CN116709037A - 5G camera-based method for transmitting monitoring key data of weather and rain - Google Patents

Abstract

The application discloses a 5G camera-based method for transmitting monitoring key data of weather and rain, which comprises the following steps: the main control CPU is connected with the camera through the CSI interface to acquire video data; the data processing module generates core data of the image or the video; and the AI pre-analysis module generates a key data stream uploading cloud according to the processed image and video information. According to the 5G camera-based method for transmitting the monitoring key data of the weather and the weather, the image processing frame and the video processing frame are integrated into a unified processing flow, so that modularized registration and dynamic loading are realized, and the processing efficiency is improved. The AI pre-analysis module performs advanced analysis to generate a key data stream, and the cloud can obtain clear data only by a small amount of video data. The application has better effects in the aspects of processing speed, bad weather resistance, data pertinence and the like.

Description

A 5G camera-based monitoring key data transmission method for wind and rain

technical field

The present invention relates to the technical field of camera recognition, in particular to a method for transmitting key data for wind and rain monitoring based on a 5G camera.

Background technique

With the development of science and technology, 5G technology provides faster and more stable network connections for the Internet of Things, smart cities and remote monitoring and other fields. However, in practical applications, due to adverse weather conditions such as wind and rain, the camera may be blocked when acquiring images and videos, resulting in a decrease in image quality, thereby affecting the accuracy of target detection and tracking. In addition, fluctuations in network signal strength may also cause delays or interruptions in data transmission, further reducing the reliability of surveillance systems.

Existing monitoring technologies face multiple challenges under wind and rain conditions: image and video quality are affected by natural factors such as rain and wind speed, network signals are poor in wind and rain, and sensor data is affected by fluctuations in network signal strength, which may lead to poor data transmission. Stable, wrong data transmission, too much data sent without pertinence, and processing too slow; the current image processing framework and video processing framework are relatively independent and mainly distributed in the cloud, and the camera lacks a built-in preprocessing module, resulting in a data processing process that is not flexible and efficient.

In view of the above problems, there is an urgent need for a monitoring key data transmission method based on 5G cameras in wind and rain. By optimizing the processing and transmission of image and video data in wind and rain, the performance and reliability of the monitoring system under severe weather conditions can be improved. The modular design realizes the flexible configuration and efficient operation of the image processing framework and video processing framework, providing a new solution for the development of future monitoring technology.

Contents of the invention

The purpose of this section is to outline some aspects of embodiments of the invention and briefly describe some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the abstract and titles of this application, to avoid obscuring the purpose of this section, abstract and titles, and such simplifications or omissions should not be used to limit the scope of the invention.

In view of the above problems, the present invention has been proposed.

Therefore, the technical problem solved by the present invention is: the existing monitoring technology is seriously affected by the weather, sending all monitoring data, lack of pertinence, slow processing, and optimization problems of how to distribute the data processing flow in the camera and the cloud.

In order to solve the above-mentioned technical problems, the present invention provides the following technical solution: a monitoring key data transmission method based on a 5G camera, including:

The main control CPU connects the camera through the CSI interface to obtain video data;

The data processing module generates core data of images or videos;

The AI pre-analysis module generates key data streams and uploads them to the cloud based on the processed image and video information.

As a preferred solution of the monitoring key data transmission method based on a 5G camera in the present invention, wherein: the main control CPU is connected to the camera through the CSI interface to obtain video data, and the main control CPU is connected to multiple channels through the CSI interface. Digital camera or MIPI camera, the camera transmits images and videos to the image processing framework and video processing framework.

As a preferred solution of the monitoring key data transmission method based on the 5G camera of the present invention, wherein the image processing framework and the video processing framework include, after the image processing framework receives the image, the decoded image The data is used as the core to generate an image processing module that connects image filtering, morphological operations, feature segmentation, feature extraction, edge detection, and image enhancement. After processing, the image is encoded into jpeg and png formats and sent to the AI pre-analysis module;

After the video processing framework receives the video, it converts the video into a video data block based on the encoded H.265, and takes the video data block as the core to generate code stream conversion, video compression, video enhancement, video preloading, RTSP protocol push and Video processing module pushed by RTP protocol.

As a preferred solution of the 5G camera-based wind and rain monitoring key data transmission method of the present invention, wherein: the image processing framework and the video processing framework also include that the video processing module and the image processing module adopt a modular approach Register to the framework, dynamically load and preload the hook function, and control the enabling or stopping of the hook function through the open interface API.

As a preferred solution of the 5G camera-based wind and rain monitoring key data transmission method of the present invention, wherein: the AI pre-analysis module includes, after completing the image and video processing, the serial data receives the external wind speed and rainfall Data, the sensor program pushes the received data to the cloud, the cloud sends control commands to the control logic unit, and the logic unit judges the wind speed and rainfall for operation;

When the wind speed is less than 6m/s and the rainfall is less than 8mm/h, it is judged that there is rain on the camera, which does not affect the image and video captured by the camera. If the network signal strength is greater than -70dBm, the video and image data will be directly uploaded to the cloud. If -70dBm < network signal If the strength is less than -75dBm, reduce the resolution of the image and video and increase the compression ratio to reduce the transmission pressure, and upload to the cloud. If the network signal strength is less than -75dBm, it will be regarded as a device failure or blocked by network information, and the data will be saved in the data cache In, and encrypt;

When 6m/s ≤ wind speed ≤ 14m/s, 8mm/h ≤ rainfall ≤ 18mm/h, it is judged that there is rain on the camera, the camera is blocked by rain, the acquired image and video are partially blocked, and the image and video are transferred to the AI pre-analysis module , to reduce noise through median filtering, use SSD target detection algorithm to identify objects, use OpenPose algorithm for human detection, and use TLD target tracking algorithm for target tracking. Send to the cloud, if the network signal strength is <-75dBm, receive the serial data in the same area to judge the network signal strength of the 5G camera in the same area, if it is less than -75dBm, it is considered that the signal is affected by the weather, otherwise it is judged as a device failure or Blocked by network information;

When the wind speed is greater than 14m/s and the rainfall is greater than 18mm/h, it is judged that there is rain on the camera, and the camera is blocked by rain, and the acquired images and videos are all blocked, and the images and videos are transferred to the AI pre-analysis module and processed through the deep learning rain removal network And the image and video are fused for multi-frame image fusion analysis. After the analysis is completed, target detection, human body detection and target tracking are carried out, and the tracking results are optimized and corrected in combination with historical tracking data and target motion characteristics. After the correction is completed, the identified predictive If the dangerous event is forwarded to the cloud in the form of an alarm, if the signal is less than -80dBm, the video stream or serial data will be temporarily saved in the data cache, and the data will be retransmitted when the network is restored.

As a preferred solution of the 5G camera-based monitoring key data transmission method for wind and rain in the present invention, wherein: the AI pre-analysis module also includes, when the wind speed > 16m/s, the camera shakes, the acquired image and video There is a blurred phenomenon, and the image and video are transferred to the AI pre-analysis module, which performs low-filtering and noise reduction on the image, extracts non-moving frames of the image from the video, calculates the motion information based on the pixel changes between the two frames of images, and uses the calculated The motion information performs motion compensation on the image, and performs dangerous event identification on the processed image and video.

As a preferred solution of the 5G camera-based wind and rain monitoring key data delivery method of the present invention, the key data flow includes processed image and video data, wind speed and rainfall data, and AI pre-analysis of dangerous event types And request camera steering instructions.

As a preferred solution of the 5G camera-based monitoring key data transmission method for wind and rain in the present invention, wherein: the request for camera steering instructions includes, when the AI pre-analysis module recognizes the preset dangerous time, send a message to the cloud Send a tracking target request, convert the target tracking of the recorded video into the target tracking of the camera, and record the dangerous time status in real time.

As a preferred solution of the 5G camera-based monitoring key data transmission method for wind and rain in the present invention, wherein: a computer device includes a memory and a processor, the memory stores a computer program, and it is characterized in that the When the processor executes the computer program, a 5G camera-based monitoring key data transfer method for wind and rain is realized.

As a preferred solution of the 5G camera-based monitoring key data transmission method for wind and rain in the present invention, wherein: a computer-readable storage medium on which a computer program is stored,

It is characterized in that, when the computer program is executed by the processor, a method for transmitting key data of wind and rain monitoring based on the 5G camera is realized.

Beneficial effects of the present invention: The image processing framework and video processing framework of the 5G camera-based key data transmission method for wind and rain monitoring provided by the present invention are integrated into a unified processing flow, which realizes modular registration and dynamic loading, and improves processing efficiency. The AI pre-analysis module performs advanced analysis to generate key data streams, and the cloud only needs a small amount of video data to obtain clear data. The invention achieves better effects in terms of processing speed, anti-bad weather ability, data pertinence and the like.

Description of drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings that need to be used in the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For Those of ordinary skill in the art can also obtain other drawings based on these drawings without any creative effort. in:

Fig. 1 is an overall flow chart of a key data transmission method for wind and rain monitoring based on a 5G camera provided by an embodiment of the present invention.

Detailed ways

In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation modes of the present invention will be described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Example. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative efforts shall fall within the protection scope of the present invention.

In the following description, a lot of specific details are set forth in order to fully understand the present invention, but the present invention can also be implemented in other ways different from those described here, and those skilled in the art can do it without departing from the meaning of the present invention. By analogy, the present invention is therefore not limited to the specific examples disclosed below.

Second, "one embodiment" or "an embodiment" referred to herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. "In one embodiment" appearing in different places in this specification does not all refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

The present invention is described in detail in conjunction with schematic diagrams. When describing the embodiments of the present invention in detail, for the convenience of explanation, the cross-sectional view showing the device structure will not be partially enlarged according to the general scale, and the schematic diagram is only an example, which should not limit the present invention. scope of protection. In addition, the three-dimensional space dimensions of length, width and depth should be included in actual production.

At the same time, in the description of the present invention, it should be noted that the orientation or positional relationship indicated by "upper, lower, inner and outer" in the terms is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention. The invention and the simplified description do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and thus should not be construed as limiting the present invention. In addition, the terms "first, second or third" are used for descriptive purposes only, and should not be construed as indicating or implying relative importance.

Unless otherwise specified and limited in the present invention, the term "installation, connection, connection" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integrated connection; it can also be a mechanical connection, an electrical connection or a direct connection. A connection can also be an indirect connection through an intermediary, or it can be an internal communication between two elements. Those of ordinary skill in the art can understand the specific meanings of the above terms in the present invention in specific situations.

Example 1

Referring to FIG. 1 , an embodiment of the present invention provides a monitoring key data transmission method based on a 5G camera for wind and rain, including:

S1: The main control CPU connects the camera through the CSI interface to obtain video data.

Furthermore, the main control CPU is connected to multiple digital cameras or MIPI cameras through the CSI interface, and the cameras transmit images and videos to the image processing framework and the video processing framework.

It should be noted that by connecting multiple digital cameras or MIPI cameras through the CSI interface, the images or video streams collected by multiple cameras can be obtained simultaneously, so that a single CPU can obtain multiple data and send the data to the image processing framework and video processing in a unified manner. The framework ensures the processing efficiency of the equipment.

S2: The data processing module generates core data of images or videos.

Furthermore, the image processing framework: after receiving the image, the image processing framework generates an image processing module that connects image filtering, morphological operations, feature segmentation, feature extraction, edge detection, and image enhancement with the decoded image data as the core After the processing is completed, encode the image into jpeg and png formats and send it to the AI pre-analysis module.

The video processing framework includes: After the video processing framework receives the video, it converts the video into video data blocks based on encoding H.265, and uses the video data blocks as the core to generate hook code stream conversion, video compression, video enhancement, video preloading, and RTSP Video processing module for protocol push and RTP protocol push.

It should be noted that the video processing module and the image processing module are registered to the framework in a modular manner, dynamically loaded and preloaded with hooking functions, and are controlled to enable or disable the hooking function through an open interface API.

It should also be noted that the hook function can be dynamically loaded and preloaded according to actual needs, thereby reducing unnecessary consumption of computing resources. For example, in scenes that do not require edge detection, no loading is performed to save computing resources. Through functional design, it is easy to add new functions or upgrade existing functions to the image processing framework and video processing framework, which helps to improve the maintainability and upgradeability of the system and adapt to the needs of future technological development.

Furthermore, H.265 has the characteristics of high compression ratio, which is suitable for our invention to transmit data to the demand when the network environment is crossed. The high compression ratio can reduce the pressure of data transmission, and when the network signal does not meet the transmission requirements Next, more videos can be saved locally. H.265 has a low codec delay and is suitable for video application scenarios where the camera requires real-time processing and transmission. Compared with H.264, H.265 can reduce the bit rate by half under the same picture quality, and can also reduce resource consumption.

S3: The AI pre-analysis module generates key data streams based on the processed image and video information and uploads them to the cloud.

Furthermore, the AI pre-analysis module includes: after image and video processing is completed, the serial data receives external wind speed and rainfall data, the sensor program pushes the received data to the cloud, and the cloud sends control commands to the control logic unit, and the logic unit judges wind speed and rainfall.

When the wind speed is less than 6m/s and the rainfall is less than 8mm/h, it is judged that there is rain on the camera, which does not affect the image and video captured by the camera. If the network signal strength is greater than -70dBm, the video and image data will be directly uploaded to the cloud. If -70dBm < network signal If the strength is less than -75dBm, reduce the resolution of the image and video and increase the compression ratio to reduce the transmission pressure, and upload to the cloud. If the network signal strength is less than -75dBm, it will be regarded as a device failure or blocked by network information, and the data will be saved in the data cache , and encrypt it.

When 6m/s ≤ wind speed ≤ 14m/s, 8mm/h ≤ rainfall ≤ 18mm/h, it is judged that there is rain on the camera, the camera is blocked by rain, the acquired image and video are partially blocked, and the image and video are transferred to the AI pre-analysis module , to reduce noise through median filtering, use SSD target detection algorithm to identify objects, use OpenPose algorithm for human detection, and use TLD target tracking algorithm for target tracking. Send to the cloud, if the network signal strength is <-75dBm, receive the serial data in the same area to judge the network signal strength of the 5G camera in the same area, if it is less than -75dBm, it is considered that the signal is affected by the weather, otherwise it is judged as a device failure or Blocked by network information.

When the wind speed is greater than 14m/s and the rainfall is greater than 18mm/h, it is judged that there is rain on the camera, and the camera is blocked by rain, and the acquired images and videos are all blocked, and the images and videos are transferred to the AI pre-analysis module and processed through the deep learning rain removal network And the image and video are fused for multi-frame image fusion analysis. After the analysis is completed, target detection, human body detection and target tracking are carried out, and the tracking results are optimized and corrected in combination with historical tracking data and target motion characteristics. After the correction is completed, the identified predictive If the dangerous event is forwarded to the cloud in the form of an alarm, if the signal is less than -80dBm, the video stream or serial data will be temporarily saved in the data cache, and the data will be retransmitted when the network is restored.

It should be noted that when the wind speed is >16m/s, the camera shakes, and the acquired images and videos are blurred, the images and videos are transferred to the AI pre-analysis module, which performs low-filtering and noise reduction on the images, and extracts non-moving frames from the images , calculate the motion information according to the pixel changes between two frames of images, and perform motion compensation on the images according to the calculated motion information, and identify dangerous events on the processed images and videos.

It should also be noted that the selected threshold is the experimental result, and the wind speed threshold is divided into three levels, namely 6m/s, 14m/s, and 16m/s. Such a setting can fully consider the drop offset of different wind forces on rainwater The ability can simulate the real environment. In windy and windy weather, the amount of rain that the wind blows rain on the camera screen, 16m/s is in line with the shake threshold measured in an open environment after the camera is installed. The network signal strength setting -70dBm is the extreme value of stable transmission. When the network signal of ordinary cameras is lower than this threshold, the transmission will be interrupted, but our invention is set to -80dBm, because our invention chooses to convert images and videos to The key data flow, and the video is encoded as H.265, with a high compression ratio, and the data flow can be transmitted only after a short network connection.

It should be noted that the key data streams include: processed image and video data, wind speed and rainfall data, AI pre-analysis of dangerous event types, and requests for camera steering instructions.

It should also be noted that when the AI pre-analysis module recognizes the preset dangerous time, it sends a tracking target request to the cloud, converting the recorded target tracking into the camera target tracking, and recording the dangerous time status in real time.

Example 2

An embodiment of the present invention provides a 5G camera-based monitoring key data transmission method for wind and rain. In order to verify the beneficial effects of the present invention, scientific demonstrations are carried out through economic benefit calculations and simulation experiments.

Set different wind and rain weather environments.

The same monitoring area adopts the cameras of our invention and traditional technical solutions respectively.

The image, video and sensor data of the two monitoring systems were collected in various wind and rain environments, and the network signal strength was recorded at the same time.

The collected data is processed and analyzed in a unified manner, and the image, video quality and sensor data transmission effect of the two monitoring systems are compared under different wind and rain environments.

Analyze the data processing speed and efficiency of the two monitoring systems in different wind and rain environments, and evaluate the real-time response capabilities of the systems to preset dangerous events.

As shown in the risk response capability comparison table shown in Table 1, as shown in the table, our invention requires less signals than traditional technical solutions under any severe circumstances, because our invention is in the face of sudden emergencies. In dangerous events, video data and image data are generated into key data streams to reduce the demand for network signals. Therefore, in the case of close network signals, our invention makes it easier to avoid network interruptions. Because our invention has already processed the image before generating the key data stream to avoid the degradation of the image quality due to transmission problems, the image quality has been significantly improved. Converting dangerous event information into key data streams and sending them to the cloud effectively avoids alarm delays caused by redundant data and greatly improves the ability to respond to emergency crises.

Table 1 Comparison Table of Risk Response Capabilities

If the functions are realized in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes. .

The logic and/or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium, For use with instruction execution systems, devices, or devices (such as computer-based systems, systems including processors, or other systems that can fetch instructions from instruction execution systems, devices, or devices and execute instructions), or in conjunction with these instruction execution systems, devices or equipment used. For the purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use in or in conjunction with an instruction execution system, device or device.

More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connection with one or more wires (electronic device), portable computer disk case (magnetic device), random access memory (RAM), Read-Only Memory (ROM), Erasable and Editable Read-Only Memory (EPROM or Flash), Fiber Optic, and Compact Disc Read-Only Memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program can be printed, as it may be possible, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or other suitable processing if necessary. The program is processed electronically and stored in computer memory.

It should be understood that various parts of the present invention can be realized by hardware, software, firmware or their combination. In the embodiments described above, various steps or methods may be implemented by software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or combination of the following techniques known in the art: Discrete logic circuits, ASICs with suitable combinational logic gates, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention without limitation, although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be carried out Modifications or equivalent replacements without departing from the spirit and scope of the technical solution of the present invention shall be covered by the claims of the present invention.

Claims (10)

1. The utility model provides a monitoring key data transmission method based on weather and rain of 5G camera which characterized in that includes:

the main control CPU is connected with the camera through the CSI interface to acquire video data;

the data processing module generates core data of the image or the video;

and the AI pre-analysis module generates a key data stream uploading cloud according to the processed image and video information.

2. The 5G camera-based method for transmitting monitoring key data of weather and rain according to claim 1, wherein: the main control CPU is connected with the cameras through the CSI interfaces to obtain video data, wherein the main control CPU is connected with the multi-path digital cameras or the MIPI cameras through the CSI interfaces, and the cameras transmit images and videos to the image processing frame and the video processing frame.

3. The 5G camera-based method for transmitting monitoring key data of weather and rain according to claim 1 or 2, wherein: the image processing frame and the video processing frame comprise an image processing module for hanging image filtering, morphological operation, feature segmentation, feature extraction, edge detection and image enhancement, wherein after the image processing frame receives an image, the image processing module takes decoded image data as a core, and encodes the image into jpeg and png formats and sends the jpeg and png formats to an AI pre-analysis module after processing is completed;

after the video processing framework receives the video, the video is converted into video data blocks based on coding H.265, and the video data blocks are used as cores to generate video processing modules for hanging code stream conversion, video compression, video enhancement, video preloading, RTSP pushing and RTP pushing.

4. The 5G camera-based weather and wind monitoring key data transmission method of claim 3, wherein: the image processing frame and the video processing frame further comprise a video processing module and an image processing module which are registered to the frame in a modularized mode, dynamically load and preload the hooking function, and control to start or stop the hooking function through an open interface API.

5. The 5G camera-based method for transmitting monitoring key data of weather and rain according to claim 4, wherein: the AI pre-analysis module comprises that after the processing of the images and the videos is completed, serial data are used for receiving external wind speed and rainfall data, a sensor program is used for pushing the received data to a cloud end, the cloud end sends a control command to a control logic unit, and the logic unit judges the wind speed and the rainfall to operate;

when the wind speed is less than 6m/s and the rainfall is less than 8mm/h, judging that the camera has rainwater, and not affecting the camera to acquire images and videos, if the network signal strength is more than-70 dBm, directly uploading the videos and image data to a cloud end, if the network signal strength is less than-70 dBm, reducing the resolution of the images and the videos, improving the compression ratio, reducing the transmission pressure, uploading the cloud end, and if the network signal strength is less than-75 dBm, considering equipment failure or being shielded by network information, storing the data in a data cache, and encrypting;

when the wind speed is less than or equal to 6m/s and less than or equal to 14m/s, the rainfall is less than or equal to 8mm/h and less than or equal to 18mm/h, judging that the camera has rainwater, the camera is blocked by the rainwater, the acquired image and video are partially blocked, the image and video are transferred into an AI pre-analysis module, noise is reduced through median filtering, an SSD target detection algorithm is utilized to identify an object, an OpenPose algorithm is utilized to detect a human body, a TLD target tracking algorithm is utilized to track the target, after a preset dangerous event is identified, a pre-analysis result is sent to a cloud in a warning mode, if the network signal intensity is less than-75 dBm, the serial data of the same area are received to judge the network signal intensity of the 5G camera in the same area, if the network signal intensity is less than-75 dBm, the signals are regarded as being affected by weather, otherwise, the equipment failure or network information shielding is judged;

when the wind speed is more than 14m/s and the rainfall is more than 18mm/h, judging that the camera has rainwater, the camera is blocked by the rainwater, acquiring all the images and videos, transferring the images and videos to an AI pre-analysis module, processing the images and videos through a deep learning rain removing network, fusing the images and videos to perform multi-frame image fusion analysis, performing target detection, human body detection and target tracking after the analysis is completed, optimizing and correcting tracking results by combining historical tracking data and target movement characteristics, forwarding the identified preset dangerous event to a cloud in an alarm mode after the correction is completed, temporarily storing the video stream or serial data in a data cache if the signal is less than-80 dBm, and re-supplementing the data after the network is recovered.

6. The 5G camera-based method for transmitting monitoring key data of weather and rain according to claim 5, wherein: the AI pre-analysis module further comprises, when the wind speed is more than 16m/s, the camera shakes, the acquired images and videos have the blurring phenomenon, the images and videos are transferred to the AI pre-analysis module, the images are subjected to low-filtering noise reduction, the images are extracted into non-moving frames, the moving information is calculated according to the pixel change between the two frames of images, the images are subjected to motion compensation according to the calculated moving information, and the processed images and videos are subjected to dangerous event identification.

7. The 5G camera-based method for transmitting monitoring key data of weather and rain according to claim 6, wherein: the key data stream comprises processed image and video data, wind speed and rain amount data, AI pre-analysis dangerous event types and a request camera steering instruction.

8. The 5G camera-based method for transmitting monitoring key data of weather and rain according to claim 7, wherein: the request camera steering instruction comprises the steps of sending a target tracking request to a cloud after the AI pre-analysis module identifies preset dangerous time, converting target tracking of recorded video into target tracking of a camera, and recording dangerous time states in real time.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that: the processor, when executing the computer program, implements the steps of the method of any one of claims 1 to 8.

10. A computer-readable storage medium having stored thereon a computer program, characterized by: the computer program, when executed by a processor, implements the method for monitoring critical data transfer based on weather and wind of a 5G camera according to any one of claims 1 to 8.