Construction site intelligent video monitoring data processing method and system

Abstract

The invention provides a construction site intelligent video monitoring data processing method and system, and the method comprises the steps: configuring corresponding monitoring equipment for each monitoring site based on the configuration information of a management end, and enabling the monitoring equipment to comprise fixed monitoring equipment and dynamic monitoring equipment; obtaining static monitoring data of the fixed monitoring equipment, performing video compression processing on the static monitoring data to obtain fixed-point transmission data, and sending the fixed-point transmission data to the management end; determining a monitoring mode of the dynamic monitoring equipment according to the structure attribute of the monitoring place, and determining an observation point of the dynamic monitoring equipment based on the monitoring mode; and acquiring real-time monitoring data acquired by the dynamic monitoring equipment based on the observation points, performing management and control analysis on the real-time monitoring data to obtain routing inspection transmission data, and sending the routing inspection transmission data to the management end.

Description

Technical Field

[0001] The present invention relates to data processing technologies, and in particular, to a method and system for processing intelligent video monitoring data at a construction site. Background Art

[0002] Construction safety has always been a key issue to be guarded against at a construction site. To improve the safety of production and life at the construction site, monitoring devices are generally installed at the construction site for monitoring.

[0003] In a traditional monitoring system, the data collected by monitoring devices is generally transmitted to a monitoring center in real time. However, since there are many monitoring devices at the construction site and the types of devices may also be different, for example, the monitoring devices may include monitoring cameras and drones, etc., and the data collected at different positions is also different. Transmitting all the data in real time will result in a huge transmission volume and reduce the transmission efficiency.

[0004] Therefore, how to reduce the data transmission volume of different types of monitoring devices and improve the data transmission efficiency has become an urgent problem to be solved today. Summary of the Invention

[0005] The present invention provides a method and system for processing intelligent video monitoring data at a construction site, which can reduce the data transmission volume of different types of monitoring devices and improve the data transmission efficiency.

[0006] In a first aspect of the present invention, there is provided a method for processing intelligent video monitoring data at a construction site, including: Configuring corresponding monitoring devices for each monitoring location based on the configuration information of the management terminal, where the monitoring devices include fixed monitoring devices and dynamic monitoring devices; Obtaining the static monitoring data of the fixed monitoring device, performing video compression processing on the static monitoring data to obtain fixed-point transmission data, and sending the fixed-point transmission data to the management terminal; Determining the monitoring mode of the dynamic monitoring device according to the structural attributes of the monitoring location, and determining the observation points of the dynamic monitoring device based on the monitoring mode; Obtaining the real-time monitoring data collected by the dynamic monitoring device based on the observation points, performing control and analysis on the real-time monitoring data to obtain patrol transmission data, and sending the patrol transmission data to the management terminal.

[0007] Optionally, in a possible implementation manner of the first aspect, obtaining the static monitoring data of the fixed monitoring device, performing video compression processing on the static monitoring data to obtain fixed-point transmission data, and sending the fixed-point transmission data to the management terminal includes: Obtaining the static monitoring data of the fixed monitoring device within the monitoring time period, comparing the similarity of multiple video frames corresponding to the static monitoring data to obtain the similarity values of adjacent video frames; Determine adjacent video frames whose similarity value is greater than or equal to the similarity threshold as the same compression group, and obtain the corresponding sub-monitoring time period of the compression group; Obtain the last video frame in the compression group as the compression frame, and copy the compression frame according to the number of video frames corresponding to the compression group to obtain multiple copied frames; Generate a compressed video segment corresponding to the sub-monitoring time period according to the copied frames, obtain the sub-video segment corresponding to the sub-monitoring time period in the static monitoring data, and replace the sub-video segment with the compressed video segment to obtain the fixed-point transmission data and send it to the management end.

[0008] Optionally, in a possible implementation manner of the first aspect, determine the monitoring mode of the dynamic monitoring device according to the structural attributes of the monitoring location, and determine the observation points of the dynamic monitoring device based on the monitoring mode, including: Analyze the structural attributes to obtain the floor attribute and the support attribute. The floor attribute corresponds to the upper structure monitoring mode, and the support attribute corresponds to the support structure monitoring mode. The monitoring mode includes the upper structure monitoring mode and the support structure monitoring mode; Obtain the top-down image collected by the dynamic monitoring device for the monitoring location based on the upper structure monitoring mode, and determine the observation points in the monitoring location that meet the top layer monitoring conditions according to the top-down image; Obtain the video image captured by the dynamic monitoring device for the monitoring location based on the acquisition route according to the support structure monitoring mode, and determine the observation points in the monitoring location that meet the support frame monitoring conditions based on the video image.

[0009] Optionally, in a possible implementation manner of the first aspect, obtain the top-down image collected by the dynamic monitoring device for the monitoring location based on the upper structure monitoring mode, and determine the observation points in the monitoring location that meet the top layer monitoring conditions according to the top-down image, including: Determine the mobile docking device corresponding to the dynamic monitoring device, and obtain the floor area of the mobile docking device; Retrieve the observation area template corresponding to the monitoring location and overlay it on the top-down image, and obtain the image area corresponding to the preset observation area in the top-down image as the area to be screened. The observation area template includes multiple preset observation areas; Perform a first screening on the area to be screened according to the floor area, and determine the area to be screened with an area greater than or equal to the occupied area ratio as the first screening area; Obtain the height judgment value and the operation density of the monitoring area corresponding to each first screening area in the monitoring location, and screen the monitoring area according to the height judgment value and the operation density, and determine the monitoring area that meets the height monitoring conditions and the operation monitoring conditions as the target area; Determine the center point of the target area as the observation point, and control the mobile docking device to move to the observation point. The top-level monitoring conditions include height monitoring conditions and operation monitoring conditions.

[0010] Optionally, in a possible implementation manner of the first aspect, obtain the height judgment value and operation density of the monitoring area corresponding to each of the primary screening areas in the monitoring area, and screen the monitoring area according to the height judgment value and operation density. Determine that the monitoring area that meets the height monitoring conditions and operation monitoring conditions is the target area, including: Obtain the monitoring areas corresponding to the primary screening areas in the monitoring area, count the first positioning quantity of the operation terminals within the positioning range corresponding to each monitoring area in the historical time period, and obtain the operation density according to the first positioning quantity; Count the total number of operation terminals in the monitoring area, obtain the operation density threshold according to the product of the density threshold ratio and the total number, determine that the monitoring area with the operation density greater than or equal to the operation density threshold meets the operation monitoring conditions, and determine the corresponding monitoring area as the height judgment area; Obtain the center point corresponding to each height judgment area as the area positioning point, and control the dynamic monitoring device to go to each area positioning point based on the same flight height; Obtain the height judgment value of the dynamic monitoring device and each height judgment area according to the infrared ranging unit of the dynamic monitoring device, determine that the height judgment area with the smallest height judgment value meets the height monitoring conditions, and determine the corresponding height judgment area as the target area.

[0011] Optionally, in a possible implementation manner of the first aspect, obtain the image video captured by the dynamic monitoring device for the monitoring area based on the acquisition route according to the support structure monitoring mode, and determine the observation point in the monitoring area that meets the support frame monitoring conditions based on the image video, including: Perform human recognition on the image video. When there are operation personnel in the image video, obtain the operation terminals within the range of the monitoring area as the target terminals; Obtain multiple docking points in the monitoring area and the observation range of the dynamic monitoring device, and based on the docking points, determine the monitoring range corresponding to each docking point according to the observation radius corresponding to the observation range; Count the second positioning quantity of the target terminals within each monitoring range in the historical monitoring time period, determine that the docking point with the largest second positioning quantity meets the support frame monitoring conditions, and determine the corresponding docking point as the observation point.

[0012] Optionally, in a possible implementation of the first aspect, obtaining the real-time monitoring data collected by the dynamic monitoring device based on the observation point, performing control and analysis on the real-time monitoring data, and sending the inspection and transmission data to the management end includes: Identifying the operators in the real-time monitoring data, and obtaining the operators who do not meet the operation wearing conditions as abnormal operators; Obtaining the predicted distance between the abnormal operator and the observation point, determining the actual distance between each operation end and the observation point in the monitoring area, and obtaining the operation end whose distance difference between the actual distance and the predicted distance is within the spacing error range as the abnormal end; When the first quantity of the abnormal ends is not equal to the second quantity of the abnormal operators, controlling the dynamic monitoring device to perform tracking processing on the abnormal operators to obtain the movement trajectories of the abnormal operators; Obtaining the movement trajectories of each operation end, determining the trajectory coincidence degree between each movement trajectory and the movement trajectory, and determining the operation end whose trajectory coincidence degree is greater than the trajectory similarity threshold as the abnormal end; Generating a reminder message and sending it to the abnormal end, and when there is an abnormal end, obtaining the identity information of the abnormal end, and generating inspection and transmission data according to the identity information and the real-time monitoring data and sending it to the management end.

[0013] Optionally, in a possible implementation of the first aspect, obtaining the predicted distance between the abnormal operator and the observation point, determining the actual distance between each operation end and the observation point in the monitoring area, and obtaining the operation end whose distance difference between the actual distance and the predicted distance is within the spacing error range as the abnormal end includes: Determining the contour area of the abnormal operator and inputting it into the ranging model, and obtaining the predicted distance output by the ranging model based on the contour area; Obtaining the current monitoring range of the dynamic monitoring device, and determining the operation end located within the current monitoring range as the determination end; Determining the actual distance between the positioning point of each determination end and the observation point, and obtaining the determination end whose distance difference between the actual distance and the predicted distance is within the spacing error range as the abnormal end.

[0014] Optionally, in a possible implementation of the first aspect, when the first quantity of the abnormal ends is not equal to the second quantity of the abnormal operators, controlling the dynamic monitoring device to perform tracking processing on the abnormal operators to obtain the movement trajectories of the abnormal operators includes: When the first quantity of the abnormal ends is not equal to the second quantity of the abnormal operators, obtaining the contour center point of the abnormal operator as the abnormal point; Align the abnormal point with the center point of the screen of the dynamic monitoring device, and obtain the lens rotation angle of the dynamic monitoring device; Determine the front view direction corresponding to the lens rotation angle, obtain the abnormal prediction distance corresponding to the abnormal contour according to the ranging model, and obtain the position point at the abnormal prediction distance from the observation point in the front view direction as the tracking point; Generate the action trajectory corresponding to the abnormal person according to multiple tracking points at adjacent moments within a preset time period.

[0015] In a second aspect of the present invention, there is provided a data processing system for intelligent video monitoring at a construction site, including: A configuration module for configuring corresponding monitoring devices for each monitoring location based on the configuration information of the management terminal, where the monitoring devices include fixed monitoring devices and dynamic monitoring devices; A compression module for obtaining the static monitoring data of the fixed monitoring device, performing video compression processing on the static monitoring data to obtain fixed-point transmission data and sending it to the management terminal; A monitoring module for determining the monitoring mode of the dynamic monitoring device according to the structural attributes of the monitoring location, and determining the observation point of the dynamic monitoring device based on the monitoring mode; A control module for obtaining the real-time monitoring data collected by the dynamic monitoring device based on the observation point, performing control analysis on the real-time monitoring data to obtain inspection transmission data and sending it to the management terminal.

[0016] The beneficial effects of the present invention are as follows: The present invention can reduce the data transmission volume of different types of monitoring devices and improve the data transmission efficiency. When transmitting the video data of the fixed monitoring device, the present invention will compress it before transmission, thereby reducing the data transmission volume and improving the data transmission efficiency. For locations that require flexible monitoring, the present invention will collect video data in different ways in combination with the structural attributes of different locations during monitoring, and will transmit the collected video data when there is an abnormality, and will not transmit it when there is no abnormality, thereby reducing the transmission volume of video data, improving the video transmission efficiency, and can also timely remind the management personnel of dangers and improve the safety of the construction site.

[0017] When monitoring the workers at the top of the floor, the present invention will first collect the top images through a drone, determine which positions can be docked for monitoring, and then select the areas where the workers are densely active for monitoring, so as to monitor the areas with higher risks and timely discover and prevent the occurrence of safety accidents. When monitoring the workers in the scaffolding, the present invention will first control the drone to collect videos of the scaffolding according to the configured route, and then judge whether there are workers in the scaffolding through the collected videos. When there are workers, the drone will be controlled to go to the area where the workers are most densely concentrated for monitoring.

[0018] When conducting control and analysis, the present invention will conduct a normative analysis on multiple workers in the video, judge whether there are workers who do not conform to the operation specifications, and remind the corresponding workers when there are abnormal workers, and transmit the corresponding videos to the management personnel, so as to improve the safety during operation and reduce the operation risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a schematic flow chart of a method for processing construction site intelligent video monitoring data provided by an embodiment of the present invention; Figure 2 is a schematic diagram of a scenario provided by an embodiment of the present invention; Figure 3 is a schematic diagram of a collection route provided by an embodiment of the invention; Figure 4 is a schematic structural diagram of a construction site intelligent video monitoring data processing system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0021] See Figure 1 , which is a schematic flow chart of a method for processing construction site intelligent video monitoring data provided by an embodiment of the present invention, Figure 1The execution entity of the method shown can be a software and / or hardware device. The execution entity of this application can include, but is not limited to, at least one of the following: user equipment, network equipment, etc. Among them, the user equipment can include, but is not limited to, a computer, a smart phone, a personal digital assistant (Personal Digital Assistant, abbreviated as: PDA), and the electronic devices mentioned above. The network equipment can include, but is not limited to, a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of computers or network servers based on cloud computing. Among them, cloud computing is a type of distributed computing, which consists of a group of loosely coupled computers forming a super virtual computer. This embodiment does not limit this. It includes steps S1 to S4, specifically as follows: S1, configure corresponding monitoring devices for each monitoring location based on the configuration information of the management end, where the monitoring devices include fixed monitoring devices and dynamic monitoring devices.

[0022] See Figure 2 , which is a schematic diagram of a scenario provided by an embodiment of the present invention. When the present solution performs construction site video transmission, it will first control the monitoring devices to collect videos of the construction site, and then process the videos through a video transmission terminal and transmit them to the management end for viewing.

[0023] The monitoring devices in this solution include dynamic monitoring devices and fixed monitoring devices. Among them, the dynamic monitoring device refers to a device that can flexibly collect data, such as a drone, a robot dog, and other more flexible monitoring devices. The fixed monitoring device refers to a device that collects videos of a fixed area, such as a fixed camera that monitors a certain fixed area.

[0024] It can be understood that there are many areas in the construction site, and the situations of different areas are also different. Therefore, the management personnel can pre-configure different monitoring devices for each location in the construction site according to different situations. For example, fixed cameras can be configured to monitor the main entrances and exits of the construction site, so as to stably and continuously monitor the main entrances and exits. For the top floors and scaffolding areas of the building, due to their complex structures, using fixed cameras may block the view. Therefore, drones can be controlled to perform more flexible monitoring at such locations.

[0025] Among them, the management end can be a terminal held by the management personnel, such as a computer. The configuration information refers to the information corresponding to the monitoring devices configured by the management personnel for each location in the construction site. The monitoring location refers to the area in the construction site that needs to be monitored, such as the construction site entrance, construction floors, scaffolding, etc.

[0026] S2, obtain the static monitoring data of the fixed monitoring device, perform video compression processing on the static monitoring data to obtain fixed-point transmission data, and send it to the management end.

[0027] When transmitting the video data of fixed monitoring devices, this solution will compress the data before transmission, thereby reducing the data transmission volume and improving the data transmission efficiency. It can be understood that if the video data of monitoring devices is transmitted in real time, it may lead to a huge amount of data during transmission and there may be duplicate data. For example, when there is no change in a certain area, there may be duplicate video frames in the transmitted video data. Therefore, when duplicate data exists in the monitored video, it can be compressed, and the redundant data can be removed before transmission.

[0028] Static monitoring data refers to the video data captured by a fixed camera in a fixed area, and fixed-point transmission data refers to the video data obtained after compressing the video data captured in a fixed area. Specifically, this solution will compress the duplicate data in the video data. In some embodiments, the method in step S2 can be implemented through the following embodiments: S21, obtain the static monitoring data of the fixed monitoring device during the monitoring time period, and compare the similarity of multiple video frames corresponding to the static monitoring data to obtain the similarity value of adjacent video frames.

[0029] The monitoring time period refers to the pre-set time period for video transmission. For example, data can be transmitted every half hour, and the video data in the past half hour can be transmitted during transmission. It can be understood that when there are duplicate segments in the video, the video frames within the corresponding time period may be the same. Therefore, it is possible to determine whether there is duplicate data in the video by the similarity of adjacent video frames.

[0030] S22, determine the adjacent video frames with the similarity value greater than or equal to the similarity threshold as the same compression group, and obtain the sub-monitoring time period corresponding to the compression group.

[0031] The similarity threshold refers to the similarity threshold, which can be pre-configured. If it is greater than or equal to this threshold, it means that the image similarity between video frames is very high. Therefore, the corresponding video frames can be used as a compression group, that is, the video frame group for video compression. The sub-monitoring time period refers to the time period where the video frames corresponding to the compression group are located.

[0032] S23, obtain the last video frame in the compression group as the compression frame, and copy the compression frame according to the number of video frames corresponding to the compression group to obtain multiple copied frames.

[0033] Due to the high similarity between video frames in the compression group, copying the last video frame can cover the data of other frames and display the latest monitoring data. For example, if the video data within a certain five minutes has not changed, the monitoring data within these five minutes can be displayed by copying the last video frame within these five minutes.

[0034] S24. Generate a compressed video segment corresponding to the sub-monitoring time period according to the copied frame, obtain a sub-video segment corresponding to the sub-monitoring time period in the static monitoring data, and replace the sub-video segment with the compressed video segment to obtain fixed-point transmission data and send it to the management end.

[0035] The compressed video segment can be obtained by splicing multiple copied frames. The sub-video segment refers to the original monitoring video segment corresponding to the sub-monitoring time period. Replacing it with the compressed video segment can reduce the storage space occupied by video data, lower the transmission cost, and thus improve the efficiency during video transmission.

[0036] S3. Determine the monitoring mode of the dynamic monitoring device according to the structural attributes of the monitoring location, and determine the observation point of the dynamic monitoring device based on the monitoring mode.

[0037] For locations that require flexible monitoring, this solution will collect video data in different ways in combination with the structural attributes of different locations during monitoring, and will transmit the collected video data when there is an abnormality, and will not transmit when there is no abnormality. This can reduce the amount of video data transmitted, improve the video transmission efficiency, and can also timely remind the management personnel of danger and improve the safety of the construction site.

[0038] Among them, the structural attribute refers to the structural characteristics of the monitoring location, including the floor structural characteristics and the support structural characteristics. This solution will perform different ways of video monitoring on the monitoring locations corresponding to the top of the floor and the scaffolding. During monitoring, different observation points will be determined according to different monitoring locations for monitoring, so that monitoring devices such as drones can obtain the largest monitoring range and improve the comprehensiveness of data during monitoring. The monitoring mode includes the mode of monitoring the top floor of the building and the mode of monitoring the scaffolding. The observation point refers to the position point where the monitoring device docks for monitoring. After the monitoring device docks at this position point, it can monitor the corresponding area. Compared with the monitoring device continuously moving and monitoring, using this method can reduce the energy consumption of the monitoring device during monitoring and improve the endurance of the monitoring device during monitoring.

[0039] Based on the above embodiments, the specific implementation manner of step S3 can be: S31. Analyze the structural attributes to obtain floor attributes and support attributes. The floor attributes correspond to the upper structure monitoring mode, and the support attributes correspond to the support structure monitoring mode. The monitoring modes include the upper structure monitoring mode and the support structure monitoring mode.

[0040] Among them, the floor attribute refers to the structural attribute corresponding to the top floor, the support attribute refers to the structural attribute corresponding to the scaffolding structure, the upper structure monitoring mode refers to the mode of performing safety monitoring on the top of the floor, and the support structure monitoring mode refers to the mode of performing safety monitoring on the scaffolding. Specifically, this solution will control the drone to monitor the operators at different locations, judge whether they comply with the operation specifications, and remind the management personnel in time when abnormalities occur.

[0041] S32. Based on the upper structure monitoring mode, obtain the top-down images collected by the dynamic monitoring device at the monitoring location, and determine the observation points at the monitoring location that meet the top floor monitoring conditions according to the top-down images.

[0042] In practical applications, the range where operators move may be different at different times. Therefore, when monitoring the operators on the top of the floor, the drone can first collect the top images to judge which positions can be used for docking and monitoring, and then select the areas where operators are densely active for monitoring, so as to monitor the areas with higher risks and discover and prevent the occurrence of safety accidents in time.

[0043] Specifically, when the observed position point meets both the condition of the operator density during monitoring and the condition of the highest observation height, that is, meets the top floor monitoring conditions, the corresponding position point can be used as an observation point. It can be understood that the reason for meeting the highest observation height is to make the observation range of the monitoring device reach the maximum. The higher the observation height, the higher the height of the monitoring device during collection, and the larger the coverage range during monitoring will be accordingly.

[0044] In some embodiments, step S32 can be implemented through the following steps: S321. Determine the mobile docking device corresponding to the dynamic monitoring device, and obtain the floor area of the mobile docking device.

[0045] The mobile docking device refers to the device for the drone to dock. For example, it can be a drone docking station, which can be configured with a buffer device and a stabilizing mechanism to ensure that the drone can maintain stability and safety when docking. It can also be configured with a mobile device, such as wheels, so that it can move to different position points for the drone to dock.

[0046] It can be understood that in order for the drone to rely on the mobile docking device for docking monitoring, it is first necessary to ensure that the mobile docking device can move to the corresponding position point. Therefore, the area of the corresponding position point must be greater than or equal to the occupied area of the mobile docking device to meet the movement conditions of the mobile docking device. So, after determining the mobile docking device corresponding to the drone, the occupied area of this device can be obtained.

[0047] S322, retrieve the observation area template corresponding to the monitoring area and overlay it on the top-down image, and obtain the image area corresponding to the preset observation area in the top-down image as the area to be screened. The observation area template includes multiple preset observation areas.

[0048] The observation area template can be pre-configured. Specifically, the drone can be first controlled to take pictures of the monitoring area according to the preset position points, and then the management personnel can select multiple position areas where the drone can perform docking monitoring from the taken pictures, and generate an observation area template based on these areas, that is, the template for docking area positioning. The preset observation area refers to the preset area where docking can be performed. Subsequently, different models of drones can be controlled to go to the corresponding position points to take top-down pictures of the monitoring area, and the shooting parameters during the top-down shooting can be the same, so as to quickly determine the areas in the monitoring area where docking monitoring can be performed and improve the data processing efficiency.

[0049] S323, perform a primary screening on the area to be screened according to the occupied area, and determine the area to be screened with an area greater than or equal to the occupied area as the primary screening area.

[0050] It can be understood that since the models of the monitoring devices for monitoring the monitoring area may be different, the corresponding mobile docking devices may also be different. Therefore, after determining multiple areas to be screened, the areas that can dock the mobile docking device can be screened out as the primary screening areas, and then combined with the operator density data and height data corresponding to the primary screening areas for secondary screening, so as to screen out the position areas that meet the requirements. The primary screening area is the area where the mobile docking device can dock.

[0051] S324, obtain the height judgment value and operation density of the monitoring area corresponding to each primary screening area in the monitoring area, and screen the monitoring area according to the height judgment value and operation density, and determine the monitoring area that meets the height monitoring conditions and operation monitoring conditions as the target area.

[0052] In practical applications, corresponding area monitoring positions can be configured for each primary screening area, so as to determine the monitoring areas corresponding to each primary screening area. The monitoring area is the area in the monitoring ground where the mobile docking device can dock. The height judgment value refers to the value for judging the observation height of each monitoring area, specifically referring to the interval distance between the drone and the corresponding monitoring area at the same flight height. The operation density refers to the density of operation personnel during operation in each monitoring area. The height monitoring condition means that when the operation monitoring condition is met, the corresponding observation height is the highest. The operation monitoring condition means that the activity density of the operation personnel exceeds the density threshold.

[0053] Specifically, in some embodiments, step S324 can be implemented in the following manner: S3241. Obtain the monitoring area corresponding to the primary screening area in the monitoring ground, count the first positioning quantity of the operation end in the positioning range corresponding to each monitoring area in the historical time period, and obtain the operation density according to the first positioning quantity.

[0054] The historical time period refers to the time period set in advance for counting the density of operation personnel. The positioning range refers to the range that can be monitored through the monitoring area. For example, it can be the monitoring range obtained based on the center point of the monitoring area and the maximum monitoring radius of the drone. The first positioning quantity refers to the positioning quantity of the operation end within the positioning range in the historical time period. Specifically, the positioning data of each operation end can be obtained, and then the number of operation ends whose positioning data appears within the positioning range in the historical time period can be counted. The operation end refers to the terminal held by the operation personnel, and the operation density is the first positioning quantity.

[0055] S3242. Count the total number of operation ends in the monitoring ground, obtain the operation density threshold according to the product of the density threshold ratio and the total number, determine that the monitoring area where the operation density is greater than or equal to the operation density threshold meets the operation monitoring condition, and determine the corresponding monitoring area as the height judgment area.

[0056] The density threshold ratio refers to the density percentage set in advance. For example, it can be 80%. By multiplying the total number of operation ends by this threshold ratio, the specific quantity corresponding to the density percentage, that is, the operation density threshold, can be obtained. If the operation density is greater than or equal to this threshold, it means that the density of operation personnel in the corresponding area is greater than or equal to the preset density ratio. This area may be the area where operation personnel often operate. Therefore, it can be determined that the corresponding area meets the operation monitoring condition and is used as the height judgment area, that is, the area for re-screening through the height value.

[0057] S3243. Obtain the center point of each height judgment area as the area positioning point, and control the dynamic monitoring device to go to each area positioning point at the same flight height.

[0058] When obtaining the height judgment values corresponding to each height judgment area, the positioning points for obtaining values in each height judgment area, that is, area positioning points, can be determined first, so that the UAV can be controlled to sequentially go to each area positioning point based on the same flight height to determine the height judgment values of each height judgment area.

[0059] S3244. According to the infrared ranging unit of the dynamic monitoring device, obtain the height judgment values of the dynamic monitoring device and each of the height judgment areas, determine that the height judgment area with the smallest height judgment value meets the height monitoring condition, and determine the corresponding height judgment area as the target area.

[0060] The infrared ranging unit refers to the unit for distance measurement. Through this unit, the interval height values between the UAV and each height judgment area, that is, the height judgment values, can be obtained. The smaller the height judgment value, the closer the distance between the height judgment area and the UAV. On the premise that the flight height of the UAV is the same, it indicates that the height of the corresponding area may be higher. Therefore, it can be determined that the height judgment area with the smallest height judgment value meets the height monitoring condition, and the obtained height judgment area is used as the finally selected target area.

[0061] S325. Determine the center point of the target area as the observation point, and control the mobile docking device to move to the observation point. The top-level monitoring conditions include height monitoring conditions and operation monitoring conditions.

[0062] After determining the observation point, the position information of the observation point can be sent to the mobile docking device, so that it can move to the corresponding position according to the position information for subsequent docking monitoring by the UAV. Through the above method, the position point during monitoring can be determined in combination with the actual situation, improving the comprehensiveness and flexibility during monitoring.

[0063] S33. According to the support structure monitoring mode, obtain the image video captured by the dynamic monitoring device for the monitored area based on the acquisition route, and determine the observation points in the monitored area that meet the support frame monitoring conditions based on the image video.

[0064] When monitoring the operators in the scaffolding, the UAV can be controlled to first perform video acquisition on the scaffolding according to the configured route, and then determine whether there are operators in the scaffolding through the acquired video, and control the UAV to go to the area with the most concentrated operators for monitoring when there are operators.

[0065] Among them, the acquisition route refers to the configured route for video acquisition of the scaffolding, see Figure 3 , which is a schematic diagram of an acquisition route provided by an embodiment of the invention. As Figure 3As shown, the acquisition route can be a route that flies around the scaffolding once, so that the scaffolding can be comprehensively video-captured, improving the accuracy during operation monitoring. The support frame monitoring condition refers to the condition corresponding to the most intensive activities of the operators when there are operators at the monitoring site.

[0066] In some embodiments, step S33 can be implemented through steps S331 to S333, specifically as follows: S331, perform person recognition on the image video. When there are operators in the image video, obtain the operation terminals within the monitoring site range as the target terminals.

[0067] In practical applications, it is possible to determine whether there are operators in the image video by performing portrait detection on the image video. When there are operators, determine the positioning information of the operators in the monitoring site through the positioning information of the operation terminals, so as to determine the area where the operators are most intensively active through the positioning information, and control the drone to fly to the corresponding area for monitoring. The target terminal is the operation terminal whose positioning information is within the monitoring site range.

[0068] S332, obtain multiple docking points in the monitoring site and the observation range of the dynamic monitoring device. Based on the docking points, determine the monitoring range corresponding to each docking point according to the observation radius corresponding to the observation range.

[0069] Among them, the docking point refers to a position point pre-set in the scaffolding for the drone to dock. A platform for the drone to dock can be set at this position point. The observation range can be the maximum monitoring range of the drone, the observation radius refers to the observation span corresponding to the observation range, and the monitoring range refers to the range that the drone can monitor at each docking point.

[0070] S333, count the second positioning quantity of the target terminals within each of the monitoring ranges during the historical monitoring time period, determine that the docking point with the largest second positioning quantity meets the support frame monitoring condition, and determine the corresponding docking point as the observation point.

[0071] The historical monitoring time period is a set time period for counting the positioning data of the operators in the monitoring site. The second positioning quantity refers to the positioning quantity of the operation terminals in each monitoring range during the historical monitoring time period. The larger the second positioning quantity, the more intensive the activities of the operators in the corresponding area. Therefore, it can be determined that the docking point corresponding to the area where the operators are most intensively active, that is, the area with the largest second positioning quantity, meets the support frame monitoring condition, and use it as the observation point for the final monitoring, so as to monitor the area with the highest risk level and improve the safety during operation.

[0072] S4. Obtain the real-time monitoring data collected by the dynamic monitoring device based on the observation point, perform control and analysis on the real-time monitoring data, and send the inspection and transmission data to the management terminal.

[0073] The real-time monitoring data refers to the real-time video collected by the dynamic monitoring device at the observation point. It can be understood that in order to reduce the data transmission volume of the video, this solution will only transmit the collected video data when an abnormal situation is detected. When performing control and analysis, this solution will perform a normative analysis on multiple operators in the video to determine whether there are operators who do not conform to the operation specifications, and will remind the corresponding personnel when there are abnormal personnel, and transmit the corresponding video to the management personnel, so as to improve the safety during operation and reduce the operation risk. The inspection and transmission data refers to the video data of abnormal personnel.

[0074] Based on the above embodiments, the specific implementation manner of step S4 can be: S41. Identify the operators in the real-time monitoring data, and obtain the operators who do not meet the operation wearing conditions as abnormal personnel.

[0075] In practical applications, the operators in the video data can be identified by means of face recognition. When there is an operator who does not wear a safety helmet, it can be determined that the corresponding person does not meet the operation wearing conditions and regard it as an abnormal person.

[0076] S42. Obtain the predicted distance between the abnormal person and the observation point, determine the actual distance between each operation end in the monitoring area and the observation point, and obtain the operation end whose distance difference between the actual distance and the predicted distance is within the spacing error range as the abnormal end.

[0077] It can be understood that since there are many operators in the construction site, if the identity information is matched one by one, it may increase the data processing volume. Therefore, in order to determine the terminal corresponding to the abnormal person and remind it, it can be determined by the predicted distance between the abnormal person and the observation point in the video and the actual distance between each operation end and the observation point. If the distance difference between the two is within the indirect error range, it means that the difference between the two is very small and may be corresponding. Therefore, the corresponding operation end can be determined as the abnormal end corresponding to the abnormal person, so as to improve the data processing efficiency.

[0078] Among them, the abnormal end is the terminal corresponding to the person who does not wear safety measures. Specifically, in some embodiments, the abnormal end can be determined by the following method: S421. Determine the contour area of the abnormal person and input it into the ranging model, and obtain the predicted distance output by the ranging model based on the contour area.

[0079] When determining the predicted distance between an abnormal person and an observation point, the distance between the abnormal person and the observation point can be predicted through the contour area of the abnormal person. The ranging model refers to a model that predicts distance data through image data. The management personnel can input multiple image data in advance for training, so that different contour area values of personnel can correspond to output different distance values. The predicted distance refers to the distance between the abnormal person and the observation point predicted based on the contour area.

[0080] S422. Obtain the current monitoring range of the dynamic monitoring device, and determine the operation end located within the current monitoring range as the judgment end.

[0081] In practical applications, the current monitoring range can be determined through the lens focal length and lens angle of the dynamic monitoring device. It can be understood that the video data captured by the dynamic monitoring device at different angles may be different. In practical applications, after the drone docks, the lens can rotate 360 degrees for monitoring, so that data around the observation point can be collected. When an abnormal person is captured, due to different rotation angles, the orientation of the captured abnormal person may also be different. Therefore, in order to improve the accuracy when determining the abnormal end, the operation end within the current monitoring range can be used as the judgment end, and then the abnormal end corresponding to the abnormal person can be screened out from each judgment end through the predicted distance.

[0082] Among them, the current monitoring range refers to the range that the current lens of the dynamic monitoring device can capture. Specifically, the monitoring direction corresponding to the rotation angle of the lens of the dynamic monitoring device can be determined first, and then the map corresponding to the monitoring location can be retrieved. The point corresponding to the observation point and the monitoring direction are determined on the map, and then the range determination frame corresponding to the lens focal length of the dynamic monitoring device is retrieved. Based on the observation point and the monitoring direction, the range determination frame is positioned, and the range corresponding to the range determination frame is determined as the current monitoring range. Then, the operation end whose positioning point is within the current monitoring range is used as the judgment end. The range determination frame can be a pre-set limiting frame for determining the shooting range corresponding to the corresponding lens focal length.

[0083] S423. Determine the actual distance between the positioning point of each judgment end and the observation point, and obtain the judgment end whose distance difference between the actual distance and the predicted distance is within the spacing error range as the abnormal end.

[0084] In practical applications, the actual distance can be determined through the point-to-point distance between the positioning point and the observation point. Through the above method, the data processing volume can be reduced and the data processing efficiency can be improved.

[0085] S43. When the first quantity of the abnormal ends is not equal to the second quantity of the abnormal persons, control the dynamic monitoring device to perform tracking processing on the abnormal persons to obtain the action trajectories of the abnormal persons.

[0086] In practical applications, it may occur that the distance between an abnormal person and other workers is very close. In this case, the terminals corresponding to other workers may also be misjudged as abnormal terminals, resulting in a mismatch between the number of abnormal terminals and the number of abnormal persons. Therefore, in order to improve the accuracy of determining abnormal terminals, when the number of abnormal terminals does not match the number of abnormal persons, this solution will track the abnormal persons to determine their corresponding movement trajectories, and determine the abnormal terminals corresponding to the abnormal persons based on the movement trajectories in the follow-up.

[0087] Among them, the first quantity is the number of terminals corresponding to the abnormal terminals, the second quantity is the number of persons corresponding to the abnormal persons, and the movement trajectory is the movement route of the abnormal persons. In some embodiments, the specific implementation manner of step S43 may be as follows: S431, when the first quantity of the abnormal terminals is not equal to the second quantity of the abnormal persons, obtain the center point of the outline of the abnormal persons as the abnormal point.

[0088] The abnormal point is the point used to track the abnormal persons. Subsequently, this solution will control the lens of the dynamic monitoring device to move and track through this point, so as to determine the movement trajectory of the abnormal persons based on the rotation angle of the lens of the dynamic monitoring device.

[0089] S432, align the abnormal point with the center point of the picture of the dynamic monitoring device, and obtain the rotation angle of the lens of the dynamic monitoring device.

[0090] It can be understood that in order to determine the movement trajectory of the abnormal persons, the abnormal persons can always be located at the center of the monitoring picture, so that the abnormal persons are always in the position directly in front of the lens. Thus, the direction where the abnormal persons are currently located can be determined through the rotation angle of the lens movement, and then the specific position point where they are located can be determined based on the predicted distance and direction between the abnormal persons and the observation point in the follow-up. The movement trajectory can be determined through multiple position points. The center point of the picture refers to the center point of the monitoring picture, and the rotation angle of the lens refers to the rotation angle of the lens of the dynamic monitoring device.

[0091] S433, determine the front view direction corresponding to the rotation angle of the lens, obtain the abnormal predicted distance corresponding to the abnormal outline according to the ranging model, and obtain the position point at the abnormal predicted distance from the observation point in the front view direction as the tracking point.

[0092] In practical applications, the front-facing direction corresponding to the rotation angle of the lens can be the direction corresponding to the front of the lens during shooting. When obtaining the abnormal prediction distance corresponding to the abnormal contour according to the ranging model, the area of the abnormal contour can also be input into the ranging model, and then the ranging model outputs the predicted distance, that is, the abnormal prediction distance. Then, a position point at an abnormal prediction distance from the observation point in the front-facing direction is determined as the tracking point corresponding to the abnormal person, that is, the point for tracking the route of the abnormal person.

[0093] S434. Generate the action trajectory corresponding to the abnormal person according to multiple tracking points at adjacent moments within a preset time period.

[0094] The preset time period is the time period set for tracking the abnormal person. For example, it can be 10 minutes. The action trajectory corresponding to the abnormal person is determined by the action position points (i.e., tracking points) of the abnormal person within 10 minutes.

[0095] S44. Obtain the movement trajectories of each operation terminal, determine the trajectory coincidence degree between each movement trajectory and the action trajectory, and determine the operation terminal with a trajectory coincidence degree greater than the trajectory similarity threshold as the abnormal terminal.

[0096] When obtaining the movement trajectory of the operation terminal, it can be obtained through the positioning points of each operation terminal within a preset time period. When determining the trajectory coincidence degree between the movement trajectory and the action trajectory, it can be determined by the distance between the position points corresponding to the movement trajectory and the action trajectory at the same moment. The position points with a distance less than the threshold are determined as the same position points. The number of the same position points is counted, and the trajectory coincidence degree is obtained according to the ratio between the number of the same position points and the number of all position points of the action trajectory. The trajectory similarity threshold is a threshold set in advance for judging the trajectory similarity. If it is greater than this threshold, it means that the corresponding trajectories are very similar. Therefore, the corresponding operation terminal can be regarded as an abnormal terminal.

[0097] S45. Generate a reminder message and send it to the abnormal terminal. When there is an abnormal terminal, obtain the identity information of the abnormal terminal, and generate inspection and transmission data according to the identity information and the real-time monitoring data and send it to the management terminal.

[0098] The reminder message is information for warning the abnormal terminal about safety, which can be information reminding it to wear safety measures. Each abnormal terminal can be bound with corresponding identity information. By sending the identity information and real-time monitoring data to the management terminal, the management personnel can timely discover the abnormal person in the construction site and the actual situation on site, and thus make targeted treatment strategies to improve operation safety.

[0099] See Figure 4, which is a schematic structural diagram of a construction site intelligent video monitoring data processing system provided by an embodiment of the present invention. The construction site intelligent video monitoring data processing system includes: A configuration module, configured to configure corresponding monitoring devices for each monitoring site based on the configuration information of the management terminal. The monitoring devices include fixed monitoring devices and dynamic monitoring devices; A compression module, configured to obtain the static monitoring data of the fixed monitoring device, perform video compression processing on the static monitoring data to obtain fixed-point transmission data, and send the fixed-point transmission data to the management terminal; A monitoring module, configured to determine the monitoring mode of the dynamic monitoring device according to the structural attributes of the monitoring site, and determine the observation points of the dynamic monitoring device based on the monitoring mode; A control module, configured to obtain the real-time monitoring data collected by the dynamic monitoring device based on the observation points, perform control analysis on the real-time monitoring data to obtain inspection transmission data, and send the inspection transmission data to the management terminal.

[0100] Figure 4 The device in the illustrated embodiment can correspondingly be used to execute Figure 1 the steps in the illustrated method embodiment. The implementation principle and technical effects are similar and will not be elaborated here.

[0101] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for processing intelligent video monitoring data at a construction site, characterized in that, Including: Configuring corresponding monitoring devices for each monitoring location based on the configuration information of the management terminal, where the monitoring devices include fixed monitoring devices and dynamic monitoring devices; Obtaining the static monitoring data of the fixed monitoring devices, performing video compression processing on the static monitoring data to obtain fixed-point transmission data and sending it to the management terminal; Determining the monitoring mode of the dynamic monitoring devices according to the structural attributes of the monitoring location, and determining the observation points of the dynamic monitoring devices based on the monitoring mode; Obtaining the real-time monitoring data collected by the dynamic monitoring devices based on the observation points, performing control and analysis on the real-time monitoring data to obtain patrol transmission data and sending it to the management terminal.

2. The method according to claim 1, wherein: Obtaining the static monitoring data of the fixed monitoring devices, performing video compression processing on the static monitoring data to obtain fixed-point transmission data and sending it to the management terminal, includes: Obtaining the static monitoring data of the fixed monitoring devices within the monitoring time period, comparing the similarity of multiple video frames corresponding to the static monitoring data to obtain the similarity values of adjacent video frames; Determining adjacent video frames with similarity values greater than or equal to the similarity threshold as the same compression group, and obtaining the sub-monitoring time period corresponding to the compression group; Obtaining the last video frame in the compression group as the compression frame, and copying the compression frame according to the number of video frames corresponding to the compression group to obtain multiple copied frames; Generating a compressed video segment corresponding to the sub-monitoring time period according to the copied frames, obtaining the sub-video segment corresponding to the sub-monitoring time period in the static monitoring data, and replacing the sub-video segment with the compressed video segment to obtain fixed-point transmission data and sending it to the management terminal.

3. The method according to claim 1, wherein: Determining the monitoring mode of the dynamic monitoring devices according to the structural attributes of the monitoring location, and determining the observation points of the dynamic monitoring devices based on the monitoring mode, includes: Analyzing the structural attributes to obtain the floor attribute and the support attribute, where the floor attribute corresponds to the upper structure monitoring mode, the support attribute corresponds to the support structure monitoring mode, and the monitoring mode includes the upper structure monitoring mode and the support structure monitoring mode; Obtaining the overhead images collected by the dynamic monitoring devices for the monitoring location based on the upper structure monitoring mode, and determining the observation points in the monitoring location that meet the top layer monitoring conditions according to the overhead images; Obtaining the video images captured by the dynamic monitoring devices for the monitoring location based on the acquisition route according to the support structure monitoring mode, and determining the observation points in the monitoring location that meet the support frame monitoring conditions based on the video images.

4. The method according to claim 3, wherein: Obtaining the overhead images collected by the dynamic monitoring devices for the monitoring location based on the upper structure monitoring mode, and determining the observation points in the monitoring location that meet the top layer monitoring conditions according to the overhead images, includes: Determining the mobile docking device corresponding to the dynamic monitoring device, and obtaining the floor area of the mobile docking device; Retrieve the observation area template corresponding to the monitored area and overlay it on the aerial image, and obtain the image area corresponding to the preset observation area in the aerial image as the area to be screened. The observation area template includes multiple preset observation areas; Perform a primary screening on the area to be screened according to the floor area, and determine that the area to be screened with an area greater than or equal to the proportion area is the primary screening area; Obtain the height judgment value and operation density of the monitoring area corresponding to each of the primary screening areas in the monitored area, and screen the monitoring area according to the height judgment value and operation density, and determine that the monitoring area that meets the height monitoring condition and operation monitoring condition is the target area; Determine the center point of the target area as the observation point, and control the mobile docking device to move to the observation point. The top-level monitoring conditions include height monitoring conditions and operation monitoring conditions.

5. The method according to claim 4, wherein Obtain the height judgment value and operation density of the monitoring area corresponding to each of the primary screening areas in the monitored area, and screen the monitoring area according to the height judgment value and operation density, and determine that the monitoring area that meets the height monitoring condition and operation monitoring condition is the target area, including: Obtain the monitoring area corresponding to the primary screening area in the monitored area, count the first positioning quantity of the operation end in the positioning range corresponding to each monitoring area in the historical time period, and obtain the operation density according to the first positioning quantity; Count the total number of operation ends in the monitored area, obtain the operation density threshold according to the product of the density threshold ratio and the total number, determine that the monitoring area with the operation density greater than or equal to the operation density threshold meets the operation monitoring condition, and determine the corresponding monitoring area as the height judgment area; Obtain the center point corresponding to each height judgment area as the area positioning point, and control the dynamic monitoring device to go to each area positioning point based on the same flight height; Obtain the height judgment value between the dynamic monitoring device and each height judgment area according to the infrared ranging unit of the dynamic monitoring device, determine that the height judgment area with the smallest height judgment value meets the height monitoring condition, and determine the corresponding height judgment area as the target area.

6. The method according to claim 3, wherein Obtain the image video of the monitored area taken by the dynamic monitoring device based on the acquisition route according to the support structure monitoring mode, and determine the observation point in the monitored area that meets the support frame monitoring condition based on the image video, including: Perform human recognition on the image video. When there are operating personnel in the image video, obtain the operation end within the scope of the monitored area as the target end; Obtain multiple docking points in the monitored area and the observation range of the dynamic monitoring device, and take the docking point as the reference, and determine the monitoring range corresponding to each docking point according to the observation radius corresponding to the observation range; Count the second positioning quantity of the target end in each monitoring range during the historical monitoring time period, determine that the docking point with the largest second positioning quantity meets the support frame monitoring condition, and determine the corresponding docking point as the observation point.

7. The method according to claim 4 or 6, characterized in that obtaining the real-time monitoring data collected by the dynamic monitoring device based on the observation point, and performing control analysis on the real-time monitoring data to obtain inspection and transmission data and sending it to the management end, includes: identifying the operators in the real-time monitoring data, and obtaining the operators who do not meet the operation wearing conditions as abnormal personnel; obtaining the predicted distance between the abnormal personnel and the observation point, determining the actual distance between each operation end in the monitoring area and the observation point, and obtaining the operation end whose distance difference between the actual distance and the predicted distance is within the spacing error range as the abnormal end; when the first number of the abnormal ends is not equal to the second number of the abnormal personnel, controlling the dynamic monitoring device to perform tracking processing on the abnormal personnel to obtain the action trajectory of the abnormal personnel; obtaining the movement trajectories of each operation end, determining the trajectory coincidence degree between each movement trajectory and the action trajectory, and determining the operation end whose trajectory coincidence degree is greater than the trajectory similarity threshold as the abnormal end; generating a reminder message and sending it to the abnormal end, and when there is an abnormal end, obtaining the identity information of the abnormal end, and generating inspection and transmission data according to the identity information and the real-time monitoring data and sending it to the management end.

8. The method according to claim 7, characterized in that obtaining the predicted distance between the abnormal personnel and the observation point, determining the actual distance between each operation end in the monitoring area and the observation point, and obtaining the operation end whose distance difference between the actual distance and the predicted distance is within the spacing error range as the abnormal end, includes: determining the contour area of the abnormal personnel and inputting it into the ranging model, and obtaining the predicted distance output by the ranging model based on the contour area; obtaining the current monitoring range of the dynamic monitoring device, and determining the operation end located within the current monitoring range as the judgment end; determining the actual distance between the positioning point of each judgment end and the observation point, and obtaining the judgment end whose distance difference between the actual distance and the predicted distance is within the spacing error range as the abnormal end.

9. The method according to claim 8, characterized in that when the first number of the abnormal ends is not equal to the second number of the abnormal personnel, controlling the dynamic monitoring device to perform tracking processing on the abnormal personnel to obtain the action trajectory of the abnormal personnel, includes: when the first number of the abnormal ends is not equal to the second number of the abnormal personnel, obtaining the contour center point of the abnormal personnel as the abnormal point; aligning the abnormal point with the center point of the screen of the dynamic monitoring device, and obtaining the lens rotation angle of the dynamic monitoring device; determining the front view direction corresponding to the lens rotation angle, obtaining the abnormal predicted distance corresponding to the abnormal contour according to the ranging model, and obtaining the position point spaced from the observation point by the abnormal predicted distance in the front view direction as the tracking point; generating the action trajectory corresponding to the abnormal personnel according to multiple tracking points at adjacent moments within a preset time period.

10. An intelligent video monitoring data processing system for construction sites, characterized in that, including: A configuration module, which is used to configure corresponding monitoring devices for each monitoring location based on the configuration information of the management terminal, and the monitoring devices include fixed monitoring devices and dynamic monitoring devices; A compression module, which is used to obtain the static monitoring data of the fixed monitoring device, perform video compression processing on the static monitoring data to obtain fixed-point transmission data and send it to the management terminal; A monitoring module, which is used to determine the monitoring mode of the dynamic monitoring device according to the structural attributes of the monitoring location, and determine the observation points of the dynamic monitoring device based on the monitoring mode; A control module, which is used to obtain the real-time monitoring data collected by the dynamic monitoring device based on the observation points, perform control analysis on the real-time monitoring data to obtain inspection transmission data and send it to the management terminal.

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