information of multiple vehicles included in a class; receiving a position report of a vehicle of the class navigating the segment; comparing the position report with the thermal trajectory map, and determining whether the thermal information is abnormal; and generating a deviation warning message when the thermal information is determined to be abnormal.

Furthermore, in order to determine whether the popularity information is abnormal, the determination of whether the popularity information is abnormal includes one or any combination of the following: determining whether the popularity information is lower than a low threshold value; and determining whether the popularity information is higher than a high threshold value, wherein when the popularity information is lower than the low threshold value or the popularity information is higher than the high threshold value, the popularity information is determined to be abnormal.

Furthermore, in order to accumulate more historical location information, when the heat information is determined to be normal, the location report is added to the historical location information of that level for that flight segment.

Furthermore, in order to send the warning message to the relevant personnel, the method for determining the flight path deviation using thermal trajectory maps further includes: transmitting the deviation warning message to the client of the relevant personnel of the vehicle.

Furthermore, in order to address the issue of deviation from the trajectory in a timely manner, the method for determining the flight path deviation using a thermal trajectory map further includes: transmitting the warning message to the computer of the relevant personnel on the vehicle using one of the following transmission methods or any combination thereof, wherein the transmission methods include SMS, email, multimedia message, voice message, video message and instant messaging.

Furthermore, in order to deliver the warning message to the correct personnel, including the driver and management personnel located in the vehicle, as well as supervisory personnel not on the vehicle.

Furthermore, in order to avoid repeatedly issuing deviation warning messages, the method for determining flight path deviation using thermal trajectory maps further includes: determining whether a corresponding deviation warning message has already been issued; and when it is determined that no corresponding deviation warning message has been issued, then transmitting the deviation warning message to the client of the relevant personnel of the vehicle.

Furthermore, in order to promptly determine whether the trajectory has deviated, the aforementioned position report is transmitted via a satellite constellation telecommunications network.

Furthermore, different navigation trajectories are generated in order to adapt to the changes in the natural environment in different seasons, and the above-mentioned historical location information corresponds to the same time period of the location report.

Furthermore, in order to adapt to different cargo carrying conditions, different navigation trajectories are generated, wherein the cargo carrying capacity level corresponding to the above-mentioned multiple historical location information corresponds to the cargo carrying capacity level corresponding to the location report.

According to one embodiment of this application, a server is provided that implements the above-described method for determining flight path deviation using a thermal trajectory map, comprising: a network device for connecting to the vehicle; and a processor connected to the network device for executing a plurality of instructions stored in non-volatile memory to implement the above-described method for determining flight path deviation using a thermal trajectory map.

According to one embodiment of this application, a server is provided that implements the above-described method for determining flight path deviation using a thermal trajectory map, comprising: a network device for connecting the vehicle and the client; and a processor connected to the network device for executing a plurality of instructions stored in non-volatile memory to implement the above-described method for determining flight path deviation using a thermal trajectory map.

According to one embodiment of this application, a vehicle management information system is provided that implements the above-described method for generating virtual vehicle clones, comprising: the server; and the vehicle.

According to one embodiment of this application, a vehicle management information system is provided that implements the above-described method for generating virtual vehicle clones, comprising: the server; the client; and the vehicle.

When managing vehicle navigation, historical experience is often used. Through the embodiments described above, the method for determining route deviation using heat map provided in this application can summarize empirical rules into heat map data, allowing for a general assessment of whether the navigation trajectory is normal based on historical experience of different classes, seasons, and/or load classes. When the navigation trajectory deviates from the historically established course, timely warnings can be issued to relevant personnel.

According to one embodiment of this application, an electronic fence processing method is provided, comprising: receiving a location report from a vehicle; determining whether the location report of the vehicle corresponds to an electronic fence; when the location report of the vehicle corresponds to the electronic fence, determining whether to trigger a warning message of the electronic fence; and when it is determined that the warning message of the electronic fence has been triggered, transmitting the warning message of the electronic fence to the client of the relevant personnel of the vehicle.

Furthermore, to avoid repeatedly sending warning messages, the electronic fence processing method further includes: when it is determined that a warning message of the electronic fence has been triggered, determining whether a corresponding warning message has already been issued; and when no corresponding warning message has been issued, then performing the aforementioned step of transmitting the warning message of the electronic fence to the client of the relevant personnel of the vehicle, wherein the aforementioned step of transmitting the warning message of the electronic fence to the client of the relevant personnel of the vehicle is performed through a satellite galaxy telecommunications network.

Furthermore, in order to address electronic fence issues promptly, the electronic fence handling method further includes: transmitting the warning message to the computer of the relevant personnel in the vehicle using one of the following transmission methods or any combination thereof, wherein the transmission methods include SMS, email, multimedia message, voice message, video message and instant messaging.

Furthermore, in order to associate the electronic fence with certain instrument readings of the vehicle, the electronic fence processing method further includes: receiving an instrument reading report from the vehicle, wherein the aforementioned step of determining whether to trigger a warning message for the electronic fence further includes: determining whether the reading range of the instrument reading report falls within the setting parameter range of the electronic fence; and when the reading range of the instrument reading report falls within the setting parameter range of the electronic fence, determining to trigger a warning message for the electronic fence.

Furthermore, in order to avoid discharging wastewater or ballast water near the shore, the instrument readings reported above relate to whether or not the equipment discharging wastewater or ballast water is activated.

Furthermore, in order to avoid the emission of high-sulfur exhaust gas near the shore, the instrument readings reported above shall be related to one or any combination of the following: fuel oil heater outlet temperature; and fuel oil heater outlet viscosity.

Furthermore, in order to avoid anchoring in the cable-laying area or injuring marine mammals, the electronic fence's setting parameters, which relate to speed in the aforementioned instrument readings, include one of the following: minimum speed; and maximum speed.

Furthermore, in order to issue a warning message within the effective time period of the electronic fence, the aforementioned step of determining whether to trigger the warning message of the electronic fence further includes: determining whether the time of the location report corresponds to a start time and an end time of the electronic fence; and determining that the warning message of the electronic fence is triggered when the time of the location report corresponds to the start time and the end time of the electronic fence.

Furthermore, in order to limit the effectiveness of electronic fencing to certain vehicle classes, the aforementioned step of determining whether to trigger the warning message of the electronic fencing further includes: determining whether the vehicle class corresponds to the corresponding class of the electronic fencing; and determining to trigger the warning message of the electronic fencing when the vehicle class corresponds to the corresponding class of the electronic fencing.

Furthermore, in order to define an electronic fence within a three-dimensional space, the range of the electronic fence includes longitude, latitude, and elevation ranges.

Furthermore, in order to define a complex-shaped electronic fence, wherein the extent of the electronic fence is the intersection or union of two or more shapes.

Furthermore, in order to automatically set up the electronic fence, the electronic fence processing method further includes: obtaining a no-fly zone announcement from an external system server; and setting the electronic fence and its start time and end time according to the no-fly zone announcement.

Furthermore, in order to automate the remote control of the instruments and equipment on the vehicle, the aforementioned warning message of the electronic fence further includes a control command issued to an instrument or equipment on the vehicle, and the aforementioned electronic fence processing method further includes: when it is determined that the warning message of the electronic fence is triggered, transmitting the control command of the warning message of the electronic fence to the corresponding instrument or equipment on the vehicle.

According to one embodiment of this application, this application provides a server for implementing the aforementioned electronic fence processing method, comprising: a network device for connecting the carrier and the client; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned electronic fence processing method.

According to one embodiment of this application, a vehicle management information system for implementing the aforementioned electronic fence processing method is provided, comprising: the server; the client; and the vehicle.

By setting up and issuing warnings through electronic fencing, complex and cumbersome regional warnings can be automated, thereby reducing the burden of navigational precautions and the chance of errors. The aforementioned automation can also include reading the readings of instruments on the vehicle and determining whether they fall within the reading range of warning messages, further automating the warning messages.

According to one embodiment of this application, a satellite-transmitted image processing method is provided, comprising: calculating the low update rate of each of the multiple surveillance cameras based on the minimum fixed bandwidth of a satellite galaxy telecommunications network and the number and resolution of multiple surveillance cameras on a carrier; and transmitting the low update rate images of the multiple surveillance cameras to a server in turn through the satellite galaxy telecommunications network.

Furthermore, in order to automate the monitoring of images, the satellite transmission image processing method further includes: using an artificial intelligence image recognition module to monitor the images transmitted by the multiple monitoring cameras; and when the artificial intelligence recognition module detects an image anomaly in the first monitoring camera among the multiple monitoring cameras, transmitting the high-refresh-rate image of the first monitoring camera to the server through the satellite galaxy telecommunications network, wherein the high-refresh-rate image is higher than the low-refresh-rate image.

Furthermore, in order to monitor the safety inside the vehicle, the aforementioned video anomalies include one or any combination of the following: fire; pipeline leak; personnel falling into the sea; pest detection; and abnormal opening of cabin doors.

Furthermore, in order to serve clients requesting high-refresh-rate images through the server, the satellite image transmission processing method further includes: determining whether a specified request has been received from the server, the specified request requesting the transmission of images from a second monitoring camera among the plurality of monitoring cameras; when the specified request is received from the server, transmitting the high-refresh-rate images from the second monitoring camera to the server through the satellite galaxy telecommunications network, wherein the high refresh rate is higher than the low refresh rate.

Furthermore, in order to serve remote clients for control and communication, the satellite transmission image processing method further includes: upon receiving the specified request from the server, performing one or any combination of the following: receiving the server's control command to the second monitoring camera via the satellite galaxy telecommunications network, and transmitting the control command to the second monitoring camera; receiving the server's remote voice data to the second monitoring camera via the satellite galaxy telecommunications network, and transmitting the remote voice data to the second monitoring camera for playback; and receiving the voice data from the second monitoring camera, and transmitting the voice data from the second monitoring camera to the server via the satellite galaxy telecommunications network.

Furthermore, in order to control the surveillance camera, the control command includes one of the following commands for the second surveillance camera: pan, tilt, and zoom.

Furthermore, in order to prioritize the transmission of commands and voice data, the transmission priority of the remote voice data, the voice data, and the control commands is higher than that of the high-refresh-rate image data.

Furthermore, in order to serve clients on the same vehicle without occupying satellite communication bandwidth, the satellite image transmission processing method further includes: after receiving the specified request, determining whether the source of the specified request is a client on the vehicle; and when the source of the specified request is a client on the vehicle, directly transmitting the image of the second monitoring camera to the client through the vehicle's internal network.

Furthermore, in order to enable the server to further recognize faces, when the artificial intelligence image recognition module monitors the image of the third monitoring camera among the multiple monitoring cameras and a face or visual recognition device appears, the high-refresh-rate image of the third monitoring camera is transmitted to the server through the satellite galaxy telecommunications network, wherein the high-refresh-rate image has a higher update rate than the low-refresh-rate image.

Furthermore, in order to serve remote clients for control and communication, the satellite transmission image processing method further includes: when the artificial intelligence image recognition module monitors the image of a third monitoring camera among the multiple monitoring cameras and detects a face or visual recognition device, it performs one or any combination of the following: receiving the server's control command for the third monitoring camera through the satellite galaxy telecommunications network. The system receives remote voice data from the server to the third surveillance camera via the satellite network and transmits the remote voice data to the second surveillance camera for playback. It also receives voice data from the third surveillance camera and transmits the voice data from the second surveillance camera to the server via the satellite network.

Furthermore, in order to determine which compartment the crew members of the vehicle are located in, the satellite transmission image processing method further includes: when the artificial intelligence recognition module monitors the image of the third monitoring camera and a face or visual recognition device appears, identifying the personnel corresponding to the face or visual recognition device; locating the compartment where the third monitoring camera is installed based on the design drawing of one compartment of the vehicle; and recording the correspondence between the personnel and the compartment.

According to one embodiment of this application, this application provides a monitoring image carrier server for implementing the aforementioned satellite transmission image processing method, comprising: a network device for connecting the plurality of monitoring cameras to the server; and a processor connected to the network device for executing a plurality of instructions stored in non-volatile memory to implement the aforementioned satellite transmission image processing method.

According to one embodiment of this application, this application provides a vehicle information system for implementing the aforementioned satellite transmission image processing method, comprising: the monitoring image vehicle server; and the plurality of monitoring cameras.

According to one embodiment of this application, this application provides a satellite-transmitted image processing method, comprising: receiving low-refresh-rate images from multiple surveillance cameras of a vehicle via a satellite galaxy telecommunications network; receiving a specified request from a source, the specified request requesting the transmission of an image from a first surveillance camera among the multiple surveillance cameras; sending the specified request to a surveillance image carrier server of the vehicle; receiving, via the satellite galaxy telecommunications network, a high-refresh-rate image of the first surveillance camera corresponding to the specified request from the surveillance image carrier server, wherein the high-refresh-rate image has a higher refresh rate than the low-refresh-rate image; and transmitting the high-refresh-rate image to the source.

Furthermore, in order to store the aforementioned high update rate images, the satellite transmission image processing method further includes storing the high update rate images in the data management layer.

Furthermore, in order to facilitate control and communication between the source and the first surveillance camera, the satellite image transmission processing method further includes one or any combination of the following: receiving control commands from the source and transmitting the control commands to the surveillance camera server via the satellite network for controlling the first surveillance camera; receiving remote voice data from the source and transmitting the remote voice data to the surveillance camera server for instructing the first surveillance camera to play the remote voice data; and receiving voice data from the first surveillance camera via the surveillance camera server through the satellite network and transmitting the voice data to the source.

Furthermore, in order to control the surveillance camera, the control command includes one of the following commands: pan, tilt, and zoom on the first surveillance camera.

Furthermore, in order to prioritize the transmission of commands and voice data, the transmission priority of the remote voice data, the voice data, and the control commands is higher than that of the high-refresh-rate image data.

Furthermore, to automate image monitoring, the satellite-transmitted image processing method further includes: using an artificial intelligence image recognition module to monitor low-refresh-rate images from the multiple monitoring cameras; and when the artificial intelligence image recognition module detects an anomaly in the image from the first monitoring camera, the artificial intelligence image recognition module, as the source, issues the specified request.

Furthermore, in order to monitor personnel entering specific compartments, the satellite-transmitted image processing method further includes: using an artificial intelligence image recognition module to monitor facial or visual recognition devices in the high-refresh-rate images; querying the personnel corresponding to the facial or visual recognition device; querying the compartment where the first monitoring camera is installed based on the compartment design drawing of the vehicle; determining whether the correspondence between the personnel and the compartment is abnormal; generating a warning message when the correspondence is determined to be abnormal; and transmitting the warning message to the client of the relevant personnel in the vehicle through the satellite galaxy telecommunications network.

Furthermore, in order to monitor personnel operating certain equipment, the satellite-transmitted image processing method further includes: using an artificial intelligence image recognition module to monitor a face or visual recognition device in the high-refresh-rate image; querying the personnel corresponding to the face or visual recognition device; querying an instrument corresponding to the first monitoring camera based on the cabin design drawing of the vehicle; determining whether the correspondence between the personnel's certificate and the instrument is abnormal; generating a warning message when the correspondence is determined to be abnormal; and transmitting the warning message to the client of the relevant personnel in the vehicle through the satellite galaxy telecommunications network.

Furthermore, in order to monitor the high-refresh-rate images transmitted by the vehicle, the satellite-transmitted image processing method further includes: receiving high-refresh-rate images from a second monitoring camera among the multiple monitoring cameras via the satellite network; monitoring the high-refresh-rate images using an artificial intelligence image recognition module; generating a warning message when the artificial intelligence image recognition module determines that an image abnormality occurs in the high-refresh-rate images; and transmitting the warning message to the client of the relevant personnel of the vehicle via the satellite network.

Furthermore, in order to monitor the safety inside the vehicle, the aforementioned video anomalies include one or any combination of the following: fire; pipeline leak; personnel falling into the sea; pest detection; and abnormal opening of cabin doors.

According to one embodiment of this application, a server for implementing the aforementioned satellite transmission image processing method is provided, comprising: a network device for connecting the monitoring image carrier server and the source; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned satellite transmission image processing method.

According to one embodiment of this application, a vehicle information system for implementing the aforementioned satellite transmission image processing method is provided, comprising: the monitoring image vehicle server; the plurality of monitoring cameras; and the server.

The satellite-transmitted image processing method provided in this application allows remote clients or AI image recognition modules to monitor multiple low-refresh-rate images transmitted from the carrier, even with limited communication bandwidth. Upon request from the client or AI image recognition module, high-refresh-rate images can be transmitted for further identification. Automating the relationship between identification personnel and the cabin or equipment significantly reduces the burden of security checks. When the automated identification images malfunction, an automatic warning message can be issued.

According to one embodiment of this application, a method for calculating the carbon footprint of cargo is provided, comprising: receiving a first reading from a power meter of a vehicle; receiving a second reading from the power meter; calculating the power consumption of the power meter based on the difference between the second reading and the first reading; identifying the cargo corresponding to the power meter based on cargo loading data of the vehicle; and calculating the carbon footprint of the cargo based on the ratio of the vehicle's power consumption to carbon emissions and the corresponding power consumption of the cargo.

Furthermore, to ensure that the first reading is taken when the cargo is loaded and powered on, the cargo carbon footprint calculation method further includes: finding the location of the vehicle corresponding to the reading time based on the reading time of the first reading; determining whether the location corresponds to the loading location of the cargo; and determining that the first reading is valid when the location corresponds to the loading location of the cargo.

Furthermore, to ensure that the second reading is taken when the cargo is unloaded and powered off, the cargo carbon footprint calculation method further includes: finding the location of the vehicle corresponding to the reading time based on the reading time of the second reading; determining whether the location corresponds to the unloading location of the cargo; and determining that the first reading is valid when the location corresponds to the unloading location of the cargo.

Furthermore, in order to measure the power consumption of the goods as early as possible, the first reading is taken when the power consumption line calculated by the power meter is connected to the load.

Furthermore, in order to fully measure the power consumption of the goods, the first reading is taken when the power-consuming line calculated by the power meter is off-load.

Furthermore, to accurately measure the ratio of electricity consumption to carbon emissions of the vehicle, the cargo carbon footprint calculation method further includes: receiving a first total electricity meter reading from the vehicle, wherein the reading time of the first reading corresponds to the reading time of the first total electricity meter; receiving a second total electricity meter reading from the vehicle, wherein the reading time of the second reading corresponds to the reading time of the second total electricity meter; receiving the vehicle's... The vehicle receives a first fuel reading from a fuel meter of an electric motor, wherein the reading time of the first reading corresponds to the reading time of the first fuel reading; receives a second fuel reading from the fuel meter, wherein the reading time of the second reading corresponds to the reading time of the second fuel reading; and calculates the ratio of the vehicle's electricity consumption to carbon emissions based on the first total electricity meter reading, the second total electricity meter reading, the first fuel reading, and the second fuel reading.

Furthermore, in order to automatically provide reports to cargo owners, the cargo carbon footprint calculation method includes: generating a carbon footprint report based on the cargo's carbon footprint; and transmitting the cargo carbon footprint report to the cargo owner's external system server via the network.

Furthermore, in order to automatically provide electricity bills to cargo owners, the cargo carbon footprint calculation method includes: generating electricity bills for the cargo based on the cargo's carbon footprint; and transmitting the cargo's electricity bills to the cargo owner's external system server via the network.

According to one embodiment of this application, a server is provided for implementing the aforementioned cargo carbon footprint calculation method, comprising: a network device for connecting the power meter and the vehicle; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned cargo carbon footprint calculation method.

According to one embodiment of this application, a server is provided for implementing the aforementioned cargo carbon footprint calculation method, comprising: a network device for connecting the sub-meter, the main meter, and the fuel meter; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned cargo carbon footprint calculation method.

The cargo carbon footprint calculation method provided in this application allows for more accurate calculations and automatically generates carbon footprint reports for cargo. This enables cargo owners to better understand the power consumption during transportation on the vehicle, allowing them to seek more energy-efficient and carbon-reducing methods for transportation.

According to one embodiment of this application, a method for calculating carbon emission exemptions for a vehicle is provided, comprising: obtaining a list of all goods for which carbon footprints should be calculated based on cargo loading data of a vehicle, the list of goods including at least one cargo; performing the above-described cargo carbon footprint calculation method on the at least one cargo to obtain at least one carbon footprint report; and generating an exemption value for carbon emissions of the vehicle based on the at least one carbon footprint report.

According to one embodiment of this application, a server is provided for implementing the aforementioned vehicle carbon emission exemption calculation method, comprising: a network device for connecting to the power meter; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned vehicle carbon emission exemption method.

According to one embodiment of this application, a server is provided for implementing the aforementioned vehicle carbon emission exemption calculation method, comprising: a network device for connecting the sub-meter, the main meter, and the fuel meter; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned vehicle carbon emission exemption method.

The carbon emission exemption calculation method provided in this application allows for more accurate calculation of the carbon footprint of goods, leading to more accurate carbon emission exemptions. It also enables vehicle managers to better understand the power consumption during transportation, allowing them to find more energy-efficient and carbon-reducing methods for transport.

This invention will describe some embodiments in detail below. However, in addition to the disclosed embodiments, this invention can also be widely applied to other embodiments. The scope of this invention is not limited to these embodiments, but is defined by the scope of the subsequent patent applications. To provide a clearer description and to enable those skilled in the art to understand the contents of this invention, the parts in the figures are not drawn according to their relative dimensions; some dimensions are exaggerated in proportion to other related scales, and irrelevant details are not fully drawn for the sake of simplicity. Furthermore, other steps unrelated to this invention can be inserted into the steps shown in the flowcharts of this invention. Unless there is a causal dependency, this invention does not limit the order of execution of the steps.

Please refer to Figure 1, which is a block diagram of an integrated vehicle management information system 100 according to an embodiment of this application. The vehicle management information system 100 implemented by the applicant is called a smart ship center or war room system, mainly used for managing various types of ships. Those skilled in the art will understand that although the embodiments of this application are illustrated using ships as vehicles, this application does not limit the vehicle to ships. For example, aircraft, rail-powered vehicles, freight vehicles, trailers, trains, etc., can all be considered as applicable to this application.

In Figure 1, the vehicle management information system 100 includes three vehicles 110. Vehicles 110 can use inertial navigation systems, radio navigation systems, and navigation satellite systems to determine their position, heading, speed, and other information. For example, the vehicle management information system 100 can include multiple navigation satellite systems 140. Navigation satellite system 140A can be a global navigation satellite system, such as the US Global Positioning System (GPS), Russia's GLONASS system, Europe's Galileo system, and China's BeiDou Navigation Satellite System. Navigation satellite system 140B can be a regional navigation satellite system, such as India's Regional Navigation Satellite System (IRNSS) and Japan's Quasi-Zenith Satellite System (QZSS). The navigation satellite signal receiver on vehicle 110 can determine its own position, heading, speed and other information based on the radio signals emitted by various navigation satellite galaxies.

The vehicle management information system 100 may include a communication satellite network and a traditional terrestrial telecommunications network to connect the vehicle 110 and the server 170. When the vehicle 110C is located in a fixed location such as a port, airport, gas station, or parking lot, it can connect to the access telecommunications network 120 via wired or wireless means. The client 190 within the vehicle 110C can connect to the telecommunications network 150 and the company's internal network 160 via the access telecommunications network 120, and finally connect to the server 170. The bandwidth of the access telecommunications network 120 is generally higher than that of the communication satellite system, the rates of using the access telecommunications network 120 are generally lower than those of the communication satellite system's telecommunications network, and the reliability and privacy of the access telecommunications network 120 are generally higher than those of the communication satellite system's telecommunications network. Therefore, the carrier 110 can preferentially use the telecommunications network 120.

Vehicle 110B can connect to telecommunications network 150 and the company's internal network 160 via the low-to-medium orbit communication satellite galaxy telecommunications network 130, and finally to server 170. Similarly, vehicle 110A can connect to telecommunications network 150 and the company's internal network 160 via the high-to-high orbit communication satellite galaxy telecommunications network 135, and finally to server 170. The operating characteristics of the low-to-medium orbit communication satellite galaxy telecommunications network 130 are different from those of the high-to-high orbit communication satellite galaxy telecommunications network 135. The latter usually refers to geostationary orbit satellites or geostationary orbit satellites, at an altitude of about 36,000 kilometers, with a small number of satellites and easy antenna tracking. The following Wikipedia page lists high-orbit communication satellites (https://en.wikipedia.org/wiki/List_of_satellites_in_geosynchronous_orbit). High-orbit satellites typically operate at altitudes of hundreds to thousands of kilometers, such as SpaceX's Starlink. However, due to the large number of satellites and their extremely high speeds, phased array antennas are used to electronically control the directional radio communication beams to track these high-speed moving low-to-medium orbit satellites. High-orbit satellites are similar to base stations in terrestrial radio networks, requiring dynamic competition for bandwidth with other users. They offer better communication quality but unstable bandwidth. High-orbit satellites are more similar to fixed leased telecommunications lines. Although the fixed bandwidth is not large, they do not require competition for bandwidth with other users.

The navigation information of the aforementioned vehicle 110 and the status information of other instruments and equipment on the vehicle can be transmitted to the server 170 through the aforementioned access telecommunications network 120, the low-to-medium orbit communication satellite network 130, and/or the high-orbit communication satellite network 135. Similarly, the instruments and equipment operating inside each vehicle 110 and the client 190 can also communicate with the server 170 through such telecommunications network connections.

Internal network 160 can be used to connect client 190A and server 170. The aforementioned telecommunications network 150 can connect to other cloud servers 175, external system servers 180, and clients 190B. For example, the aforementioned telecommunications network 150 can be provided by Category I and Category II telecommunications operators licensed by various governments. Client 190B can use a Virtual Private Network Protocol (VPN) to connect to internal network 160 for connecting to server 170. In one embodiment, cloud server 175 can also connect to internal network 160 via a VPN. In other words, part or all of server 170 is not located within internal network 160, but rather outside of internal network 160. Client 190 and other instruments can connect to cloud server 175.

Those skilled in the art will understand that, through network parameter settings, cloud server 175 can be considered as server 170 or at least as part of server 170 in server logic. Server 170 as mentioned in this application may refer to either server 170 within the internal network 160 or any combination of cloud server 175.

In addition, the telecommunications network 150 is also used to connect to the external system server 180. For example, the external system server 180 can provide information such as meteorological data, parts procurement data, government declaration data, freight forwarding data, customs declarations, and container data from container yards. The server 170 can utilize the aforementioned external system server 180 through one or more accounts, allowing one or more authorized user accounts to obtain relevant information.

The vehicle management information system 100 can set up multiple user accounts (or simply users), and can also set access permissions for each user account for each type of function. Each user account can contain one or more types of personal biometric data, such as fingerprints, retina, facial models, voiceprints, and headshots. The client 190 can include a biometric data reading device to identify the user. For example, the client 190 or a surveillance camera can take a photo and send it to the server 170. Then, the server 170 can use an AI-trained deep neural network to identify the user in the photo. In another embodiment, the user can wear a visual recognition device, such as a machine-readable code like a barcode or QR code. The surveillance camera can decode the machine code presented by the aforementioned visual recognition device and then correspond it to the user.

Please refer to Figure 2, which is a block diagram of a vehicle information system 200 according to an embodiment of this application. The vehicle information system 200 includes an internal vehicle network 210, such as an internal network 210 composed of various switches. To connect various computers, the vehicle information system 200 includes an internal vehicle wired network 220 and/or an internal vehicle wireless network 230. The internal vehicle wired network 220 may conform to industry standards such as IEEE 802.3, Token Ring, etc. The internal vehicle wireless network 230 may also conform to industry standards such as IEEE 802.11, Bluetooth, etc.

In order to connect to the telecommunications network 120, the low-Earth orbit communication satellite network 130, and the high-Earth orbit communication satellite network 135 shown in Figure 1, the vehicle information system 200 may include an external network router 240 for connecting to the telecommunications network connection device 250, the low-Earth orbit communication satellite connection device 252, and the high-Earth orbit communication satellite connection device 254, respectively. The external network router 240 can, based on the availability of the telecommunications network 120, the low-Earth orbit communication satellite network 130, and the high-Earth orbit communication satellite network 135, respectively, select the appropriate connection device to connect to the aforementioned telecommunications networks.

Those skilled in the art will understand that the aforementioned telecommunications network connection device 250, low- and medium-orbit communication satellite connection device 252, and high-orbit communication satellite connection device 254 may have specific components such as antennas, modems, power amplifiers, and filters.

To connect to server 170, the vehicle information system 200 may include client 190. Client 190 can be a common end-user computer, such as a smartphone, personal digital assistant, tablet, desktop computer, or laptop. The computer's operating system can run a common web browser or a specific application as a client connecting to server 170. For example, the operating system could be Apple's iOS, macOS, Microsoft's Windows operating system, or Google's Android operating system. The application is an application installed within the operating system environment. The web browser could be Chrome, Edge, Fire Fox, or Safari. The client 190 may have a wired network connection device and/or a wireless network connection device for connecting to the aforementioned internal wired network 220 and/or internal wireless network 230 of the vehicle. The client 190 may connect to the aforementioned telecommunications network 150 via an external network router 240 to connect to the company's internal network 160. The client 190 may also connect to the Internet. The client 190 may be installed anywhere within the vehicle 110 that has an internal network, such as the bridge, engine room, captain's office, and cabins.

Because the vehicle 110 has many compartments housing numerous machines and instruments, and the external environment also needs to be monitored, multiple surveillance cameras 282 are required to monitor and record both internally and externally. Each surveillance camera 282 may include one or more lenses, each capturing a portion of the spectrum. This spectrum may include ultraviolet, visible light, and infrared light. The lenses may have zoom capabilities, allowing for image magnification and reduction. The surveillance camera 282 may include pan, tilt, and zoom functions, and the PTZ function can be remotely controlled. The aforementioned surveillance camera 282 may include non-volatile memory to record captured images. The surveillance camera 282 may include a wired network connection device and/or a wireless network connection device for connecting to the internal wired network 220 and/or internal wireless network 230 of the vehicle, so as to communicate with the surveillance video vehicle server 280 inside the vehicle 110. The surveillance camera 282 can receive instructions from the client 190 inside the same vehicle 110 and transmit the surveillance video to the client 190 for playback in real time. It can also receive PTZ commands from the client 190 to perform pan, tilt, zoom, and other functions. The aforementioned surveillance camera 282 may include a microphone and a speaker, and the client 190 may communicate with personnel in front of the surveillance camera 282 via audio. Those skilled in the art will understand that the aforementioned surveillance camera 282 may refer to commercially available network surveillance cameras (IP cameras).

The aforementioned surveillance vehicle server 280 may have a wired network connection device and/or a wireless network connection device for connecting to the aforementioned internal wired network 220 and/or internal wireless network 230 of the vehicle, so as to communicate with multiple surveillance cameras 282 inside the vehicle 110. The surveillance cameras 282 can receive control commands and/or PTZ commands from the surveillance vehicle server 280 and transmit the captured images to the surveillance vehicle server 280 in real time. The surveillance camera server 280 can have a non-volatile memory device, such as a hard drive, magnetic tape, optical disc, or flash memory, capable of recording the images captured by each surveillance camera 282 along with their corresponding timestamps in the non-volatile memory device. Furthermore, the surveillance camera server 280 can transmit the recorded images captured by the surveillance cameras 282 to the server 170 via an external network router 240. The client 190 can connect to the server 170 to play the images captured by a specific surveillance camera 282.

The aforementioned surveillance camera server 280 may include an artificial intelligence image recognition module. It can identify faces or silhouettes in the images transmitted from the surveillance camera 282. Furthermore, as mentioned earlier, the server 170 may contain each user's personal biometric data. The aforementioned surveillance camera server 280 can identify which user a face in the image belongs to. In one embodiment, the user inside the device may wear a visual recognition device, such as a one-dimensional or two-dimensional barcode with user identification information, to facilitate image recognition.

Server 170 can store cabin design plans for each vehicle 110. For example, a ship may have multiple decks, each with multiple cabins. Each cabin may have one or more instruments and equipment. The cabin design plans can record the installation location of each surveillance camera 282 and the area it captures. The surveillance vehicle server 280 can request cabin design plans from server 170 or store the cabin design plans for its respective vehicle 110. Based on the installation location of the surveillance camera 282, the surveillance vehicle server 280 can determine the location of the identified user inside the vehicle 110.

Furthermore, the monitoring vehicle server 280 can upload the user's location to the server 170. The client 190 of the same vehicle 110 can also be directly connected to the monitoring vehicle server 280 to know the location of each user inside the vehicle. In the event of an emergency, the server 170 and client 190 can know the user's last location for purposes such as headcount and emergency evacuation.

Server 170 may contain personnel data for each user, such as the licenses and permits held by each user. Regulations may stipulate that personnel need certain licenses or permits to operate certain instruments or equipment. Therefore, when a surveillance camera 282 is filming a piece of equipment, the surveillance camera server 280 can transmit the user data of the identified operator to server 170. Server 170 can then determine whether the user is qualified to operate the equipment based on that user's personnel data. When the server 170 detects that the operator is unqualified, it can issue an alarm to the user and the personnel managing the vehicle via instant messaging software, SMS, or other means. It can also communicate with the user through the microphone and speaker of the monitoring camera 282, for example, by issuing a warning tone. Furthermore, when the instrument can accept commands from the server 170, the server 170 can prevent the instrument from operating according to the user's commands.

In one embodiment, since maritime regulations require that a qualified officer be on duty at the bridge, the server 170 can monitor whether the personnel on the bridge are qualified. When the server 170 finds that the personnel on the bridge are unqualified, it can issue an alarm to the personnel managing the vehicle through instant messaging software, SMS, or other means. It can also communicate with the personnel on the bridge through the microphone and speaker of the monitoring camera 282 in the bridge, for example, by issuing a warning voice.

In one embodiment, when the surveillance camera 282 has a PTZ function, it may also include an automatic face tracking function, automatically controlling the PTZ function of the camera to track faces. The surveillance camera 282 can transmit PTZ parameters back to the surveillance image carrier server 280 and/or the server 170. The server 170 can enable or disable the automatic tracking function of the surveillance camera 282. In another embodiment, two surveillance cameras 282 connected in the field of view both have PTZ and automatic face tracking functions. When a user is about to leave the controllable field of view of the first monitoring camera 282, the server 170 can instruct the second monitoring camera 282 to adjust its controllable field of view to the user's direction, so as to perform image tracking and handover of the user's movements.

In one embodiment, when the surveillance camera 282 has a PTZ function, it may also include an automatic anomaly tracking function, automatically controlling the PTZ function of the camera to track abnormal parts. For example, when a pipeline leaks or catches fire in the image, a rat is identified in the cabin, or a person falls into the sea is identified, the surveillance camera 282 can report the anomaly to the surveillance video carrier server 280 and/or the server 170.

In one embodiment, the multiple surveillance cameras 282 of the vehicle 110 have overlapping views. For example, the surveillance cameras 282 at the bow, midship, and stern can interactively identify the same neighboring vessels. Since the same neighboring vessel is positioned differently in the images captured by the multiple surveillance cameras 282, the surveillance vehicle server 280 can estimate at least one of the following information about the neighboring vessel: distance, size, speed, etc., based on the difference in angle.

When the monitoring vehicle server 280 has vehicle identification capabilities, it can identify the class of adjacent vehicles based on images captured by one or more monitoring cameras 282. Since the server 170 can contain data on vehicles of all classes worldwide, knowing the size of adjacent vehicles allows for more accurate estimation of distance and speed.

The carrier 110 may also include an AIS transceiver 260, which is used to broadcast the location of the carrier 110 via radio at regular or irregular intervals according to the AIS (Automatic Identification System) standard specifications, and to receive radio locations broadcast by other nearby carriers 110. Due to the limited propagation distance of radio, the AIS transceiver 260 can only receive AIS data broadcast by other nearby carriers 110. The AIS transceiver 260 can transmit the transmitted and received AIS data to an AIS data forwarding device 270. The AIS data forwarding device 270 can transmit the transmitted and received AIS data to the server 170 and other devices via an external network router 240. The AIS data transfer device 270 may include non-volatile memory, which can store the transmitted and received AIS data for future reference. The AIS data transfer device 270 can also transmit the transmitted and received AIS data to a computer inside the vehicle, such as client 190 and/or monitoring screen vehicle server 280, via the vehicle's internal network 210.

Those skilled in the art will understand that although AIS data is used as an example in this application, this application is applicable to any radio broadcast data with a specific format specification, and is not limited to AIS. For example, ADS-B (Automatic Dependent Surveillance-Broadcast) used in aircraft can also have the function of receiving radio broadcast data (ADS-B Out) and receiving radio broadcast data (ADS-B In). The aforementioned radio broadcast data may include, but is not limited to, the following information: vehicle number, vehicle class, vehicle name, vehicle nationality, vehicle reference coordinates, vehicle head coordinates, vehicle tail coordinates, vehicle speed, vehicle direction, vehicle head draft, vehicle mid-draft draft, vehicle tail draft, vehicle attitude relative to the ground, vehicle operating status, vehicle hazardous load, vehicle emergency information, and surrounding weather information (e.g., wind speed and wind direction).

In one embodiment of the present invention, the standards used for transmitting and receiving the aforementioned AIS and/or ADS-B are collectively referred to as carrier location radio broadcasting. In other words, the aforementioned AIS transceiver 260 can be referred to as carrier location radio broadcasting transceiver 260, and the aforementioned AIS data transfer device 270 can be referred to as carrier location radio broadcasting data transfer device 270.

Because AIS transmitters are widely deployed—for example, fishermen often equip fishing nets, buoys, fixed fishing nets, and marine aquaculture facilities with AIS transmitters—the AIS data forwarding device 270 continuously transmits this carrier-unidentified AIS data, wasting a significant amount of communication bandwidth. Therefore, in one embodiment, the AIS data forwarding device 270 can have a filtering function. Under certain conditions, the AIS data forwarding device 270 will not forward AIS data from a particular carrier to the server 170 and/or other data consumers, thereby saving communication bandwidth. For example, the above situations may include incorrect carrier number of AIS data, zero carrier rate of AIS data, or lack of carrier nationality for AIS data.

In the embodiment shown in Figure 2, one or more vehicle instrument control devices 290 are also included, connected to the vehicle's internal network 210. The vehicle instrument control device 290 can transmit readings from the instruments it controls or monitors to a client 190 or other computer within the vehicle 110, or it can transmit readings back to a server 170. In addition to transmitting readings, the vehicle instrument control device 290 can also receive commands from the server 170 and/or other certified computers. For example, the aforementioned vehicle instrument control device 290 can be used to monitor the vehicle host and various auxiliary machines. The uploaded readings may include, but are not limited to, the main engine speed, the temperature of each cylinder, fuel consumption, the auxiliary engine speed, power generation, servo angle, the speed of each propeller, pitch configuration, cable tension, draft, radar operation status, the opening and closing status of various cabin doors, crane status, lifeboat status, fuel heater outlet temperature, fuel heater outlet viscosity, anchor status, sub-meter readings, total meter readings, fuel gauge, the vehicle's three-axis attitude, and the status of cabin doors discharging wastewater or ballast water, etc.

Please refer to Figure 3, which is a block diagram of a server 170 according to an embodiment of this application. The server 170 may comprise a cluster server farm consisting of one or more computers. Logically, the server 170 can be divided into a three-tier structure, each tier comprising a cluster server farm consisting of one or more computers. The aforementioned three-tier structure includes an access tier 310, a business logic tier 320, and a data management tier 330.

The data management layer 330 may include at least one database management system (DBMS), such as a traditional relational database management system or an update-based database management system. The data management layer 330 may also include a file server for storing large numbers of files. The data management layer 330 primarily performs storage, retrieval, and other management tasks related to data and/or files according to the requirements of the business logic layer 320.

The access layer 310 may include a web server conforming to HTML standards, or an access server with a proprietary interface. For example, the aforementioned AIS data transfer device 270 may connect to the access server through an interface such as a Web Service. The aforementioned monitoring video carrier server 280 may also receive images through an access server with a proprietary interface specification. Those skilled in the art will understand that the access layer 310 may include servers with one or more interfaces for connecting various vehicle instrument control devices 290, AIS data transfer devices 270, monitoring video carrier servers 280, and clients 190. The aforementioned vehicle instrument control device 290, AIS data transfer device 270, monitoring screen vehicle server 280, and client 190 can be referred to as a client in a broad sense, in relation to server 170. In one embodiment, client 280 can use an HTML-compliant web browser to connect to the web server of access layer 310.

In one embodiment, the business logic layer 320 may include one or more application servers, such as J2EE or IIS. It may also include one or more business logic process application servers, such as Microsoft's Power BI. Those skilled in the art will understand that the business logic layer 320 may include software and hardware that implement the functionality of the various embodiments provided in this application; for example, software components deployed in JavaBeans format can individually implement a particular business logic. For example, the business logic layer 320 can receive requests from the access layer 310, and based on the functions required in the requests, retrieve corresponding data from the data management layer 330, or send corresponding data to the data management layer 330 to the relevant data structure. After processing the data according to the above functions, it generates response data corresponding to the above requests and sends it back to the access layer 310. The access layer 310 can further forward the requests to the requesting vehicle instrument control device 290, AIS data transfer device 270, monitoring video vehicle server 280, and client 190, which is the aforementioned client in a broad sense.

When the access layer 310 receives requests from a broad range of clients, it may not be necessary for the business logic layer 320 and/or data management layer 330 of the server 170 to process them. For example, when client 190 needs weather data, the access layer 310 can forward the weather data request to the external system server 180B. After the external system server 180B sends back the weather data, the access layer 310 can directly or after modifying the response format send the weather data back to client 190.

In another embodiment, when client 190 needs to access external system server 180A via remote desktop, terminal, or thin client, server 170 pre-stores one or more sets of usernames and passwords for external system server 180B in data management layer 330. When access layer 310 receives a login request from client 190, it can first have business logic layer 320 determine whether the user has the corresponding permissions. When business logic layer 320 learns from data management layer 330 that the user has the permissions, it can retrieve the corresponding username and password and connect to external system server 180A to log in. Next, the server 170 can act as a bridge between the client 190 and the external system server 180A to transmit communication messages back and forth.

In some cases, in addition to transmitting data to the data management layer 330 for storage, the business logic layer 320 must also transmit formatted data to the external system server 180A. Accordingly, the program components of the business logic layer 320 can retrieve the corresponding username and password from the data management layer 330 and connect to the external system server 180A to perform corresponding automated operations.

Please refer to Figure 4, which is a schematic diagram of a virtual clone (or digital clone) of a vehicle displayed in a window according to an embodiment of this application. To better manage the vehicle 110, the server 170 can provide the client 190 with virtual clones of the vehicle formed by images, videos, and/or any machine-readable drawing language, allowing the user of the client 190 to understand the status of the vehicle corresponding to the virtual clone. The client 190 can display the aforementioned virtual clone in a window or in full-screen mode.

The vehicle 110 shown in Figure 4 is a small container ship. It is sailing in the open sea with relatively mild weather; there are no other ships nearby on its starboard side, and the sun is rising. The date and time are displayed in the upper right corner. Figure 4 also shows the container ship's loading status, with several containers mounted in front of and behind the bridge. At the bottom of the window are several control options, such as a square stop button, a single arrow to the right to release, a single arrow to the left to rewind, double arrows to the right to fast forward, and double arrows to the left to rewind. These buttons control the playback sequence of the virtual clone. In addition to controlling the playback sequence, users can use the mouse, scroll wheel, trackball, etc., to zoom in and out on the center of the screen, the center of the vehicle, or a specific point on the screen. Users can also adjust the direction and width of the viewpoint.

In one embodiment, the aforementioned virtual clone is drawn on client 190 by the renderer based on the description language transmitted from server 170. In other words, for the same vehicle, the first client 190 and the second client 190 can receive the same description language, but different users of the two clients 190 can adjust the parameters themselves so that the angle and size of the virtual clone they see are different. The description language can follow standard formats, such as 3GML, VRML, X3D, WebGL, etc. Those skilled in the art will understand that the web browser of client 190 can use a built-in renderer or an external renderer to generate the virtual clone's image. The server 170 can continuously provide the drawing language to the client 190 for screen updates via streaming.

In another embodiment, the client 190 may be too weak to support the real-time drawing of the description language by the painter. Therefore, the server 170 can transmit the drawing results as an image or video to the client 190 after drawing on the server 170 according to the visual settings and instructions given by the client 190.

To construct virtual clones, server 170 or its business logic layer 320 can be used to implement a method for generating virtual clones. This method can generate a 3D model representing the virtual clone of the vehicle itself based on the 3D model of the vehicle and its cargo loading data in the data management layer 330. For example, server 170 can generate a 3D model of the container ship of the class from which the clone is to be generated, as well as a 3D model of its surrounding environment.

Furthermore, the aforementioned vehicle instrument control device 290 can report other information that can be displayed on the vehicle's exterior. For example, the vehicle instrument control device 290 can be used to control one or more rotating marine radars. When a rotating marine radar is activated, the vehicle instrument control device 290 can transmit its operating status back to the server 170. Therefore, the above-described method for generating virtual clones can cause the rotating marine radar at the corresponding location of the virtual clone to rotate or remain stationary depending on whether the rotating marine radar is activated or not. In another example, the vehicle instrument control device 290 can be used to control the crane of a lifeboat or a contact boat. When the crane lifts the lifeboat or berth to the lowered position, the vehicle instrument control device 290 can transmit its operational status and the position of the lifeboat or berth to the server 170. Therefore, the method for generating the virtual clone described above can display the virtual clone accordingly based on the crane's operational status and the position of the lifeboat or berth. In a further example, the vehicle instrument control device 290 can determine the opening and closing status of certain doors and equipment, such as the side doors and gangways used by the pilot to board the ship. The vehicle instrument control device 290 can transmit the operational status of the side doors and gangways to the server 170. Therefore, the above-mentioned method for generating virtual clones can display the virtual clones according to the working status of the side cabin doors and gangways.

In addition, based on the cargo loading data stored on server 170, it can be determined how many containers are loaded in the container rows in front of and behind the driver's cab. It can also be determined what standard length these containers are, and which containers are refrigerated containers with refrigeration capabilities. Based on this cargo loading data, the virtual clone generation method allows the corresponding container row to display the corresponding containers for each virtual clone. It can also assign different colors or display methods to each type of container.

To facilitate identification of the container's destination, this method of creating virtual avatars can color-code or display each container differently based on its intended port of discharge. For example, a container scheduled to be unloaded at the next port of call can be displayed in the first color, a container scheduled to be unloaded at the port after that can be displayed in the second color, and so on.

The method for generating this virtual clone can read the terrain and feature model in the data management layer 330 based on the location reported by vehicle 110, and generate a descriptive language for the terrain and features surrounding the vehicle. For example, when a ship is entering or leaving port, its position in the port area can be depicted based on the location of vehicle 110. Users can see its correspondence with breakwaters, buoys, buildings on the shore, etc.

Through the vehicle instrument control device 290 and/or the AIS data transmission device 270, the server 170 can obtain one or any combination of the vehicle's speed, heading, bow direction, rudder direction, wind direction, wind speed, and draft. This method of generating a virtual clone can draw corresponding water wave and wind direction data near the vehicle based on the aforementioned data.

The virtual clone can be generated by using meteorological and time data provided by the vehicle instrument control device 290 and/or the external system server 180, including but not limited to information such as wind direction, wind speed, wave height, sun position, moon position, precipitation, and cloud cover. Based on the aforementioned data, the virtual clone can draw the corresponding weather, day and night, and vehicle surface shadow conditions near the vehicle.

AIS data provided by the AIS data transfer device 270 or the external system server 180, and/or radar information provided by the vehicle instrument control device 290, allows the server 170 to obtain information such as the positions of other vehicles near the vehicle. When the server 170 learns the class of other vehicles and can access the 3D model of that class of vehicle in the data management layer 330, the virtual clone generation method can also generate virtual clones of other vehicles. In one embodiment, multiple virtual clones of vehicles can appear in the same 3D model or window to help the user understand the relationship between the positions of these vehicles. This is crucial for navigation safety. When server 170 is unable to generate virtual clones of other vehicles, it can generate markers of other vehicles near their location to alert that other vehicles are present.

The virtual avatar function can be used for training, allowing novice drivers to remotely observe experienced drivers navigating the vehicle and learn from their experience. This is especially useful in busy port areas and choke points. After an accident or emergency, replaying the virtual avatar image of the vehicle involved can quickly reconstruct the situation and clarify responsibility as soon as possible. The virtual avatar function can also be used for remote monitoring and instruction. When novice drivers are operating the vehicle, experienced drivers can remotely monitor their actions to prevent dangerous situations. The virtual clone function can also allow drivers in vehicles to quickly gain situational awareness in bad weather, so as to avoid collisions with other vehicles or terrain features.

Please refer to Figure 5, which is a schematic diagram of a navigation heat map according to an embodiment of this application. The area shown in Figure 5 is the southwestern waters of Taiwan, and the navigation heat map is formed by the historical navigation tracks of the applicant's fleet. Since each vehicle 110 transmits its position back to the server 170 for recording and storage, the server 170 can mark the position history of each vehicle 110 on the nautical chart. The denser the historical record points, or the higher the number of times a certain area is passed, the closer the color of that area on the nautical chart will be to a warm red, indicating that the frequency of vehicles appearing in that area is very high. Conversely, if a region has a very low historical frequency of vehicle appearances, its color on the nautical chart will tend towards cool colors like green or blue, indicating a low frequency of vehicle appearances in that area. In other words, the server 170 can color different areas of the map based on the frequency of vehicle appearances. Each color can be called a heat map, representing a certain range of vehicle appearance frequency. The colored map is called a heat map and is transmitted to the client 190 for user reference.

However, wind direction and tides change with the seasons. The trajectory of the same vehicle navigating between two ports may differ depending on the season. Furthermore, vehicles of different classes may have different trajectories in the same season due to their performance differences. Therefore, for voyages between two ports, server 170 can generate heatmaps based on the season and the vehicle's class. In other words, each vehicle class can correspond to a different heatmap at any given time.

Next, server 170 can apply the location of a vehicle of that class to a heat map of the same season for that class. In one embodiment, when the area where the location is located is too low in frequency or count on the heat map, it indicates that the vehicle has deviated from its usual course. Server 170 can therefore issue a warning to the user account of the vehicle's driver, the user account of the vehicle's supervisor, and/or other administrators. In another embodiment, server 170 can also issue a warning to the aforementioned user accounts when the distance between the location and an area above a certain frequency on the heat map exceeds a critical value, that is, when the distance from an area of a certain heat level is too far.

The data management layer 330 of the server 170 can contain vehicle-level data, as well as data on the vehicle's crew and their shore-based monitoring personnel. This data can include email accounts, instant messaging software accounts (such as Line, WhatsApp, etc.), phone numbers, radio communication device codes, etc. Off-track warnings can be transmitted via email, instant messaging, SMS, telephone, or radio voice messages. The aforementioned heat map can be attached to the warning message as reference data.

In one implementation, the aforementioned historical location records could include more information about the vehicle's load. The probability of generating error warnings would be further reduced when referring to thermal trajectory maps generated under the same season, class, and similar load.

The server 170 can include an alert module. Alert messages generated by different software or hardware modules can be sent, resent, periodically sent, recorded, and cleared through this module. Alert messages can include information such as alert message number, alert urgency, alert reason, alert user account, alert generation time, alert transmission method, alert transmission result, alert response result, and alert clearing time. Administrators can use the alert module to add, delete, modify, and query various alerts.

For example, after the server 170 receives the position of the vehicle, it can perform the aforementioned thermal trajectory map deviation judgment. When the judgment result is deviation, a warning message can be generated and sent to the aforementioned warning module for further processing.

The aforementioned heat map is generated based on the historical location trajectories of vehicles 110 managed by the vehicle management information system 100. In another embodiment, server 170 can obtain the location information of all vehicles within a certain range from external system server 180, some of which are not vehicles 110 managed by the vehicle management information system 100. For example, the location information of all vehicles within a certain range over a certain period of time can be used to form a heat map. From this heat map, the heat intensity of each area within that range can be determined.

Once a vehicle reports its location, server 170 can determine the heat level of the area where that location is located. If the heat level is too low, it indicates that other vehicles should not enter that area. This means the vehicle may have mistakenly entered a temporarily designated no-fly zone, an armed conflict zone, or a shallow, dangerous area. Conversely, if the heat level is too high, it indicates that the vehicle density in that area is too high, and the probability of a collision is too high. In either case, server 170 can issue a corresponding warning message.

Please refer to Figure 6, which is a schematic diagram of an electronic fence according to an embodiment of this application. Similar to Figure 5, the area shown in Figure 6 is the southwestern waters of Taiwan. The client 190 can use the electronic fence setting method to set one or more areas. As shown in Figure 6, the client 190 can directly select an area by clicking on vertices. Alternatively, an area can be set by inputting latitude and longitude coordinates, sequentially defining the entered locations. This area can be described as the fenced area enclosed by the electronic fence. Those skilled in the art will understand that the aforementioned fenced area can be a triangle, a quadrilateral, or other polygon. In another embodiment, the area described above can be circular or elliptical, and the client 190 can input the center and radius, or input two focal points and radii to set the enclosure of the electronic fence.

Next, the user can set one or more warning trigger events corresponding to the fenced area. For example, when the aforementioned fenced area is a no-fly zone announced by the military of various countries, a warning will be triggered and a corresponding warning message will be generated when the reported location of various vehicles 110 is within the fenced area. As mentioned earlier, the server 170 may include a warning module. After the electronic fencing function triggers a warning and generates a warning message, the warning message can be sent to the driver of the vehicle, the vehicle's supervisor, and relevant management personnel through the aforementioned warning module.

The announcements regarding no-fly zones are time-sensitive. Therefore, client 190 can set a time limit for the electronic fence. After the time limit expires, the electronic fence and its corresponding warning trigger settings will cease operation. Similarly, client 190 can also set the activation time for the electronic fence. Before the activation time, the electronic fence and its corresponding warning trigger settings will not activate.

In addition to users configuring the electronic fence and its corresponding warning trigger events via client 190, server 170 can also automatically configure the electronic fence and its corresponding warning trigger events. For example, server 170 can automatically receive government notices from external system server 180, such as Notices to Mariners and Notices to Airmen (NOTAM). Since these notices have a fixed format, and even machine-readable versions, server 170 can include parser software that can automatically parse the no-fly zones and related information published in these notices. Then, based on the scope of the aforementioned no-fly zone and the time period in which it was set, the electronic fence and its corresponding warning trigger events are automatically configured.

In one embodiment, the warning trigger event of the electronic fencing can be associated with the vehicle class. For example, areas with shallow water can be designated as shallow-slope electronic fencing. However, shallow-slope electronic fencing only applies to certain classes of vehicles 110 with deeper drafts, and not to other classes of vehicles 110 with smaller tonnages and shallower drafts.

In one embodiment, the warning triggering event of the electronic enclosure can be related to the vehicle's speed. For example, some countries may designate certain areas as habitats for marine mammals. To reduce the likelihood of marine mammals being injured by vehicles, these countries may require vehicles to reduce their speed to below a certain threshold when entering these areas. Therefore, speed-restricted enclosure areas can be established. When vehicle 110 reports its location within the enclosure and its speed exceeds the threshold, the corresponding warning for the speed-restricted enclosure area may be triggered.

Conversely, in areas where communication or power cables are laid, a minimum speed enclosure can be established to prevent vehicles from anchoring and breaking the cables. When the vehicle 110 reports its location within this enclosure and its speed exceeds a minimum speed limit, the corresponding warning for the minimum speed enclosure may be triggered.

In another embodiment, the warning triggering event of the electronic fencing can be related to the instrument status or readings on the vehicle. For example, some coastal countries stipulate that wastewater or ballast water cannot be discharged within a certain distance offshore. Therefore, a fencing area can be set up to prevent the discharge of wastewater or ballast water. When the vehicle instrument control device 290 on the vehicle 110 reports to the server 170 about the activation of the equipment for discharging wastewater or ballast water, the corresponding warning for the aforementioned fencing area preventing the discharge of wastewater or ballast water may be triggered.

Similarly, some coastal countries stipulate that high-sulfur fuels cannot be used within a certain distance from the port, and must be switched to low-sulfur fuels (0.5%) or alternative fuels. Therefore, a designated area for low-sulfur fuel conversion can be established. Since high-sulfur fuels require higher heating temperatures, low-sulfur fuels do not. Therefore, the temperature of the heated fuel can indicate whether high-sulfur or low-sulfur fuel is being used. When the vehicle instrument control device 290 on vehicle 110 reports to server 170 the outlet temperature and/or viscosity readings of the fuel heaters for the vehicle's main unit, generator, and/or boiler, it can be determined whether vehicle 110 has switched to low-sulfur fuel. When vehicle 110 enters the aforementioned enclosure area for switching to low-sulfur fuel, and the fuel heater outlet temperature and/or viscosity readings still indicate that the switch to low-sulfur fuel has not yet been made, the corresponding warning for the aforementioned enclosure area for switching to low-sulfur fuel may be triggered.

After vehicle 110 leaves the port area, it must rely on the satellite network to communicate with server 170. Due to the limited bandwidth of satellite communication, vehicle 110 encounters difficulties when it needs to simultaneously transmit all the video footage captured by multiple surveillance cameras 282 to server 170. Therefore, the surveillance camera server 280 included in vehicle 110 can handle this processing. For example, surveillance camera server 280 can extract a segment of video or a single image from each surveillance camera 282 in a round-robin manner and transmit it to server 170 via the satellite network. The server 170 may have a monitoring screen server module to receive processed images transmitted from the monitoring screen vehicle server 280 on each vehicle 110 and store them in the data management layer 330. The vehicle monitoring images received by the monitoring screen server module may include videos or images captured by each monitoring camera 282, but their update interval or frame rate is lower than the update rate captured by the monitoring camera 282. In this application, the vehicle images received by the monitoring screen server module may be referred to as low-update-rate images or low-update-rate vehicle images.

Those skilled in the art will understand that, in addition to reducing the update rate to reduce the satellite communication bandwidth used, the resolution can also be reduced to reduce the bandwidth used. However, regardless of whether the resolution is reduced, the images of the vehicle received by the monitoring screen server module can all be low-refresh-rate images.

As previously mentioned, the network bandwidth between vehicle 110 and the high-orbit communication satellite galaxy telecommunications network 135 can be fixed. Since this communication is the communication bottleneck between the monitoring vehicle server 280 and the monitoring server module, this fixed bandwidth can be regarded as the network bandwidth between the monitoring vehicle server 280 and the monitoring server module.

Within a fixed bandwidth, a portion of the bandwidth can be pre-configured for the transmission of the aforementioned low-refresh-rate images. Those skilled in the art will understand that, in one embodiment, the vehicle's internal network 210, internal wired network 220, internal wireless network 230, and external network router 240 can support this pre-configured bandwidth setting function through network settings. The monitoring vehicle server 280 can configure the refresh rate of the images uploaded to each monitoring camera 282 on the server 170 according to the aforementioned pre-configured bandwidth setting.

For example, if the bandwidth allocated to low-refresh-rate image transmission is fixed at 10 MBytes/second, and the carrier 110 has ten surveillance cameras 282, with each surveillance camera 282 transmitting approximately 10 MBytes of video or image data, then the surveillance image carrier server 280 can transmit the video or image data of one surveillance camera 282 per second, completing a round of transmission of video or image data from all ten surveillance cameras 282 every ten seconds. Therefore, the average image refresh rate of each surveillance camera 282 is 0.1 frames per second.

In one embodiment, the monitoring screen service module of the server 170 can be a three-layer structure as shown in Figure 2. In another embodiment, the monitoring screen service module can have specific and/or independent software and hardware to have dedicated network bandwidth, and can also include graphics processing hardware to accelerate image processing. For example, the monitoring screen service module can be a server cluster or a virtual server cluster.

Client 190 can request monitoring footage from a vehicle 110 from the monitoring video service module of server 170. When client 190 does not specify video from a monitoring camera 282 of vehicle 110, the monitoring video service module can provide low-refresh-rate images from multiple recently updated monitoring cameras 282 to client 190 in turn.

Please refer to Figure 7, which is a schematic diagram of a window 700 for viewing surveillance images of vehicle 110 on client 190 according to an embodiment of this application. In Figure 7, the display screen or window of client 190 shows low-refresh-rate images 710A~710F from multiple surveillance cameras 282 of a certain vehicle 110. The user can get a general understanding of the status of vehicle 110 through these low-refresh-rate images 710A~710F.

When client 190 specifies to view video from a particular surveillance camera 282 of the vehicle 110, the monitoring screen service module of server 170 can issue a command to the monitoring screen vehicle server 280 of the vehicle 110, instructing the monitoring screen vehicle server 280 to send images with a higher or normal update rate to the monitoring screen service module. During this period, the monitoring screen vehicle server 280 may choose not to send low-refresh-rate images from the other surveillance cameras 282 initially, or only send low-refresh-rate images from the other surveillance cameras 282 if there is sufficient bandwidth. In this way, the update rate of the images from the other surveillance cameras 282 will be even lower. In other words, the image transmission priority of the designated surveillance camera 282 is increased.

As previously mentioned, client 190 can issue PTZ commands to a monitoring camera 282 through the monitoring screen service module. The monitoring screen service module can forward the PTZ commands to the monitoring screen carrier server 280 of the carrier 110, causing the monitoring screen carrier server 280 to send images with a higher or normal update rate to the monitoring screen service module. In other words, the image transmission priority of the monitoring camera 282 that receives the PTZ commands is increased.

When the demand for image transmission increases, the carrier 110 can also additionally utilize the medium- and low-orbit communication satellite network 130 to support it. Therefore, low-priority, low-refresh-rate images can be transmitted through the medium- and low-orbit communication satellite network 130 without occupying the fixed bandwidth of the original high-orbit communication satellite network 135.

In addition to receiving instructions from the surveillance camera server module to increase the image transmission priority of a particular surveillance camera 282, the surveillance camera vehicle server 280 can also increase the image transmission priority of a particular surveillance camera 282 based on the situation captured by that surveillance camera 282. For example, the surveillance camera vehicle server 280 may include a vehicle intelligent image module, which uses the software and hardware of the surveillance camera vehicle server 280 to implement artificial intelligence to analyze the images of each surveillance camera 282 in order to achieve the aforementioned intelligent functions such as security monitoring and tracking. When an abnormality is detected in a surveillance camera 282, such as a pipe leak, fire, or the discovery of an unidentified person, the vehicle's intelligent imaging module can enable the surveillance camera vehicle server 280 to prioritize the image transmission of the surveillance camera 282 where the abnormality occurred. Furthermore, it can also notify the surveillance camera server module 170 of the abnormality and related information about the surveillance camera 282 (such as PTZ settings and viewpoint).

In another embodiment, the vehicle intelligent imaging module can be a computer connected to the vehicle server 280 that monitors the image, containing software and hardware for implementing the aforementioned artificial intelligence and intelligent functions such as security monitoring and tracking. The computer referred to here can be a computer similar to the aforementioned client 190, which will not be elaborated here.

The monitoring screen service module of server 170 can also have an artificial intelligence image monitoring module to realize artificial intelligence and analyze the low update rate images of each monitoring camera 282 in order to achieve the aforementioned intelligent functions such as security monitoring and tracking. When an abnormality is detected in a monitoring camera 282, such as a fire or the discovery of an unidentified person, the intelligent image module of server 170 can enable the monitoring screen carrier server 280 to increase the image transmission priority of the monitoring camera 282 where the abnormality occurred.

As mentioned earlier, since the intelligent imaging module of the server 170 can access the user personnel data of the data management layer 330, it can perform more artificial intelligence judgments. For example, the aforementioned driver's cab requires a licensed driver to be on duty, and certain instruments and equipment require licensed personnel to operate them.

Whether receiving an abnormal notification from the smart imaging module or the vehicle's smart imaging module, the monitoring screen service module of server 170 can generate a corresponding warning and issue it through the aforementioned warning module. The monitoring screen service module of server 170 can also issue a warning sound to the speaker of the corresponding monitoring camera 282, enabling those present to respond to the abnormal situation.

When multiple clients 190 need to access images from different surveillance cameras 282 on the same vehicle 110, or perform PTZ operations on different surveillance cameras 282 on the same vehicle 110, the surveillance video server module can schedule the requests of multiple clients 190 in sequence to prevent the fixed bandwidth from being exhausted by multiple image transmissions.

When a client 190 on a certain vehicle 110 needs to access the image of the monitoring camera 282 of the vehicle 110 through the server 170, or to perform PTZ operation on the monitoring camera 282 of the same vehicle 110, the monitoring image servo module can redirect the request of the client 190 to the monitoring image vehicle server 280 of the vehicle 110, so as to prevent the fixed satellite communication bandwidth from being exhausted by repeated image transmission.

Because vehicle 110 consumes a large amount of fossil fuels during movement, international regulations require the calculation of a Carbon Intensity Index (CII) for vehicle 110 to improve carbon fuel efficiency. In one embodiment, server 170 includes a CII calculation module that can calculate the CII for each vehicle 110 based on the amount of different fuels consumed by each vehicle 110 over a certain period of time and the carbon content of each fuel. For example, the CII for vehicle 110 can be calculated using months, quarters, or years as units.

Certain special containers or items carried by vehicle 110 require electrical power to maintain their temperature. For convenience, these special containers or items are collectively referred to as temperature-controlled containers in this application. The electricity consumed by the temperature-controlled containers is generated by the generator on vehicle 110, which burns fuel, thus increasing the carbon intensity index of vehicle 110. Therefore, when calculating the carbon intensity index of vehicle 110, the carbon emissions used to generate electricity to power the temperature-controlled containers can be deducted.

However, not all the electricity generated by the generator on vehicle 110 is supplied to the temperature-controlled cabinets; it is also supplied to other shipboard equipment. Vehicle 110 does not have a dedicated generator for the temperature-controlled cabinets. Therefore, please refer to Figure 8, which is a block diagram of a carbon footprint calculation information system 800 according to an embodiment of this application. The carbon footprint calculation information system 800 is used to calculate the carbon footprint report for each temperature-controlled cabinet, which can generate invoices for payment to the temperature-controlled cabinet owners and calculate the exempted carbon emissions from supplying the temperature-controlled cabinets.

The carbon footprint calculation information system 800 includes some components shown in the embodiments of Figures 1 and 2, which will not be described in detail here. The carbon footprint calculation information system 800 includes one or more temperature control cabinets 810. Each temperature control cabinet 810 corresponds to a power meter 820 for calculating the power consumption of that temperature control cabinet 810. The correspondence between the temperature control cabinets 810 and the power meters 820 can be recorded in the cargo loading data of the server 170. The vehicle instrument control device 290 can be connected to each power meter 820 to read the power consumption readings of the power meters 820. When a temperature control cabinet 810 is powered on during port loading, the vehicle instrument control device 290 can transmit the first reading of the power meter 820 to the server 170. When the temperature control cabinet 810 is powered off and unloaded at another port, the vehicle instrument control device 290 can transmit the second reading of the power meter 820 to the servo terminal 170. The difference between the second reading and the first reading is the power consumed by the temperature control cabinet 810 during transportation between the two ports.

The power supplied by the distributor 820 comes from the generator 840 (or generator set). In one embodiment, the oil consumption of the temperature control cabinet 810 can be calculated based on the typical power generation efficiency of the generator 840, such as the oil consumption required per kilowatt-hour, and thus the carbon emissions can be determined from the oil consumption. Accordingly, the client 190 can instruct the server 170 to provide the power consumed by the temperature control cabinet 810, and generate a carbon footprint report 890 for the temperature control cabinet 810 based on the preset oil-to-electricity conversion efficiency of the generator 840. Furthermore, an electricity bill can be generated for the owner based on the power consumed by the temperature control cabinet 810.

The server 170 can automatically transmit the carbon footprint report 890 and/or payment invoice electronically to the external system server 180 via the telecommunications network 150, so as to provide the owner with access to check the carbon footprint of the temperature control cabinet 810 and make payment.

The server 170 can also automatically generate an exemption carbon emission report 880 for the voyage based on the total power consumption of all temperature-controlled containers 810 between the two ports and the pre-set oil-to-electricity conversion efficiency of the generator 840. This exemption carbon emission report 880 can also be electronically transmitted to the external system server 180 via the telecommunications network 150 so that regulatory authorities can be informed of the exempted carbon emissions. The server 170 can also automatically transmit the exemption carbon emission report 880 to the carbon intensity index calculation module so that the carbon intensity index calculation module can exempt the vehicle from certain carbon intensity indicators based on the exemption carbon emission report 880.

In the embodiment shown in Figure 8, a fuel meter 850 may also be included to calculate the amount of fuel output from the fuel tank 860 to the generator, and a total meter 830 to calculate the total power generation of the generator 840. The vehicle instrument control device 290 can be connected to the total meter 830 and the fuel meter 850 to transmit their readings to the server 170. Accordingly, the server 170 can calculate the fuel-to-electricity conversion efficiency of the generator 840 based on the amount of fuel consumed during a certain flight and the total power generation, that is, the efficiency value of how many kilowatt-hours of electricity are generated for every amount of carbon emitted. When the actual fuel-to-electricity conversion efficiency value and electricity consumption can be used for calculation, the data of the aforementioned exempt carbon emission report 880 and temperature control cabinet carbon footprint report 890 can be more accurate and realistic.

Please refer to Figure 9, which is a flowchart illustrating a vehicle virtual clone generation method 900 according to an embodiment of this application. This vehicle virtual clone generation method 900 can be applied to the vehicle management information system 100 of Figure 1, particularly the server 170. Those skilled in the art will understand that the vehicle virtual clone generation method 900 can be implemented as multiple computer instructions and data stored in non-volatile memory. After the computer included in the server 170 executes the multiple computer instructions, the vehicle virtual clone generation method 900 can be implemented. This application does not limit the order in which any two steps are performed unless there is a direct or indirect causal relationship between them. The method 900 for generating a virtual clone of the vehicle can be started by step 910.

Step 910: Receive a read request from the virtual clone of the first vehicle 110 from the client 190. As previously mentioned, when the client 190 has a 3D model painter or browser, the client 190 may request to read a 3D model file at a certain time. When it does not have a 3D model painter or browser, the client 190 may request to read an image file at a certain time and from a certain viewpoint.

Optional Step 920: This step is optional. In this step, the weather information of the location and time of the first vehicle 110 is received from the external system server 180. This weather information can be used to describe the position of the sun, moon, stars, light, atmosphere, and ocean of the first vehicle 110 in the 3D model.

Step 930: The vehicle information and 3D model of the first vehicle 110 at that time can be read from the data management layer 330, and the 3D model of the virtual clone can be generated based on the vehicle information and 3D model of the first vehicle at that time. The aforementioned first vehicle information may include, but is not limited to, data that affects the external model of the first vehicle 110, such as heading, bow direction, speed, attitude, draft, cabin door opening status, radar activation status, crane status, etc. The 3D model of the vehicle can be combined with the meteorological information read in step 920 to generate the 3D model of the virtual clone.

Optional Step 932: This step is optional. This step can read the current cargo loading data of the first vehicle 110 from the data management layer 330 and modify the aforementioned 3D model of the virtual clone based on the cargo loading data. As mentioned earlier, the loading situation of the cargo on the first vehicle 110 can be described based on the cargo loading data. In one embodiment, the container color can be described based on the type of container. In another embodiment, the container color can be described based on the container's port of discharge.

Optional Step 934: This step is optional. This step can read the 3D model of the terrain and features at the current location of the first vehicle 110 from the data management layer 330, and correct the aforementioned 3D model of the virtual clone. This allows the user to view the relative situation of the first vehicle 110 and the nearby terrain and features through the 3D model.

Optional step 936: Following the optional step 920 above, when the corresponding meteorological information of the first vehicle can be obtained, the position of the sun, moon, stars, light, atmosphere and ocean of the first vehicle 110 can be described in the three-dimensional model based on the meteorological information.

Optional Step 940: Steps 940 and 945 are optional. This step determines whether there are other vehicles around the first vehicle 110. For example, it can determine whether there is at least one second vehicle 110 adjacent to the first vehicle 110 based on the information transmitted from the AIS information relay device 270 on the first vehicle 110 to the server 170, or the AIS information obtained from the external system server 180. When there are no other vehicles adjacent to the first vehicle 110, the process can proceed to step 950. Otherwise, the process can proceed to step 945.

Optional Step 945: Steps 940 and 945 are optional. Step 945 is similar to step 930. It reads the 3D model and vehicle information of at least one adjacent second vehicle 110, and modifies the 3D model of the virtual clone based on the 3D model and vehicle information of the at least one second vehicle. In this way, the 3D model of the virtual clone can obtain the 3D models of two vehicles 110 and their relative situations.

Optional step 950: Determine whether to output an image. As described in step 910, when client 190 has a 3D model painter or viewer, client 190 can request to read a 3D model file at a specific time, and the process can proceed to step 970. When client 190 does not have a 3D model painter or viewer, client 190 can request to read an image file at a specific time and viewpoint, and the process can proceed to step 960.

Optional Step 960: This step 960 is optional. This step can draw an image based on the viewpoint required by the reading in step 910 and the 3D model of the virtual clone, and then send the image to the client 170.

Step 970: Send the 3D model of the virtual clone to client 170. Based on this, client 170 can automatically draw the 3D model of the virtual clone and adjust the view angle, distance, and position on client 170. The painter or browser on client 170 can automatically draw the image based on the above drawing parameters and output it to the screen or printer for user reference.

Please refer to Figure 10, which is a flowchart illustrating a method 1000 for determining flight path deviation using a heat map according to an embodiment of this application. This method 1000 for determining flight path deviation using a heat map can be applied to the vehicle management information system 100 of Figure 1, particularly the server 170. Those skilled in the art will understand that this method 1000 can be implemented as multiple computer instructions and data stored in non-volatile memory. After the computer included in the server 170 executes these multiple computer instructions, the method 1000 for determining flight path deviation using a heat map can be implemented. This application does not restrict the order in which the two steps are performed if there is no direct or indirect causal relationship between them. The method 1000 for determining route deviation using a thermal trajectory map can be executed starting from step 1010.

Step 1010: Based on the historical location information of multiple vehicles 110 included in Class 1, generate a heat map of one segment for that class. Each of the aforementioned historical location information corresponds to that segment. Multiple vehicles 110 of the same class typically have the same power system and dynamic parameters. The aforementioned segment represents the segment from a first position to a second position, which can be a port, airport, etc. Those skilled in the art will understand that the segment from the first position to the second position differs from the segment from the second position to the first position due to different current and/or airflow directions. The aforementioned historical location information may include time and its corresponding location, and may also include cargo transport information (e.g., load weight). The heat map may contain multiple regions, and the heat of each region represents the frequency or number of times the historical location information is received. Next, the thermal trajectory map method 1000 can perform a main loop for judging the course deviation of vehicles of this class, and the process proceeds to step 1020.

Step 1020: Receive a position report from a vehicle of this class traveling in this segment. In one embodiment, the AIS information forwarding device 270 of the vehicle 110 can transmit AIS information to the server 170 via the access telecommunications network 120, the low-Earth orbit communication satellite galaxy telecommunications network 130, and the high-Earth orbit communication satellite galaxy telecommunications network 135 shown in FIG. 1. In another embodiment, the vehicle instrument control device 290 of the vehicle 110 can control navigation instruments such as inertial navigation instruments, astronomical navigation instruments, satellite navigation instruments, and radio communication satellite navigation instruments to transmit AIS information to the server 170 through the access telecommunications network 120, the low-to-medium orbit communication satellite galaxy telecommunications network 130, and the high-to-earth orbit communication satellite galaxy telecommunications network 135 shown in Figure 1. After receiving the location report, the server 170 knows that the location report corresponds to the aforementioned heat map because the data management layer 330 has information about the vehicle level.

Step 1030: Compare the location report with the heat map, using the heat information from the location report. In one embodiment, one of several regions on the heat map can be located first based on the location report. Then, the heat information for that region is obtained.

Step 1040: Determine if the popularity information is abnormal. In one embodiment, it can be determined whether the popularity information is below a low threshold value. When the popularity information is below the low threshold value, the process can proceed to step 1060. In another embodiment, it can be determined whether the popularity information is above a high threshold value. When the popularity information is above the high threshold value, the process can proceed to step 1060. In other words, in a certain embodiment, it can be determined whether the popularity information is within a normal range. When the popularity information is not within the normal range, the process can proceed to step 1060. When the heat information is determined to be within the normal range, the process can proceed to step 1050 or return to step 1020.

Optional Step 1050: This step is optional. Since the location report was determined to be normal in step 1040, this step allows you to add the location report to the corresponding historical location information for this level. This ensures that the current location report will be taken into account the next time a heatmap for this level is generated.

Step 1060: Based on the location report and the thermal trajectory map, generate a warning message indicating deviation from the trajectory. This warning message can be sent to the warning module. Then, the process can proceed to optional step 1070, or directly to step 1080.

Optional Step 1070: This step is optional. Since the vehicle may remain in the area for a period of time, multiple position reports will be issued during this period, triggering multiple warnings. Therefore, this step can determine whether a corresponding deviation warning message has been issued. If a corresponding deviation warning message has been issued, the process can return to step 1020. If no corresponding deviation warning message has been issued, the process can proceed to step 1080.

Step 1080: The deviation warning message is transmitted to the client 190 of the relevant personnel on the vehicle. As mentioned earlier, the relevant personnel on the vehicle may include the driver and administrators located on the vehicle, or monitoring personnel on shore. In addition to the client 190 of the relevant personnel, the warning message can also be transmitted to the computers of these relevant personnel, such as mobile phones or satellite phones, via SMS, email, multimedia messages, voice messages, video messages, instant messaging, etc. The process then returns to step 1020 to receive the next position report from the vehicle.

When managing vehicle navigation, historical experience is often relied upon. The method for determining route deviation using heat map provided in this application summarizes empirical rules into a heat map, allowing for a general assessment of whether the navigation trajectory is normal based on historical experience of different classes, seasons, and/or load classes. When the navigation trajectory deviates from the historically established course, timely warnings can be issued to relevant personnel.

Please refer to Figure 11, which is a flowchart illustrating an electronic fence setting method 1100 according to an embodiment of this application. This electronic fence setting method 1100 can be applied to the vehicle management information system 100 of Figure 1, particularly the server 170. Those skilled in the art will understand that the electronic fence setting method 1100 can be implemented as multiple computer instructions and data stored in non-volatile memory. The computer included in the server 170 executes these multiple computer instructions to implement the electronic fence setting method 1100. This application does not limit the order in which any two steps are performed unless there is a direct or indirect causal relationship between them. The electronic fence setup method 1100 can be started from step 1110.

Step 1110: Receive at least three coordinates to set up an electronic fence based on those coordinates. In another embodiment, the center coordinates and radius can be received to set up a circular or cylindrical electronic fence. In yet another embodiment, the two foci and radius of an ellipse can be received to set up an elliptical or elliptical cylindrical electronic fence. Those skilled in the art will understand that the above-described electronic fence can be a combination of intersections or unions of multiple shapes. In one embodiment, the coordinates can be received from the electronic fence setting program on client 190. In another embodiment, the coordinates can be received from an external system server 180. For example, receiving notifications of no-fly zones from official websites of various countries may include the longitude and latitude of the coordinates of each vertices in the no-fly zone in clockwise or counterclockwise order, and may also include the start and end times.

In some embodiments, the coordinates described above only include longitude and latitude, and the electronic fence is a region projected onto the Earth's surface. In other embodiments, in addition to longitude and latitude, the coordinates may include an elevation range. For example, a no-navigation zone may be set from sea level to an altitude of 50,000 feet. When the coordinates include an elevation range, the electronic fence described above can be a three-dimensional electronic fence, rather than just an electronic fence projected onto the Earth's surface.

Optional Step 1120: This step is optional. This step is used to receive the corresponding start time and/or end time of the electronic fence from the client 190 or the external system server 180. In some embodiments, the start time and/or end time of the electronic fence can be indefinite. Regardless of its representation, logically, the electronic fence can start indefinitely or end indefinitely.

Optional step 1130: This step is used to receive setting parameters from the client 190 for the instrument readings of the electronic fence corresponding to the vehicle. As mentioned earlier, when the electronic fence is associated with readings of certain instruments on the vehicle, these setting parameters can be received from the electronic fence setting program of the client 190. That is, when the instrument readings of the vehicle 110 fall within the range of these setting parameters, a warning message can be triggered. In one embodiment, when certain instruments are specific to a certain class of vehicle, it means that the electronic fence is associated with that class and not with other classes. In another embodiment, the electronic fence can be associated with multiple readings from multiple instruments.

Step 1140: Set the warning message for the electronic fence. The electronic fence can be associated with the start time, end time, setting parameters, and multiple coordinates as described above.

In one embodiment, the warning message may contain control commands. For example, control commands may be issued to a certain instrument or device of the vehicle 110.

Step 1150: Store the electronic fence and its corresponding information. In the embodiments shown in Figures 1 and 3, the electronic fence setting method 1100 running in the business logic layer 320 of the server 170 can store the electronic fence and its corresponding information in the data management layer 330.

Optional Step 1160: This step is optional. This step is used to transmit the electronic fence and its corresponding information to the client 190. Upon receiving the electronic fence, the client 190 can display the fence's perimeter and its corresponding information on a map or nautical chart.

Please refer to Figure 12, which is a flowchart illustrating an electronic fence warning method 1200 according to an embodiment of this application. This electronic fence warning method 1200 can be applied to the vehicle management information system 100 of Figure 1, particularly the server 170. Those skilled in the art will understand that the electronic fence warning method 1200 can be implemented as multiple computer instructions and data stored in non-volatile memory. The electronic fence warning method 1200 can be implemented after the computer included in the server 170 executes the multiple computer instructions. This application does not limit the order in which any two steps are performed unless there is a direct or indirect causal relationship between them. Electronic fence warning method 1200 can be started from step 1210.

Step 1210: Receive a position report from a vehicle 110. In one embodiment, this step may also receive one or more instrument reading reports from the vehicle 110, such as readings reported by the vehicle instrument control device 290. In one embodiment, the position report of the vehicle 110 may not originate from the vehicle 110 itself, but may be obtained from an external system server 180.

Step 1220: Determine whether the vehicle's reported location corresponds to at least one electronic fence. That is, whether the reported location is within the area of an electronic fence. If it is within the area of the electronic fence, the process can proceed to step 1230. If the location is not associated with any electronic fence, the process can return to step 1210.

Step 1230: Determine whether to trigger a warning message for the at least one electronic fence. When one or more instrument reading reports from the carrier 110 are received in step 1210, and the reading range falls within the set parameter range of the at least one electronic fence, and the location report time falls within the start and end times, a warning message for the electronic fence will be triggered. In other words, when the location, time, instrument readings, and other information reported correspond to the at least one electronic fence, the process will trigger a warning message and can proceed to step 1240 or step 1250. If any of the reported location, time, or instrument reading does not correspond to the information associated with the at least one electronic fence, the process can return to step 1210.

Optional Step 1240: This step is optional. This step is used to determine whether a corresponding warning message has been issued. Since the vehicle may remain in the area for a period of time, multiple location reports will be issued during this period, triggering multiple warnings. Therefore, this step can determine whether a corresponding electronic fencing warning message has been issued. If a corresponding electronic fencing warning message has been issued, the process can return to step 1210. If no corresponding deviation from the track warning message has been issued, the process can proceed to step 1250.

Step 1250: The warning message from the electronic fence is transmitted to the client terminals of the relevant personnel on the vehicle. As mentioned earlier, the relevant personnel on the vehicle may include the driver and management personnel located on the vehicle, or monitoring personnel on shore. In addition to the client terminals of the aforementioned relevant personnel, the warning message can also be transmitted to their computers, such as mobile phones or satellite phones, via SMS, email, multimedia messages, voice messages, video messages, instant messaging, etc. The process then returns to step 1210 to receive the next location report from the vehicle.

In one embodiment, the warning message may contain a control command issued to a certain instrument device of the vehicle 110. In this embodiment, step 1250 may transmit the warning message to the corresponding vehicle instrument control device 290 of the vehicle 110, so that it executes the control command issued by the warning message.

In one embodiment, the electronic fence setting method 1100 shown in FIG11 can be executed earlier than the electronic fence warning method 1200 shown in FIG12. In this embodiment, an electronic fence processing method is provided, which sequentially includes the aforementioned electronic fence setting method 1100 and electronic fence warning method 1200.

Please refer to Figure 13, which is a flowchart illustrating a satellite image processing method 1300 according to an embodiment of this application. This satellite image processing method 1300 can be applied to the vehicle management information system 100 of Figure 1, particularly the monitoring vehicle server 280. Those skilled in the art will understand that the satellite image processing method 1300 can be implemented as multiple computer instructions and data stored in non-volatile memory. After the computer included in the monitoring vehicle server 280 executes these multiple computer instructions, the satellite image processing method 1300 can be implemented. This application does not limit the order in which the two steps are performed if there is no direct or indirect causal relationship between them. The satellite-transmitted image processing method 1300 may be executed starting from step 1310.

Step 1310: Calculate the low update rate for each surveillance camera based on the minimum fixed bandwidth of the leased satellite galaxy telecommunications network and the number and resolution of the multiple surveillance cameras 282. The size of each round of data transmission can be calculated from the number and resolution of the multiple surveillance cameras 282. Based on the ratio of the desired data transmission size to the minimum fixed bandwidth, the time required to transmit one round of data can be calculated; this is the update rate for each surveillance camera. Since this update rate should be lower than the normal recording update rate of each surveillance camera, it is called the low update rate. In one embodiment, the satellite galaxy telecommunications network can be the high-orbit communication satellite galaxy telecommunications network 135 shown in Figure 1. However, this application does not limit it to any particular type of satellite galaxy telecommunications network; it can also be a medium- or low-orbit communication satellite galaxy telecommunications network 130, as long as the satellite galaxy telecommunications network can guarantee a minimum fixed bandwidth. The process can proceed to step 1320 or step 1330.

Optional step 1320: Utilize artificial intelligence to monitor the images transmitted from the multiple surveillance cameras at a normal update rate. As previously mentioned, the surveillance video carrier server 280 may include an artificial intelligence image recognition module for monitoring the images transmitted from the multiple surveillance cameras at a normal update rate. This artificial intelligence image recognition module can monitor various abnormal situations, such as fires, pipeline leaks, personnel falling into the sea, and personnel entering or leaving cabins. When the artificial intelligence image recognition module detects an abnormality in the image from a particular surveillance camera, it will receive a specified request from the artificial intelligence image recognition module.

Optional step 1325: Determine if a request has been received from the AI image recognition module to transmit the image from the monitoring camera that detected the image abnormality to the server 170. If the request is received, the process can proceed to step 1340. If no request is received, the process can proceed to step 1330.

Step 1330: Determine if a specified request has been received from server 170. In one embodiment, client 190 may issue a specified request for a particular surveillance camera 282 through server 170, and may also send PTZ commands. In another embodiment, server 170 may also have an AI image recognition module to automatically monitor abnormalities in low-refresh-rate images from multiple vehicles, such as monitoring unauthorized personnel operating instruments or entering unauthorized compartments. When an abnormality is detected, server 170 will issue a specified request for a particular surveillance camera 282. Based on this, the process can proceed to step 1335 or step 1340. When it is determined that no specified request has been received from server 170, the process can proceed to step 1360.

Optional step 1335: Determine whether the client 190 issuing the specified request and/or PTZ command originates from the same vehicle 110. That is, determine whether the specified request received in step 1330 originates from the same vehicle 110. When the specified request and/or PTZ command is issued by the client 190 of the same vehicle 110, the process can proceed to step 1350. Otherwise, the process proceeds to step 1340.

Step 1340: Transmit the high-refresh-rate video from the surveillance camera 282 corresponding to the specified request to the server 170 via the satellite galaxy telecommunications network. The high refresh rate referred to here is higher than the aforementioned low refresh rate, but less than or equal to the normal refresh rate of the surveillance camera 282. In one embodiment, the sound received by the audio module or microphone of the surveillance camera 282 can be transmitted to the server 170 via the satellite galaxy telecommunications network before the video data. The specified request from the server 170 may also include voice information, which can be played through the loudspeaker or speaker of the surveillance camera 282. After the specification is completed, the process can return to step 1320 or step 1360.

Step 1350: The image from the designated surveillance camera is transmitted via the vehicle's internal network 210 to the client 190 within the same vehicle 110. Voice messages sent by the client 190 can be played through the speaker or loudspeaker of the surveillance camera 282. Sound received by the microphone or radio module of the surveillance camera 282 can be transmitted to the speaker or loudspeaker of the client 190 for playback. PTZ commands sent by the client 190 can also be transmitted via the vehicle's internal network 210. Through steps 1335 and 1350, the user of client 190 does not need to consider in advance whether he or she is on the same vehicle 110 as the designated surveillance camera 282, and can seamlessly obtain the image of the surveillance camera 282 from the nearest location without wasting the bandwidth of the satellite galaxy telecommunications network.

Step 1360: Transmit low-refresh-rate images from all monitoring cameras 282 on vehicle 110 to server 170 in turn via the satellite galaxy's telecommunications network. Those skilled in the art will understand that step 1360 can be interrupted at any time by a specified request from server 170, or by a specified request from the artificial intelligence image recognition module.

Please refer to Figure 14, which is a flowchart illustrating a satellite image processing method 1400 according to an embodiment of this application. This satellite image processing method 1400 can be applied to the vehicle management information system 100 of Figure 1, particularly the server 170. Those skilled in the art will understand that the satellite image processing method 1400 can be implemented as multiple computer instructions and data stored in non-volatile memory. The satellite image processing method 1400 can be implemented by the computer included in the server 170 executing the multiple computer instructions. This application does not limit the order in which any two steps are performed unless there is a direct or indirect causal relationship between them. Satellite image processing method 1400 can be started from step 1410.

Step 1410: Receive low-refresh-rate images from multiple monitoring cameras 282 on one or more carriers 110 via a satellite galaxy telecommunications network. This step corresponds to step 1360 shown in Figure 3. A description of the satellite galaxy telecommunications network can be found in step 1310. This step may include storing the aforementioned low-refresh-rate images in the data management layer 330 for later retrieval. The images can also be played on the screen of the console on the server 170 or the screen of the client 190. The process can proceed to optional steps 1420 or 1425.

Optional step 1420: Utilize artificial intelligence to monitor the low-refresh-rate images of the multiple monitoring cameras 282. This step is used to enable the artificial intelligence image monitoring module of the server 170 to remotely monitor the abnormal status of these low-refresh-rate images. If an abnormality is detected in the image of a certain monitoring camera 282, a specified request will be issued, causing the monitoring image carrier server 280 of that vehicle to transmit the high-refresh-rate image of that monitoring camera 282.

Step 1425: Determine if a specified request has been received. This specified request can originate from a client 190 or from the aforementioned AI video monitoring module. If a specified request is received, the process can proceed to step 1430. If no specified request is received, the process can proceed to the optional step 1490 or return to step 1410. The specified request may also include a PTZ command.

Step 1430: Send the specified request to the vehicle's monitoring screen vehicle server 280. This step corresponds to step 1330 in Figure 13.

Step 1440: Receive the high-refresh-rate images from the monitoring camera 282 corresponding to the specified requirements from the monitoring camera server of the vehicle via the satellite galaxy telecommunications network.

Step 1450: Transmit the high-refresh-rate image to the specified source. As described in step 1425, when the specified source is client 190, the high-refresh-rate image can be transmitted to client 190. When the specified source is the aforementioned AI image monitoring module, the high-refresh-rate image can be transmitted to the aforementioned AI image monitoring module. In one embodiment, this step may include storing the high-refresh-rate image in the data management layer 330 for later retrieval. It can also be played on the screen of the main console on the server 170.

In one embodiment, steps 1440 and 1450 can be performed simultaneously, meaning that the server 170 receives high-refresh-rate images from the carrier 110 while simultaneously transmitting the received high-refresh-rate images. In one embodiment, in addition to the high-refresh-rate images, the client 190 can receive audio data from the designated surveillance camera 282, and the audio data emitted by the client 190 can also be transmitted to the designated surveillance camera 282 for playback. PTZ commands issued by the client 190 can also be transmitted to the designated surveillance camera 282 for execution. The process can then proceed to the optional step 1460, or, after the specified requirements are completed, jump back to step 1410 from the loop of steps 1440 and 1450.

Optional step 1460: Monitor the high-refresh-rate image using artificial intelligence. Regardless of whether the source of the specified request is the aforementioned artificial intelligence image monitoring module or the monitoring screen from the vehicle server 280 of the vehicle 110, the server 170 can enable the aforementioned artificial intelligence image monitoring module to monitor the high-refresh-rate image. In one embodiment, steps 1440, 1450, and 1460 can be performed simultaneously, meaning that the server 170 can receive the high-refresh-rate image from the vehicle 110, transmit the received high-refresh-rate image, and simultaneously enable the aforementioned artificial intelligence image monitoring module to monitor the high-refresh-rate image.

Optional step 1470: Determine if the high update rate image is abnormal. If an abnormality is found in the high update rate image, the process can proceed to step 1480. Otherwise, the process can return to the loop of steps 1440, 1450, and 1460.

Step 1480: Server 170 can generate a warning message based on the abnormal situation and transmit the warning message to the client of the relevant personnel in the vehicle. As mentioned above, the relevant personnel in the vehicle may include the driver and management personnel located in the vehicle, or the monitoring personnel on shore. In addition to the client of the aforementioned relevant personnel, the warning message can also be transmitted to the computers of these relevant personnel, such as mobile phones or satellite phones, through SMS, email, multimedia messages, voice messages, video messages, instant messaging, etc.

Optional step 1490: Determine whether a high-refresh-rate image has been actively sent by vehicle 110. This step corresponds to steps 1325 and 1340 shown in Figure 13. When the AI image monitoring module of the monitoring vehicle server 280 detects an anomaly in the image of a certain monitoring camera 282 in step 1320, it can actively send the high-refresh-rate image of that monitoring camera 282 to the server 170 in step 1340. When a high-refresh-rate image is received from vehicle 110, the process can enter the loop of steps 1440, 1450, and 1460. If no high update rate image is received from vehicle 110, the process can return to step 1410.

Please refer to Figure 15, which is a flowchart illustrating a cargo carbon footprint calculation method 1500 according to an embodiment of this application. This cargo carbon footprint calculation method 1500 can be applied to the vehicle management information system 100 of Figure 1, particularly the server 170. Those skilled in the art will understand that the cargo carbon footprint calculation method 1500 can be implemented as multiple computer instructions and data stored in non-volatile memory. The computer included in the server 170 executes these multiple computer instructions to implement the cargo carbon footprint calculation method 1500. This application does not limit the order in which any two steps are performed unless there is a direct or indirect causal relationship between them. The cargo carbon footprint calculation method 1500 can be started from step 1510.

Step 1510: Receive a first reading from a power meter 820 on a carrier 110. This first reading can be taken when the power-consuming line calculated by the power meter 820 is connected to a load, that is, when the goods are powered on. The power meter 820 can be a smart meter, capable of transmitting the first reading to the server 170 via power lines or other data lines. Those skilled in the art will understand that the first reading can be received earlier than the receiving time in this step.

Optional step 1512: Receive the first main meter reading from a main meter 830 of the carrier 110. The main meter 830 may be a smart meter capable of transmitting the first main meter reading to the server 170 via power lines or other data lines. Those skilled in the art will understand that the time of receiving the first reading can differ from the time of receiving the first main meter reading by a certain time interval. For example, the difference could be within a few minutes or an hour.

Optional step 1514: Receive a first fuel reading from a fuel meter 850 of the generator 840 of the vehicle 110. This fuel meter may be a smart fuel meter capable of transmitting the first fuel reading to a server 170 via a data line. Those skilled in the art will understand that the time it takes for the first main meter reading to be received can differ from the time it takes for the first fuel reading by a certain time interval. For example, the difference could be within a few minutes or an hour.

Step 1520: Receive the second reading from the power meter 820. This second reading can be taken when the power-consuming line calculated by the power meter 820 is unloaded, that is, when the goods are unloaded.

Optional step 1522: Receive the second main meter reading from the main meter 830. Those skilled in the art will understand that the time of the second reading can differ from the time of the second main meter reading by a certain time interval. For example, it can differ by a few minutes or an hour.

Optional step 1524: Receive the second fuel reading from the fuel meter 850. Those skilled in the art will understand that the time of receipt of the second main meter reading can differ from the time of receipt of the second fuel reading by a certain time interval. For example, the difference can be within a few minutes or an hour.

Step 1530: Calculate the power consumption of the sub-meter 820 based on the difference between the second reading and the first reading.

Step 1540: Based on the cargo loading data of the vehicle 110, find the cargo corresponding to the power meter 820.

Optional step 1550: Calculate the ratio of electricity consumption to carbon emissions of the vehicle based on the readings of the first total electricity meter, the second total electricity meter, the first fuel meter, and the second fuel meter. The difference between the first and second total electricity meter readings represents the total electricity generation of the generator, and the difference between the first and second fuel meter readings represents the total fuel consumption of the generator, which can also be converted into total carbon emissions. The ratio of electricity consumption to carbon emissions of the vehicle can be calculated accordingly. Those skilled in the art will understand that when steps 1512, 1514, 1522, 1524, and 1550 are omitted in the cargo carbon footprint calculation method 1500, the aforementioned ratio of electricity consumption to carbon emissions can be measured beforehand.

Step 1560: Calculate the carbon footprint of the cargo, that is, the carbon emissions used to transport the cargo, based on the ratio of the vehicle's electricity consumption to carbon emissions and the corresponding electricity consumption of the cargo.

Optional step 1570: Generate a carbon footprint report and/or electricity bill for the cargo based on its carbon footprint, and send it to the cargo owner's external system server 180.

In one embodiment, to ensure that the above readings are taken during loading or unloading of goods, after receiving the readings, the position of the vehicle corresponding to the reading time can be considered. The readings are valid only when the vehicle is within the loading or unloading point. For example, the readings received in steps 1510, 1512, and 1514 are valid only if the vehicle is within a certain range of the loading point at the time of reading. Similarly, the readings received in steps 1520, 1522, and 1524 are valid only if the vehicle is within a certain range of the unloading point at the time of reading.

Please refer to Figure 16, which is a flowchart illustrating a vehicle carbon emission exemption calculation method 1600 according to an embodiment of this application. This vehicle carbon emission exemption calculation method 1600 can be applied to the vehicle management information system 100 of Figure 1, particularly the server 170. Those skilled in the art will understand that the vehicle carbon emission exemption calculation method 1600 can be implemented as multiple computer instructions and data stored in non-volatile memory. After the computer included in the server 170 executes the multiple computer instructions, the vehicle carbon emission exemption calculation method 1600 can be implemented. This application does not limit the order in which any two steps are performed unless there is a direct or indirect causal relationship between them. The vehicle carbon emission exemption calculation method 1600 can be started from step 1610.

Step 1610: Based on the cargo loading data of a vehicle 110, obtain a list of all cargoes for which carbon footprints should be calculated. The cargo list includes one or more cargoes that require power supplied by the generator 840 of the vehicle 110 during transport.

Step 1620: For each item in the shipment list, perform the shipment carbon footprint calculation method 1500 described above to obtain multiple carbon footprint reports. The multiple carbon footprint reports described above can be obtained in step 1560 of Figure 15.

Step 1630: Based on the multiple carbon footprint reports, generate the carbon emission exemption value. The carbon emissions of all goods included in the cargo manifest can be summed to determine the carbon emission exemption for vehicle 110.

According to one embodiment of this application, a method for generating a virtual clone of a vehicle is provided, comprising: receiving a read request for a virtual clone of a first vehicle from a client; reading the vehicle information and three-dimensional model of the first vehicle at that time, and generating a three-dimensional model of the virtual clone based on the vehicle information and three-dimensional model of the first vehicle at that time; and outputting the three-dimensional model of the virtual clone to the client.

Furthermore, in order to depict the apparent state of the first vehicle at that time, the three-dimensional model of the virtual clone is used to represent the apparent state of the vehicle information, wherein the vehicle information includes one or any combination of the following: the on-state of the rotating radar; the pointing angle of the dish communication antenna; the on-state of the external cabin door; the state of the anchor chain; the configuration state of the lifeboat; and the state of the crane.

Furthermore, in order to depict the weather conditions at the time of the first vehicle, the method for generating the virtual clone of the vehicle further includes: receiving weather information corresponding to the location and time of the first vehicle from an external system server; and correcting the three-dimensional model of the virtual clone based on the corresponding weather information of the first vehicle.

Furthermore, in order to depict the cargo loaded by the first vehicle at that time, the method for generating the virtual clone of the vehicle further includes: reading the cargo loading data of the first vehicle at that time; and correcting the three-dimensional model of the virtual clone based on the cargo loading data.

Furthermore, in order to depict the types of goods carried by the first vehicle at that time, the multiple goods carried by the first vehicle were of different colors according to their types.

Furthermore, in order to depict the unloading destination of the cargo carried by the first vehicle at that time, the multiple cargoes carried by the first vehicle are different colors according to their different unloading destinations.

Furthermore, in order to depict the terrain and features near the first vehicle, the method for generating the virtual clone of the vehicle further includes: reading the three-dimensional model of the terrain and features at the current location of the first vehicle, and correcting the three-dimensional model of the virtual clone.

Furthermore, in order to depict other vehicles near the first vehicle, the method for generating the virtual clone of the vehicle further includes: determining whether the first vehicle is adjacent to other vehicles; and when the first vehicle is adjacent to a second vehicle, reading the three-dimensional model of the second vehicle, and correcting the three-dimensional model of the virtual clone based on the three-dimensional model of the second vehicle.

Furthermore, in order to depict the state of the second vehicle, the method for generating a virtual clone of the vehicle further includes: reading the vehicle state of the at least one second vehicle, and modifying the three-dimensional model of the virtual clone according to the vehicle state of the at least one second vehicle, wherein the three-dimensional model of the virtual clone is used to represent the explicit state of the vehicle information of the second vehicle.

Furthermore, in order to depict the virtual clone of the first vehicle in real time, the method for generating the virtual clone of the vehicle further includes: after receiving the read request of the virtual clone, receiving the vehicle information of the first vehicle at that time from the first vehicle.

Furthermore, in order to receive information from a remote first vehicle, wherein the aforementioned vehicle information received from the first vehicle at the time of receipt is transmitted through a satellite network.

Furthermore, in order to support clients that lack the ability to draw 3D models, the method for generating a virtual clone of a vehicle further includes: drawing a 3D model of the virtual clone to generate an image; and outputting the image to the client.

Furthermore, to support the client's ability to adjust the viewpoint, the image is drawn based on viewpoint information transmitted by the client.

According to one embodiment of this application, a server is provided for implementing the above-described vehicle virtual clone generation method, comprising: a network device for connecting to the client; and a processor connected to the network device for executing a plurality of instructions stored in non-volatile memory to implement the above-described vehicle virtual clone generation method.

According to one embodiment of this application, a vehicle management information system is provided that implements the above-described method for generating virtual vehicle clones, comprising: the server; the client; and the first vehicle.

Through the above embodiments, the vehicle virtual clone generation method provided in this application can be used for education and training, allowing novice drivers to remotely observe the navigating conditions of experienced drivers and learn from their experience. This is particularly useful in busy port areas and choke points. After an accident or emergency, replaying the virtual clone image of the vehicle involved in the accident can quickly reconstruct the situation at the time and clarify responsibility as soon as possible. The virtual clone function can also be used for remote monitoring and teaching. When novice drivers are operating the vehicle, experienced drivers can remotely monitor the novice drivers' operations to prevent danger. The virtual clone function can also allow drivers in vehicles to quickly gain situational awareness in bad weather, so as to avoid collisions with other vehicles or terrain features.

According to one embodiment of this application, a method for determining route deviation using a thermal trajectory map is provided, comprising: generating a thermal trajectory map of a class for a segment based on multiple historical position information of multiple vehicles included in a class; receiving a position report of a vehicle of the class navigating the segment; comparing the position report with the thermal trajectory map, and determining whether the thermal information is abnormal; and generating a deviation warning message when the thermal information is determined to be abnormal.

Furthermore, in order to determine whether the popularity information is abnormal, the determination of whether the popularity information is abnormal includes one or any combination of the following: determining whether the popularity information is lower than a low threshold value; and determining whether the popularity information is higher than a high threshold value, wherein when the popularity information is lower than the low threshold value or the popularity information is higher than the high threshold value, the popularity information is determined to be abnormal.

Furthermore, in order to accumulate more historical location information, when the heat information is determined to be normal, the location report is added to the historical location information of that level for that flight segment.

Furthermore, in order to send the warning message to the relevant personnel, the method for determining the flight path deviation using thermal trajectory maps further includes: transmitting the deviation warning message to the client of the relevant personnel of the vehicle.

Furthermore, in order to address the issue of deviation from the trajectory in a timely manner, the method for determining the flight path deviation using a thermal trajectory map further includes: transmitting the warning message to the computer of the relevant personnel on the vehicle using one of the following transmission methods or any combination thereof, wherein the transmission methods include SMS, email, multimedia message, voice message, video message and instant messaging.

Furthermore, in order to deliver the warning message to the correct personnel, including the driver and management personnel located in the vehicle, as well as supervisory personnel not on the vehicle.

Furthermore, in order to avoid repeatedly issuing deviation warning messages, the method for determining flight path deviation using thermal trajectory maps further includes: determining whether a corresponding deviation warning message has already been issued; and when it is determined that no corresponding deviation warning message has been issued, then transmitting the deviation warning message to the client of the relevant personnel of the vehicle.

Furthermore, in order to promptly determine whether the trajectory has deviated, the aforementioned position report is transmitted via a satellite constellation telecommunications network.

Furthermore, different navigation trajectories are generated in order to adapt to the changes in the natural environment in different seasons, and the above-mentioned historical location information corresponds to the same time period of the location report.

Furthermore, in order to adapt to different cargo carrying conditions, different navigation trajectories are generated, wherein the cargo carrying capacity level corresponding to the above-mentioned multiple historical location information corresponds to the cargo carrying capacity level corresponding to the location report.

According to one embodiment of this application, a server is provided that implements the above-described method for determining flight path deviation using a thermal trajectory map, comprising: a network device for connecting to the vehicle; and a processor connected to the network device for executing a plurality of instructions stored in non-volatile memory to implement the above-described method for determining flight path deviation using a thermal trajectory map.

According to one embodiment of this application, a server is provided that implements the above-described method for determining flight path deviation using a thermal trajectory map, comprising: a network device for connecting the vehicle and the client; and a processor connected to the network device for executing a plurality of instructions stored in non-volatile memory to implement the above-described method for determining flight path deviation using a thermal trajectory map.

According to one embodiment of this application, a vehicle management information system is provided that implements the above-described method for generating virtual vehicle clones, comprising: the server; and the vehicle.

According to one embodiment of this application, a vehicle management information system is provided that implements the above-described method for generating virtual vehicle clones, comprising: the server; the client; and the vehicle.

When managing vehicle navigation, historical experience is often used. Through the embodiments described above, the method for determining route deviation using heat map provided in this application can summarize empirical rules into heat map data, allowing for a general assessment of whether the navigation trajectory is normal based on historical experience of different classes, seasons, and/or load classes. When the navigation trajectory deviates from the historically established course, timely warnings can be issued to relevant personnel.

According to one embodiment of this application, an electronic fence processing method is provided, comprising: receiving a location report from a vehicle; determining whether the location report of the vehicle corresponds to an electronic fence; when the location report of the vehicle corresponds to the electronic fence, determining whether to trigger a warning message of the electronic fence; and when it is determined that the warning message of the electronic fence has been triggered, transmitting the warning message of the electronic fence to the client of the relevant personnel of the vehicle.

Furthermore, to avoid repeatedly sending warning messages, the electronic fence processing method further includes: when it is determined that a warning message of the electronic fence has been triggered, determining whether a corresponding warning message has already been issued; and when no corresponding warning message has been issued, then performing the aforementioned step of transmitting the warning message of the electronic fence to the client of the relevant personnel of the vehicle, wherein the aforementioned step of transmitting the warning message of the electronic fence to the client of the relevant personnel of the vehicle is performed through a satellite galaxy telecommunications network.

Furthermore, in order to address electronic fence issues promptly, the electronic fence handling method further includes: transmitting the warning message to the computer of the relevant personnel in the vehicle using one of the following transmission methods or any combination thereof, wherein the transmission methods include SMS, email, multimedia message, voice message, video message and instant messaging.

Furthermore, in order to associate the electronic fence with certain instrument readings of the vehicle, the electronic fence processing method further includes: receiving an instrument reading report from the vehicle, wherein the aforementioned step of determining whether to trigger a warning message for the electronic fence further includes: determining whether the reading range of the instrument reading report falls within the setting parameter range of the electronic fence; and when the reading range of the instrument reading report falls within the setting parameter range of the electronic fence, determining to trigger a warning message for the electronic fence.

Furthermore, in order to avoid discharging wastewater or ballast water near the shore, the instrument readings reported above relate to whether or not the equipment discharging wastewater or ballast water is activated.

Furthermore, in order to avoid the emission of high-sulfur exhaust gas near the shore, the instrument readings reported above shall be related to one or any combination of the following: fuel oil heater outlet temperature; and fuel oil heater outlet viscosity.

Furthermore, in order to avoid anchoring in the cable-laying area or injuring marine mammals, the electronic fence's setting parameters, which relate to speed in the aforementioned instrument readings, include one of the following: minimum speed; and maximum speed.

Furthermore, in order to issue a warning message within the effective time period of the electronic fence, the aforementioned step of determining whether to trigger the warning message of the electronic fence further includes: determining whether the time of the location report corresponds to a start time and an end time of the electronic fence; and determining that the warning message of the electronic fence is triggered when the time of the location report corresponds to the start time and the end time of the electronic fence.

Furthermore, in order to limit the effectiveness of electronic fencing to certain vehicle classes, the aforementioned step of determining whether to trigger the warning message of the electronic fencing further includes: determining whether the vehicle class corresponds to the corresponding class of the electronic fencing; and determining to trigger the warning message of the electronic fencing when the vehicle class corresponds to the corresponding class of the electronic fencing.

Furthermore, in order to define an electronic fence within a three-dimensional space, the range of the electronic fence includes longitude, latitude, and elevation ranges.

Furthermore, in order to define a complex-shaped electronic fence, wherein the extent of the electronic fence is the intersection or union of two or more shapes.

Furthermore, in order to automatically set up the electronic fence, the electronic fence processing method further includes: obtaining a no-fly zone announcement from an external system server; and setting the electronic fence and its start time and end time according to the no-fly zone announcement.

Furthermore, in order to automate the remote control of the instruments and equipment on the vehicle, the aforementioned warning message of the electronic fence further includes a control command issued to an instrument or equipment on the vehicle, and the aforementioned electronic fence processing method further includes: when it is determined that the warning message of the electronic fence is triggered, transmitting the control command of the warning message of the electronic fence to the corresponding instrument or equipment on the vehicle.

According to one embodiment of this application, this application provides a server for implementing the aforementioned electronic fence processing method, comprising: a network device for connecting the carrier and the client; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned electronic fence processing method.

According to one embodiment of this application, a vehicle management information system for implementing the aforementioned electronic fence processing method is provided, comprising: the server; the client; and the vehicle.

By setting up and issuing warnings through electronic fencing, complex and cumbersome regional warnings can be automated, thereby reducing the burden of navigational precautions and the chance of errors. The aforementioned automation can also include reading the readings of instruments on the vehicle and determining whether they fall within the reading range of warning messages, further automating the warning messages.

According to one embodiment of this application, a satellite-transmitted image processing method is provided, comprising: calculating the low update rate of each of the multiple surveillance cameras based on the minimum fixed bandwidth of a satellite galaxy telecommunications network and the number and resolution of multiple surveillance cameras on a carrier; and transmitting the low update rate images of the multiple surveillance cameras to a server in turn through the satellite galaxy telecommunications network.

Furthermore, in order to automate the monitoring of images, the satellite transmission image processing method further includes: using an artificial intelligence image recognition module to monitor the images transmitted by the multiple monitoring cameras; and when the artificial intelligence recognition module detects an image anomaly in the first monitoring camera among the multiple monitoring cameras, transmitting the high-refresh-rate image of the first monitoring camera to the server through the satellite galaxy telecommunications network, wherein the high-refresh-rate image is higher than the low-refresh-rate image.

Furthermore, in order to monitor the safety inside the vehicle, the aforementioned video anomalies include one or any combination of the following: fire; pipeline leak; personnel falling into the sea; pest detection; and abnormal opening of cabin doors.

Furthermore, in order to serve clients requesting high-refresh-rate images through the server, the satellite image transmission processing method further includes: determining whether a specified request has been received from the server, the specified request requesting the transmission of images from a second monitoring camera among the plurality of monitoring cameras; when the specified request is received from the server, transmitting the high-refresh-rate images from the second monitoring camera to the server through the satellite galaxy telecommunications network, wherein the high refresh rate is higher than the low refresh rate.

Furthermore, in order to serve remote clients for control and communication, the satellite transmission image processing method further includes: upon receiving the specified request from the server, performing one or any combination of the following: receiving the server's control command to the second monitoring camera via the satellite galaxy telecommunications network, and transmitting the control command to the second monitoring camera; receiving the server's remote voice data to the second monitoring camera via the satellite galaxy telecommunications network, and transmitting the remote voice data to the second monitoring camera for playback; and receiving the voice data from the second monitoring camera, and transmitting the voice data from the second monitoring camera to the server via the satellite galaxy telecommunications network.

Furthermore, in order to control the surveillance camera, the control command includes one of the following commands for the second surveillance camera: pan, tilt, and zoom.

Furthermore, in order to prioritize the transmission of commands and voice data, the transmission priority of the remote voice data, the voice data, and the control commands is higher than that of the high-refresh-rate image data.

Furthermore, in order to serve clients on the same vehicle without occupying satellite communication bandwidth, the satellite image transmission processing method further includes: after receiving the specified request, determining whether the source of the specified request is a client on the vehicle; and when the source of the specified request is a client on the vehicle, directly transmitting the image of the second monitoring camera to the client through the vehicle's internal network.

Furthermore, in order to enable the server to further recognize faces, when the artificial intelligence image recognition module monitors the image of the third monitoring camera among the multiple monitoring cameras and a face or visual recognition device appears, the high-refresh-rate image of the third monitoring camera is transmitted to the server through the satellite galaxy telecommunications network, wherein the high-refresh-rate image has a higher update rate than the low-refresh-rate image.

Furthermore, in order to serve remote clients for control and communication, the satellite transmission image processing method further includes: when the artificial intelligence image recognition module monitors the image of a third monitoring camera among the multiple monitoring cameras and detects a face or visual recognition device, it performs one or any combination of the following: receiving the server's control command for the third monitoring camera through the satellite galaxy telecommunications network. The system receives remote voice data from the server to the third surveillance camera via the satellite network and transmits the remote voice data to the second surveillance camera for playback. It also receives voice data from the third surveillance camera and transmits the voice data from the second surveillance camera to the server via the satellite network.

Furthermore, in order to determine which compartment the crew members of the vehicle are located in, the satellite transmission image processing method further includes: when the artificial intelligence recognition module monitors the image of the third monitoring camera and a face or visual recognition device appears, identifying the personnel corresponding to the face or visual recognition device; locating the compartment where the third monitoring camera is installed based on the design drawing of one compartment of the vehicle; and recording the correspondence between the personnel and the compartment.

According to one embodiment of this application, this application provides a monitoring image carrier server for implementing the aforementioned satellite transmission image processing method, comprising: a network device for connecting the plurality of monitoring cameras to the server; and a processor connected to the network device for executing a plurality of instructions stored in non-volatile memory to implement the aforementioned satellite transmission image processing method.

According to one embodiment of this application, this application provides a vehicle information system for implementing the aforementioned satellite transmission image processing method, comprising: the monitoring image vehicle server; and the plurality of monitoring cameras.

According to one embodiment of this application, this application provides a satellite-transmitted image processing method, comprising: receiving low-refresh-rate images from multiple surveillance cameras of a vehicle via a satellite galaxy telecommunications network; receiving a specified request from a source, the specified request requesting the transmission of an image from a first surveillance camera among the multiple surveillance cameras; sending the specified request to a surveillance image carrier server of the vehicle; receiving, via the satellite galaxy telecommunications network, a high-refresh-rate image of the first surveillance camera corresponding to the specified request from the surveillance image carrier server, wherein the high-refresh-rate image has a higher refresh rate than the low-refresh-rate image; and transmitting the high-refresh-rate image to the source.

Furthermore, in order to store the aforementioned high update rate images, the satellite transmission image processing method further includes storing the high update rate images in the data management layer.

Furthermore, in order to facilitate control and communication between the source and the first surveillance camera, the satellite image transmission processing method further includes one or any combination of the following: receiving control commands from the source and transmitting the control commands to the surveillance camera server via the satellite network for controlling the first surveillance camera; receiving remote voice data from the source and transmitting the remote voice data to the surveillance camera server for instructing the first surveillance camera to play the remote voice data; and receiving voice data from the first surveillance camera via the surveillance camera server through the satellite network and transmitting the voice data to the source.

Furthermore, in order to control the surveillance camera, the control command includes one of the following commands: pan, tilt, and zoom on the first surveillance camera.

Furthermore, in order to prioritize the transmission of commands and voice data, the transmission priority of the remote voice data, the voice data, and the control commands is higher than that of the high-refresh-rate image data.

Furthermore, to automate image monitoring, the satellite-transmitted image processing method further includes: using an artificial intelligence image recognition module to monitor low-refresh-rate images from the multiple monitoring cameras; and when the artificial intelligence image recognition module detects an anomaly in the image from the first monitoring camera, the artificial intelligence image recognition module, as the source, issues the specified request.

Furthermore, in order to monitor personnel entering specific compartments, the satellite-transmitted image processing method further includes: using an artificial intelligence image recognition module to monitor facial or visual recognition devices in the high-refresh-rate images; querying the personnel corresponding to the facial or visual recognition device; querying the compartment where the first monitoring camera is installed based on the compartment design drawing of the vehicle; determining whether the correspondence between the personnel and the compartment is abnormal; generating a warning message when the correspondence is determined to be abnormal; and transmitting the warning message to the client of the relevant personnel in the vehicle through the satellite galaxy telecommunications network.

Furthermore, in order to monitor personnel operating certain equipment, the satellite-transmitted image processing method further includes: using an artificial intelligence image recognition module to monitor a face or visual recognition device in the high-refresh-rate image; querying the personnel corresponding to the face or visual recognition device; querying an instrument corresponding to the first monitoring camera based on the cabin design drawing of the vehicle; determining whether the correspondence between the personnel's certificate and the instrument is abnormal; generating a warning message when the correspondence is determined to be abnormal; and transmitting the warning message to the client of the relevant personnel in the vehicle through the satellite galaxy telecommunications network.

Furthermore, in order to monitor the high-refresh-rate images transmitted by the vehicle, the satellite-transmitted image processing method further includes: receiving high-refresh-rate images from a second monitoring camera among the multiple monitoring cameras via the satellite network; monitoring the high-refresh-rate images using an artificial intelligence image recognition module; generating a warning message when the artificial intelligence image recognition module determines that an image abnormality occurs in the high-refresh-rate images; and transmitting the warning message to the client of the relevant personnel of the vehicle via the satellite network.

Furthermore, in order to monitor the safety inside the vehicle, the aforementioned video anomalies include one or any combination of the following: fire; pipeline leak; personnel falling into the sea; pest detection; and abnormal opening of cabin doors.

According to one embodiment of this application, a server for implementing the aforementioned satellite transmission image processing method is provided, comprising: a network device for connecting the monitoring image carrier server and the source; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned satellite transmission image processing method.

According to one embodiment of this application, a vehicle information system for implementing the aforementioned satellite transmission image processing method is provided, comprising: the monitoring image vehicle server; the plurality of monitoring cameras; and the server.

The satellite-transmitted image processing method provided in this application allows remote clients or AI image recognition modules to monitor multiple low-refresh-rate images transmitted from the carrier, even with limited communication bandwidth. Upon request from the client or AI image recognition module, high-refresh-rate images can be transmitted for further identification. Automating the relationship between identification personnel and the cabin or equipment significantly reduces the burden of security checks. When the automated identification images malfunction, an automatic warning message can be issued.

According to one embodiment of this application, a method for calculating the carbon footprint of cargo is provided, comprising: receiving a first reading from a power meter of a vehicle; receiving a second reading from the power meter; calculating the power consumption of the power meter based on the difference between the second reading and the first reading; identifying the cargo corresponding to the power meter based on cargo loading data of the vehicle; and calculating the carbon footprint of the cargo based on the ratio of the vehicle's power consumption to carbon emissions and the corresponding power consumption of the cargo.

Furthermore, to ensure that the first reading is taken when the cargo is loaded and powered on, the cargo carbon footprint calculation method further includes: finding the location of the vehicle corresponding to the reading time based on the reading time of the first reading; determining whether the location corresponds to the loading location of the cargo; and determining that the first reading is valid when the location corresponds to the loading location of the cargo.

Furthermore, to ensure that the second reading is taken when the cargo is unloaded and powered off, the cargo carbon footprint calculation method further includes: finding the location of the vehicle corresponding to the reading time based on the reading time of the second reading; determining whether the location corresponds to the unloading location of the cargo; and determining that the first reading is valid when the location corresponds to the unloading location of the cargo.

Furthermore, in order to measure the power consumption of the goods as early as possible, the first reading is taken when the power consumption line calculated by the power meter is connected to the load.

Furthermore, in order to fully measure the power consumption of the goods, the first reading is taken when the power-consuming line calculated by the power meter is off-load.

Furthermore, to accurately measure the ratio of electricity consumption to carbon emissions of the vehicle, the cargo carbon footprint calculation method further includes: receiving a first total electricity meter reading from the vehicle, wherein the reading time of the first reading corresponds to the reading time of the first total electricity meter; receiving a second total electricity meter reading from the vehicle, wherein the reading time of the second reading corresponds to the reading time of the second total electricity meter; receiving the vehicle's... The vehicle receives a first fuel reading from a fuel meter of an electric motor, wherein the reading time of the first reading corresponds to the reading time of the first fuel reading; receives a second fuel reading from the fuel meter, wherein the reading time of the second reading corresponds to the reading time of the second fuel reading; and calculates the ratio of the vehicle's electricity consumption to carbon emissions based on the first total electricity meter reading, the second total electricity meter reading, the first fuel reading, and the second fuel reading.

Furthermore, in order to automatically provide reports to cargo owners, the cargo carbon footprint calculation method includes: generating a carbon footprint report based on the cargo's carbon footprint; and transmitting the cargo carbon footprint report to the cargo owner's external system server via the network.

Furthermore, in order to automatically provide electricity bills to cargo owners, the cargo carbon footprint calculation method includes: generating electricity bills for the cargo based on the cargo's carbon footprint; and transmitting the cargo's electricity bills to the cargo owner's external system server via the network.

According to one embodiment of this application, a server is provided for implementing the aforementioned cargo carbon footprint calculation method, comprising: a network device for connecting the power meter and the vehicle; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned cargo carbon footprint calculation method.

According to one embodiment of this application, a server is provided for implementing the aforementioned cargo carbon footprint calculation method, comprising: a network device for connecting the sub-meter, the main meter, and the fuel meter; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned cargo carbon footprint calculation method.

The cargo carbon footprint calculation method provided in this application allows for more accurate calculations and automatically generates carbon footprint reports for cargo. This enables cargo owners to better understand the power consumption during transportation on the vehicle, allowing them to seek more energy-efficient and carbon-reducing methods for transportation.

According to one embodiment of this application, a method for calculating carbon emission exemptions for a vehicle is provided, comprising: obtaining a list of all goods for which carbon footprints should be calculated based on cargo loading data of a vehicle, the list of goods including at least one cargo; performing the above-described cargo carbon footprint calculation method on the at least one cargo to obtain at least one carbon footprint report; and generating an exemption value for carbon emissions of the vehicle based on the at least one carbon footprint report.

According to one embodiment of this application, a server is provided for implementing the aforementioned vehicle carbon emission exemption calculation method, comprising: a network device for connecting to the power meter; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned vehicle carbon emission exemption method.

According to one embodiment of this application, a server is provided for implementing the aforementioned vehicle carbon emission exemption calculation method, comprising: a network device for connecting the sub-meter, the main meter, and the fuel meter; and a processor connected to the network device for executing multiple instructions stored in non-volatile memory to implement the aforementioned vehicle carbon emission exemption method.

The carbon emission exemption calculation method provided in this application allows for more accurate calculation of the carbon footprint of goods, leading to more accurate carbon emission exemptions. It also enables vehicle managers to better understand the power consumption during transportation, allowing them to find more energy-efficient and carbon-reducing methods for transport.

100: Vehicle Management Information System 110: Vehicle 110A: Vehicle 110B: Vehicle 110C: Vehicle 120: Access Telecommunications Network 130: Medium and Low Orbit Communication Satellite System Telecommunications Network 135: High Orbit Communication Satellite System Telecommunications Network 140: Navigation Satellite System 140A: Navigation Satellite System 140B: Navigation Satellite System 150: Telecommunications Network 160: Internal Network 170: Server 175: Cloud Server 180: External System Server 180A: External System Server 180B: External System Server 190: Client 190A: Client 190B: Client 200: Vehicle Information System 210: Vehicle Internal Network 220: Internal wired network of the vehicle; 230: Internal wireless network of the vehicle; 240: External network router; 250: Telecommunication network connection device; 252: Medium and low orbit communication satellite connection device; 254: High orbit communication satellite connection device; 260: AIS transceiver; 270: AIS information forwarding device; 280: Monitoring video vehicle server; 282: Monitoring camera terminal; 290: Vehicle instrument control device; 310: Access layer; 320: Business logic layer; 330: Data management layer; 700: Windows; 710A~710F: Low refresh rate images; 800: Carbon footprint calculation information system; 810: Temperature control cabinet; 820: Distributor meter. 830: Main Electricity Meter 840: Generator 850: Fuel Meter 860: Fuel Tank 880: Exemption from Carbon Emission Report 890: Carbon Footprint Report 1510~1570: Steps 900: Method for Generating Virtual Vehicle Clones 910~970: Steps 1000: Method for Determining Flight Line Deviation Using Thermal Track Maps 1010~1080: Steps 1100: Method for Setting Up Electronic Fences 1110~1160: Steps 1200: Method for Electronic Fence Warnings 1210~1250: Steps 1300: Satellite Transmission Image Processing Method 1310~1360: Steps 1400: Satellite Transmission Image Processing Method 1410~1490: Steps; 1500: Cargo Carbon Footprint Calculation Method; 1510~1570: Steps; 1600: Vehicle Carbon Emission Exemption Calculation Method; 1610~1630: Steps

Figure 1 is a block diagram of an integrated vehicle management information system 100 according to an embodiment of this application. Figure 2 is a block diagram of a vehicle information system 200 according to an embodiment of this application. Figure 3 is a block diagram of a server 170 according to an embodiment of this application. Figure 4 is a schematic diagram of a virtual clone (or digital clone) of a vehicle displayed in a window according to an embodiment of this application. Figure 5 is a schematic diagram of a flight thermal trajectory map according to an embodiment of this application. Figure 6 is a schematic diagram of an electronic fence according to an embodiment of this application. Figure 7 is a schematic diagram of a window 700 for viewing monitoring images of vehicle 110 on client 190 according to an embodiment of this application. Figure 8 is a block diagram of a carbon footprint calculation information system 800 according to an embodiment of this application. Figure 9 is a flowchart of a vehicle virtual clone generation method 900 according to an embodiment of this application. Figure 10 is a flowchart of a method 1000 for determining flight path deviation using thermal trajectory maps according to an embodiment of this application. Figure 11 is a flowchart of an electronic fence setting method 1100 according to an embodiment of this application. Figure 12 is a flowchart of an electronic fence warning method 1200 according to an embodiment of this application. Figure 13 is a flowchart of a satellite transmission image processing method 1300 according to an embodiment of this application. Figure 14 is a flowchart of a satellite transmission image processing method 1400 according to an embodiment of this application. Figure 15 is a flowchart of a cargo carbon footprint calculation method 1500 according to an embodiment of this application. Figure 16 is a flowchart of a vehicle carbon emission exemption calculation method 1600 according to an embodiment of this application.

1200: Electronic Fence Warning Method 1210~1250: Steps

Claims (10)

An electronic fencing method includes: receiving a vehicle's position report and instrument reading report via a satellite network, wherein the instrument reading report contains readings relating to one or any combination of the following: vehicle speed; whether wastewater or ballast water discharge equipment is activated; fuel heater outlet temperature; and fuel heater outlet viscosity; and determining whether the vehicle's position report corresponds to an electronic fencing system. When the vehicle's location report corresponds to the electronic fence, it is determined whether to trigger a warning message from the electronic fence. This warning message further includes a control command issued to an instrument on the vehicle. The steps for determining whether to trigger the warning message further include: determining whether the vehicle's level corresponds to the corresponding level of the electronic fence; determining whether the reading range of the instrument's reported reading falls within the set parameter range of the electronic fence; and... When the reading reported by the instrument falls within the set parameter range of the electronic fence and when the level of the vehicle corresponds to the corresponding level of the electronic fence, a warning message for the electronic fence is triggered; and when the warning message for the electronic fence is triggered, the warning message for the electronic fence is transmitted to the client of the relevant personnel of the vehicle and the corresponding instrument equipment of the vehicle. The electronic fence processing method as described in claim 1 further includes: when it is determined that a warning message of the electronic fence has been triggered, determining whether a corresponding warning message has been issued; and when no corresponding warning message has been issued, performing the step of transmitting the warning message of the electronic fence to the client of the relevant personnel of the vehicle, wherein the step of transmitting the warning message of the electronic fence to the client of the relevant personnel of the vehicle is performed through the satellite galaxy telecommunications network. The electronic fencing method as described in claim 1 further includes a computer that transmits the warning message to relevant personnel of the vehicle using one or any combination of the following transmission methods, wherein the transmission methods include SMS, email, multimedia message, voice message, video message and instant messaging. The electronic fencing processing method as described in claim 1, wherein the setting parameter range of the electronic fencing includes one of the following: minimum rate; and maximum rate. The electronic fence processing method as described in claim 1 further includes the step of determining whether to trigger a warning message for the electronic fence: determining whether the time of the location report corresponds to a start time and an end time of the electronic fence; and determining to trigger a warning message for the electronic fence when the time of the location report corresponds to the start time and the end time of the electronic fence. The electronic fencing processing method as described in claim 1, wherein the range of the electronic fencing includes a range of longitude, latitude, and elevation. The electronic fence processing method as described in claim 1, wherein the scope of the electronic fence is the intersection or union of two or more shapes. The electronic fence processing method as described in claim 1 further includes: obtaining a no-fly zone announcement from an external system server; and setting the electronic fence and its start time and end time according to the no-fly zone announcement. A server for implementing an electronic fencing processing method includes: a network device for connecting a vehicle and a client; and a processor connected to the network device for executing a plurality of instructions stored in non-volatile memory to implement the electronic fencing processing method as described in any one of claims 1 to 8. A vehicle management information system for implementing an electronic fencing method includes: a server, a client, and a vehicle as described in claim 9.