TWI900925B - Management system using artificial intelligence - Google Patents

Abstract

The invention provides a management system using artificial intelligence comprising a plurality monitoring modules, a servers and a robot terminal. Each monitoring module is used to provide a monitoring data. The server is used to receive monitoring data from the plurality of monitoring modules, and a artificial intelligence module in the server analyzes the monitoring data to generate a work schedule. The work schedule comprises at least one work task and a work address. The robot terminal is used to receive the work schedule, move to the work address and perform work tasks according to the work schedule.

Description

Management systems using artificial intelligence

The present invention relates to a management system that utilizes artificial intelligence. More specifically, the present invention relates to a management system that can utilize artificial intelligence to interpret monitoring data and drive a robot terminal to perform on-site work.

During construction projects, managers often need to manually visit various locations on the construction site to verify the status of various terminal devices or environmental parameters such as ambient temperature and humidity, resulting in unnecessary manpower waste. To address this issue, some manufacturers have developed monitoring systems that use robotic terminals such as mobile phones or tablets to read the status of various monitoring modules. This allows managers to access the status of various terminal devices or environments via the internet using their mobile phones or tablets. However, these monitoring systems are only used to aggregate and display data. Even if the monitoring system determines that the monitoring data is abnormal, traditional monitoring systems cannot immediately respond to unexpected events.

For example, imagine a sudden landslide or heavy rain upstream of a construction site in a mountainous area. Even if the monitoring system records the event through various sensors or surveillance cameras, the construction site may be quite large, and managers, caught in the rush and chaos, may not be able to detect and address it in time. Therefore, the industry needs a new management system that applies artificial intelligence. This management system should be able to utilize robotic terminals to handle on-site situations based on the actual situation, allowing users to more efficiently manage the entire construction site or workflow.

This invention proposes a management system that applies artificial intelligence. It can use artificial intelligence to analyze on-site conditions and generate a real-time work schedule for the robot terminal, which then goes to the site to handle the work according to the schedule.

The present invention provides a management system utilizing artificial intelligence, comprising multiple monitoring modules, a server, and a robotic terminal. Each monitoring module is configured to provide monitoring data. The server receives the monitoring data from the multiple monitoring modules, and an artificial intelligence module within the server analyzes the monitoring data to generate a work schedule. The work schedule includes at least one work task and a work address. The robotic terminal receives the work schedule, moves to the work address according to the work schedule, and executes the work task.

In some embodiments, at least a portion of the monitoring module's monitoring data includes environmental parameters of the environment in which the monitoring module is located, or includes the status of a terminal device to which the monitoring module is electrically connected. Furthermore, the management system utilizing artificial intelligence further includes a plurality of controllable devices, and the server transmits the control permissions of the controllable devices to be controlled in the proposed solution to the robot terminal based on the work schedule proposed by the artificial intelligence module. Furthermore, the artificial intelligence module determines whether an abnormal event has occurred based on the monitoring data of at least one monitoring module, and the artificial intelligence module generates the work address based on the monitoring address of the monitoring module associated with the abnormal event. Furthermore, the artificial intelligence module generates a work task based on the nature of the abnormal event.

In summary, the AI-powered management system of the present invention utilizes an AI module to analyze the location and on-site values of monitoring data to determine the location and type of abnormal events. Subsequently, the AI module generates a task schedule for the robot terminal, allowing the robot terminal to proceed to the site according to the task schedule.

The following text further discloses the features, objectives, and functions of the present invention. However, unless otherwise defined, the following descriptions are merely examples of embodiments of the present invention and are not intended to limit the scope of the present invention. In other words, any equivalent variations and modifications made within the scope of the present invention will remain within the spirit and scope of the present invention and should be considered further embodiments of the present invention.

Figure 1 is a schematic diagram of an AI-enabled management system according to a specific embodiment of the present invention. As shown in Figure 1 , the AI-enabled management system 1 includes one or more robot terminals 10, at least one server 20, multiple wireless transmission base stations 30, and multiple monitoring modules 40. Each robot terminal 10 can communicate with the server 20 via a wireless connection. This embodiment does not limit the communication method used for data transmission, such as 4G, 5G, Wi-Fi, or other suitable communication methods. In addition to wirelessly connecting to the robot terminals 10, the server 20 can also connect to multiple monitoring modules 40 and multiple terminal devices 50 via multiple wireless transmission base stations 30. Of course, the server 20 may also be directly connected to multiple monitoring modules 40 and multiple terminal devices 50 without going through the wireless transmission base station 30, and this embodiment is not limited thereto.

The robot terminal 10 can be a movable mechanical device and can also include basic security functions such as providing lighting, sound, and fire extinguishing. Alternatively, the robot terminal 10 can have a robotic arm or other basic structure for interacting with the surrounding environment, and this embodiment is not limited thereto. The server 20 can be composed of one or more computers or cloud operating systems, and its function is to be a device for data exchange or calculation. In practice, the robot terminal 10 may be pre-installed with a corresponding application for connecting to the server 20 over the network or logging into the network platform maintained by the server 20, so that the server 20 can directly manage the robot terminal 10, such as issuing instructions to the robot terminal 10. In addition, the management system 1 using artificial intelligence can be applied to various types of construction sites. The server 20 can have an artificial intelligence module (not shown) inside, and the artificial intelligence module can be pre-trained or pre-fed with relevant knowledge of construction site management, which is not limited in this embodiment.

The monitoring module 40 can be a sensor capable of monitoring a specific environment or object. Monitoring data from the monitoring module 40 may be transmitted to the server 20 via a wireless transmission base station 30, or the server 20 may obtain the monitoring data directly from the network without passing through the wireless transmission base station 30. In practice, since multiple monitoring modules 40 are typically installed in different locations, if the monitoring module 40 is only capable of short- to medium-range communication and lacks long-range communication capabilities, one or more wireless transmission base stations 30 can be installed within the construction site/area, with the wireless transmission base stations 30 responsible for communication with the remote server 20. Of course, if the monitoring module 40 itself has the function of long-distance communication, it can be understood that the wireless transmission base station 30 should be an unnecessary device.

In one example, when monitoring module 40 is a sensor for monitoring a specific environment, different devices can be used to meet various measurement requirements. For example, monitoring module 40 can be a thermometer to measure the temperature at a location, a hygrometer to measure the humidity at a location, a rain gauge to measure the rainfall at a location, a water level gauge to measure the presence of water at a location, a pressure gauge to measure the air pressure at a location, or a flow meter to measure the flow of liquid or gas in a pipeline, among other environmental parameters. In other words, the monitoring data can be rainfall values, water level values, air pressure values, or flow values, without limitation in this embodiment. When the monitoring module 40 is a sensor that monitors a specific object, the monitoring module 40 can be connected to a terminal device and detect the usage status of the terminal device. In practice, the monitoring module 40 also has a monitoring address, which can be assigned by the installation personnel when the monitoring module 40 is installed, or obtained by the monitoring module 40 through self-positioning. In one example, the monitoring module 40 may be an application installed in a portable electronic device. For example, a mobile phone may be equipped with various detection functions such as a thermometer, altimeter, or GPS. Information obtained from the mobile phone's hardware can also be considered as monitoring data provided by the monitoring module 40, although this embodiment is not limited thereto.

The aforementioned terminal device may be a machine tool (e.g., an excavator or a truck). When the terminal device is started (e.g., by turning on the power switch or starting the engine), the monitoring module 40 connected to the terminal device can detect the operating current or operating voltage (i.e., monitoring data), thereby knowing that the terminal device has been started. For example, the terminal device can be a security lock or a smart camera. When the terminal device is triggered (the lock is opened or the camera captures a specific image), the monitoring module 40 connected to the terminal device can detect the detailed information or warning signal (i.e., monitoring data) provided by the terminal device, thereby notifying the user of an abnormality around the terminal device. In other words, the terminal device can refer to various motors, pumps, construction vehicles, power supplies, construction equipment, or parts of buildings. This embodiment is not limited to terminal devices.

In actual operation, after the robot terminal 10 is activated, it can automatically (regularly) transmit an access signal containing location data to the server 20. The server 20 then obtains the address of the robot terminal 10 based on the access signal. In addition, the robot terminal 10 can pre-store a task schedule. For example, the administrator can use the server 20 to issue the address and corresponding task to the robot terminal 10. The server 20 can also store device distribution data, which records the monitoring address of each monitoring module 40. Suppose a monitoring module 40 is connected to a streetlight. When the AI module of server 20 determines that the streetlight is faulty based on the monitoring data provided by this monitoring module 40, the AI module of server 20 can generate a work address based on the monitoring address of this monitoring module 40. Furthermore, because the AI module of server 20 determines that the streetlight is faulty, it can determine that the nature of this abnormal event is "lighting required" and thus generate the corresponding work task of "lighting."

In one example, the AI module of server 20 can determine which robot terminal 10 is closest based on the addresses provided by all robot terminals 10. The AI module of server 20 then sends the work address and task to the closest robot terminal 10. Because robot terminals 10 are mobile, they can autonomously move to the work address (i.e., the area around the faulty streetlight) and turn on the light to provide illumination according to the task instructions.

In another example, suppose a monitoring module 40 is connected to a piece of equipment. When the server 20's AI module determines that the equipment has been activated based on the monitoring data provided by this monitoring module 40, the server 20's AI module can generate a work address based on the monitoring address of the monitoring module 40. Furthermore, because the server 20's AI module determines that the equipment has been activated abnormally, it can determine that the nature of this abnormal event is "need for on-site imagery" and thus generate the corresponding work task of "take a photo." The server 20's AI module then sends the work address and work task to the corresponding robot terminal 10. The robot terminal 10 can automatically move to the work site, that is, around the abnormally activated tool, and turn on the camera to capture on-site images according to the task instructions of the work task, allowing the manager to determine the reason for the tool to start.

In another example, let's assume that a monitoring module 40 is a camera. When the server 20's AI module determines, based on the monitoring data (images) provided by this monitoring module 40, that a traffic accident has occurred at a certain intersection, the server 20's AI module can generate a work address based on the monitoring address of this monitoring module 40. Furthermore, because the server 20's AI module has determined that a traffic accident has occurred, it can determine that the nature of this abnormal event is "necessitating warning and fire prevention," and thus generate the corresponding work task of "providing warnings and extinguishing fires." Of course, upon determining a traffic accident, the server 20's AI module can immediately contact medical personnel. At the same time, the server 20's artificial intelligence module sends the work location and task to the corresponding robot terminal 10. The robot terminal 10 automatically moves to the work location, which is the area surrounding the accident scene. Following the task instructions, it turns on its warning lights to prevent secondary collisions with other vehicles, activates its camera, and detects any fire. If so, it activates the fire extinguishing equipment installed on the robot terminal 10 to extinguish the fire.

In another example, let's assume a monitoring module 40 is a water level gauge. When the server 20's AI module determines that the water level is too high based on the monitoring data (images) provided by this monitoring module 40, the server 20's AI module can generate a work address based on the monitoring address of this monitoring module 40. Furthermore, because the server 20's AI module has determined that flooding has occurred, it can determine that the nature of this abnormal event is "preventing the water level from rising," and thus generate the corresponding work task of "closing the water valve." At this point, the server 20's AI module will send the work address and work task to the corresponding robot terminal 10. The robot terminal 10 can first move to the work address, which is the area around the water valve. In practice, a water valve, as a critical controllable device, may require corresponding control permissions to operate. To enable the robot terminal 10 to operate the water valve, the server 20's artificial intelligence module can provide not only the work address and task but also the control permissions for the water valve when providing a work schedule. Accordingly, the robot terminal 10 will use the control permissions to close the water valve according to the task instructions.

In summary, the AI-powered management system of the present invention utilizes an AI module to analyze the location and on-site values of monitoring data to determine the location and type of abnormal events. Subsequently, the AI module generates a task schedule for the robot terminal, allowing the robot terminal to proceed to the site according to the task schedule.

1: AI-enabled management system 10: Robot terminal 20: Server 30: Wireless transmission base station 40: Monitoring module

FIG1 is a schematic diagram of a management system using artificial intelligence according to a specific embodiment of the present invention.

1: Management system using artificial intelligence

10: Robot Terminal

20: Server

30: Wireless transmission base station

40: Monitoring module

Claims (4)

A management system utilizing artificial intelligence comprises: a plurality of monitoring modules, each configured to provide monitoring data; a server configured to receive the monitoring data from the monitoring modules, and an artificial intelligence module within the server to analyze the monitoring data to generate a work schedule comprising at least one work task and a work address; and a robot terminal configured to receive the work schedule, move to the work address according to the work schedule, and execute the work task; the artificial intelligence module determines whether an abnormal event has occurred based on the monitoring data from at least one monitoring module, and generates the work address based on a monitoring address of the monitoring module associated with the abnormal event. In the management system applying artificial intelligence as claimed in claim 1, at least a portion of the monitoring data of the monitoring module includes an environmental parameter of the environment in which the monitoring module is located, or includes the status of a terminal device to which the monitoring module is electrically connected. The management system using artificial intelligence as claimed in claim 1 further includes multiple controllable devices, and the server transmits a control permission of the controllable device that needs to be controlled in a proposed solution to the robot terminal based on the work schedule proposed by the artificial intelligence module. In the management system using artificial intelligence as claimed in claim 1, the artificial intelligence module generates the work task based on the nature of an abnormal event.