Safe air-ground cooperative monitoring unmanned aerial vehicle system for public event disaster exploration

Abstract

The invention discloses a public event disaster exploration safety air-ground cooperative monitoring unmanned aerial vehicle system. The system comprises an exploration task preprocessing module, an air-ground cooperative monitoring module, an exploration terminal monitoring and early warning module and an emergency auxiliary processing module. Based on the unmanned aerial vehicle platform, the artificial investigation process of the public event risk disaster hidden danger point is monitored in real time, and air-ground cooperative artificial investigation safety monitoring, early warning and rescue guarantee of the public event risk disaster hidden danger point is provided, so that the safety guarantee capability of the artificial investigation work of the public event risk disaster hidden danger point can be effectively improved; and the life and property safety of public event risk disaster exploration personnel is guaranteed to the maximum extent.

Description

Technical Field

[0001] This invention patent relates to the application field of drones for exploring potential hazards of public event disasters, and specifically relates to a drone system for collaborative monitoring of public event disaster exploration with safety in the air and on the ground. Background Art

[0002] In recent years, as a carrier platform with outstanding characteristics such as strong mobility, good convenience, and multiple payload modules, drones have been increasingly widely used in the fields of early warning and monitoring of various public event risk disasters, such as data collection and monitoring of potential hazard points in the prevention of public event risk disasters, reconnaissance and assessment in flood and drought disaster rescue, and disaster data collection. Based on the drone carrier, the application of technologies such as remote sensing, geographic information, Beidou positioning, 5G communication, artificial intelligence, and big data can greatly improve the efficiency of prevention and rescue work for various sudden public event disasters.

[0003] Although the new generation of information technology mainly based on drones has been widely used in the field of public event risk disasters, reducing the workload of on-site exploration and investigation of many potential hazard points, due to the extremely professional and complex characteristics of public event risk disasters, in order to accurately and truly grasp the comprehensive information of public event risk potential hazard points, the on-site exploration work carried out by professional personnel is still an essential link. Since many potential hazard points are often located in areas inaccessible to humans and with inconvenient transportation or areas with large potential disaster hazards themselves, which pose potential hazards to personal safety, there are serious potential safety hazards for professional personnel during the on-site exploration process. On the one hand, there is no real-time monitoring and early warning of the safety status of exploration personnel during the exploration process, and on the other hand, there is no real-time tracking of the exploration process, resulting in a lag in rescue work in case of sudden accidents. Therefore, in view of the actual situation that drone technology has been widely used in the prevention and rescue work of public event risk disasters, making full use of the characteristics of the drone flight platform to build a drone system for collaborative monitoring of public event disaster exploration with safety in the air and on the ground can effectively improve the safety guarantee ability of manual exploration work for public event risk disaster potential hazard points and maximize the protection of the life and property safety of public event risk disaster exploration personnel. Summary of the Invention

[0004] The purpose of the present invention is to provide a drone system for collaborative monitoring of public event disaster exploration with safety in the air and on the ground in view of the deficiencies of the prior art. This system can real-time monitor the manual exploration process of public event risk disaster potential hazard points based on the drone platform and provide safety monitoring, early warning, and rescue guarantee for manual exploration of public event risk disaster potential hazard points with collaboration between the air and the ground.

[0005] To achieve the above purpose, the technical solution adopted by the present invention is as follows: A collaborative monitoring UAV system for public event disaster exploration safety in the air and on the ground, the key lies in: including an exploration task preprocessing module, an air-ground collaborative monitoring module, an exploration terminal monitoring and early warning module, and an emergency assistance handling module, where: The exploration task preprocessing module is used to implement the preprocessing of specific exploration tasks and data; The air-ground collaborative monitoring module is used to monitor the exploration process of exploration personnel at public event risk disaster hidden danger points in real time by integrating the monitoring information of UAV on-board equipment, terminal equipment carried by exploration personnel, and multi-source monitoring equipment, and dynamically analyze situations such as deviation from the task planning scheme and potential risks; The exploration terminal monitoring and early warning module is used to provide exploration personnel with real-time monitoring status reminders and early warning information, and prompt exploration personnel to carry out exploration work according to the safety plan through active response and passive response and other methods; The emergency assistance handling module is used to provide auxiliary support for exploration personnel to self-rescue from danger or for external rescue personnel to carry out rescue work in case of safety accidents of exploration personnel.

[0006] Further, the exploration task preprocessing module includes a spatial data preprocessing sub-module, an exploration task preprocessing sub-module, an intelligent exploration route planning sub-module, an exploration identification learning sub-module, and a full-process intelligent self-inspection sub-module, where: The spatial data preprocessing sub-module is integrated and encapsulated based on mature GIS commercial software, and is used for the storage, management, and analysis of geospatial data within a certain range around the exploration task of specific public event risk disaster hidden danger points; the geospatial data includes information such as terrain, landform, traffic, water system, and buildings, structures, obstacles, etc.; The exploration task preprocessing sub-module is used to preprocess the data related to the exploration task of specific public event risk disaster hidden danger points, input and extract information such as exploration time, exploration route, exploration points, exploration personnel, etc. related to the exploration task of public event risk disaster hidden danger points, and store the above data; The intelligent exploration route planning sub-module is used to plan the inspection route and inspection range for the exploration task of specific public event risk disaster hidden danger points. According to the starting point and ending point of the route input by exploration personnel, based on the spatial data processed by the spatial data preprocessing sub-module, the exploration task data processed by the exploration task preprocessing sub-module, and the GIS spatial analysis function, use the man-machine interaction method to plan a reasonable inspection route for exploration personnel and set an effective exploration monitoring and early warning range, and preset a following flight plan for the monitoring UAV; The exploration identification learning sub-module is used to input, extract, and automatically learn the characteristics of exploration personnel who need to be monitored and warned, as well as their attached identification elements. By means of text, voice, and taking pictures, basic characteristic information such as the height, weight, clothing color, and special identification worn by exploration personnel is input. The characteristic portrait of exploration personnel is established by extracting characteristics, enabling the UAV to track the status of exploration personnel in real time based on the characteristic portrait when performing tasks. The full-process intelligent self-check sub-module is used to complete the preprocessing of exploration task data and then conduct full-process simulation operation self-check according to the actual exploration process to ensure that each module can work normally when the task is actually executed.

[0007] Furthermore, the air-ground collaborative monitoring module includes a multi-mode collaborative monitoring sub-module, an environmental mutation monitoring sub-module, a multi-source monitoring data fusion sub-module, and a comprehensive analysis sub-module, where: The multi-mode collaborative monitoring sub-module follows and monitors the real-time movement trajectory of exploration personnel based on the multi-mode collaborative monitoring mode combining feature image recognition and Beidou positioning, provides support for the risk warning analysis of exploration personnel, and guides and controls the UAV to automatically follow. The environmental mutation monitoring sub-module monitors the changes in the surrounding environment of the exploration task through the UAV's own flight state monitoring and sensor monitoring information, providing support for the risk warning analysis of exploration personnel. The multi-source monitoring data fusion sub-module is used to access and fuse the real-time monitoring information of multi-source public event risk disaster monitoring equipment already installed at exploration potential hazard points, providing support for the risk warning analysis of exploration personnel. The comprehensive analysis sub-module conducts comprehensive analysis based on the monitoring data obtained by the multi-mode collaborative monitoring sub-module, the environmental mutation monitoring sub-module, and the multi-source monitoring data fusion sub-module, and outputs the corresponding risk warning analysis results of exploration personnel.

[0008] Furthermore, the multi-mode collaborative monitoring sub-module calculates the position of exploration personnel through two modes of collaboration and guides the UAV to follow and monitor. One is the feature image recognition mode. Using the pre-established characteristic portrait of exploration personnel, the position coordinates P of exploration personnel are obtained through a mature monocular vision method. t , and the other is the Beidou positioning mode. Using the Beidou positioning function of the mobile terminal carried by exploration personnel, the real-time position coordinates P of exploration personnel are obtained. b , and according to the size of the confidence factor Z, the real-time position coordinates of exploration personnel are calculated. , where the confidence factor Z = SQI / 70, where SQI ( )(It) is the signal quality indication index of the Beidou positioning device on the terminal device carried by the survey personnel. This index comprehensively considers various factors such as the signal strength, signal stability, interference degree, and bit error rate of Beidou positioning, and measures the quality of the Beidou satellite signals received by the terminal. The method for the drone to follow and monitor is as follows: In the first step, taking the real-time position coordinate P of the survey personnel as the center and a certain distance as the radius, a circular area is calculated. In the second step, according to the pre-processed geospatial data, the terrain height is calculated using the spatial operation function of GIS, and the distribution of various buildings, structures, obstacles, etc. is analyzed to obtain the flight routes available for the drone within the circular area. In the third step, feature points of the survey personnel, such as the corner points and edges of the survey personnel, are extracted from the images obtained by the drone camera and compared with the pre-established feature portraits of the survey personnel. If the matching rate of the feature point comparison reaches or exceeds 50%, that position is selected for follow-up monitoring. If the comparison matching rate is lower than 50%, the position and attitude of the drone within the circular area are adjusted until the comparison matching rate reaches or exceeds 50%. If there is no area in the circular area with a comparison matching rate reaching or exceeding 50%, it indicates that there are many obstructions in the current inspection route of the survey personnel, and the drone sends a command to the terminal device carried by the survey personnel, asking the survey personnel to adjust the inspection route in a timely manner; Further, the environmental mutation monitoring sub-module obtains information on the changes in wind speed, wind direction, temperature, air pressure, and precipitation in the current environment through the flight state of the drone itself, and obtains mutation information on the terrain, landform, and related appendages within the range of the inspection route of the survey personnel through continuous frame comparison of video images; Further, the steps for the comprehensive analysis sub-module to conduct comprehensive analysis include: In the first step, using the GIS spatial calculation function, various monitoring data obtained by the multi-mode collaborative monitoring sub-module, the environmental mutation monitoring sub-module, and the multi-source monitoring data fusion sub-module are matched to the corresponding spatial positions and displayed in the form of an electronic map. In the second step, the above monitoring data is compared with the historical inspection and monitoring data of the risk disaster hidden points of public events in the survey, and similar areas and similar monitoring data are excluded, and the monitoring mutation point data that has not appeared before is retained. In the third step, the above monitoring mutation point data is sent to the terminal device carried by the survey personnel in the form of early warning information to remind the survey personnel to pay attention to protection; Further, the inspection terminal monitoring and early warning module includes a motion state monitoring sub-module, an over-limit early warning sub-module, a passive response sub-module, and an intervention command sub-module, where: The motion state monitoring sub-module monitors the motion state of the survey personnel during the on-site inspection process using the motion sensing device of the survey personnel's terminal device, including the motion speed and direction of the survey personnel, and monitors the real-time position coordinates of the survey personnel using the Beidou positioning device; The over-limit warning sub-module performs real-time warning and reminder for situations beyond the pre-planned inspection route, exploration monitoring, and warning range; The passive response sub-module is used to adjust its inspection route or movement mode according to the warning information and reply in a timely manner after the exploration personnel's terminal device receives the warning information sent by the air-ground collaborative monitoring module; The intervention command sub-module is used to issue instructions from the exploration personnel's terminal device to command the adjustment of the inspection route when the exploration personnel are unable to conduct inspections according to the pre-set planned route due to the complexity of the actual exploration work at the potential hazard points of public event risks and many emergencies; Further, the steps for the intervention command sub-module to adjust the inspection route include: the first step is for the exploration personnel to re-select the inspection route on the map through the terminal device and submit it to the exploration task pre-processing module; the second step is for the exploration task pre-processing module to call the intelligent inspection route planning sub-module to optimize the new inspection route through the man-machine interaction operation of the exploration task participants; the third step is after determining the new inspection route, the exploration personnel conduct on-site exploration using the new inspection route and command the drone to update the inspection route to conduct air-ground collaborative monitoring according to the new route.

[0009] Further, the emergency event auxiliary disposal module includes an emergency event rapid response sub-module, a drone search and rescue sub-module, and an air-ground response sub-module, where: The emergency event rapid response sub-module integrates the information of the exploration personnel's terminal device and the drone monitoring information, combines the spatial data and inspection route set by the exploration task pre-processing module, activates the emergency event rapid response function at different levels according to the exploration personnel's risk matrix analysis method, and supports the emergency event rapid response requirements of the air-ground collaborative exploration personnel through the dispatching command of man-machine interaction, the call response of air-ground information, and the real-time summary and analysis of air-ground information; Further, the exploration personnel's risk matrix analysis method calculates the risk level of the current exploration task by using the matrix analysis method according to the different levels of the monitoring of the connection status between the drone and the exploration terminal by the air-ground collaborative monitoring module and the exploration terminal monitoring and warning module and the monitoring of environmental mutations, and determines whether to activate the emergency event rapid response function of the emergency event rapid response sub-module according to the preset risk level threshold; Furthermore, the matrix analysis method is a method for semi-qualitative analysis of risks based on a two-dimensional coordinate table. The specific steps are to use the link status of the drone and the survey terminal as the monitoring accessibility index T, quantified according to a 1-5 point system as the horizontal coordinate value of the coordinate matrix, and the environmental mutation monitoring status as the potential hazard index W, quantified according to a 1-5 point system as the vertical coordinate value of the coordinate matrix, and then obtain the risk level value R according to R=T×W to form a risk matrix, and then divide it into four levels of green, orange, yellow and red according to the value of R from small to large, representing no risk, low risk, medium risk and high risk status respectively; After the emergency rapid response submodule is started, the drone search and rescue submodule quickly searches and locates the on-site survey personnel in the current survey mission status according to the command of the emergency rapid response submodule, and sends drone search information to the emergency rapid response submodule in real time; The air-to-ground response submodule continuously polls and calls through wireless transmission signals such as WiFi, 5G, UHF / VHF, etc., to establish a communication link between the drone and the ground survey personnel terminal to find out the status of the emergency or eliminate and resolve the potential risk status.

[0010] The remarkable effects of the present invention are: 1. By combining drones with GIS technology, real-time monitoring of the safety of surveyors during the survey of potential disaster sites in public events is achieved, providing effective support for the safety of surveyors; 2. Based on the use of GIS spatial analysis and matrix analysis methods, real-time analysis and intelligent judgment of the safety of surveyors can be achieved, the efficiency of monitoring and early warning can be improved, and the safety of on-site surveyors can be provided with the capabilities of pre-prevention, in-process monitoring and early warning, and post-event rapid response, thereby maximizing the personal safety of surveyors. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a system structure block diagram of the present invention; Figure 2 It is a schematic diagram of the structure of the exploration task preprocessing module; Figure 3 It is a structural diagram of the air-ground collaborative monitoring module; Figure 4 It is a structural diagram of the monitoring and early warning module of the survey terminal; Figure 5 It is a structural diagram of the emergency auxiliary handling module. DETAILED DESCRIPTION

[0012] The specific implementation manner and working principle of the present invention are further described in detail below with reference to the accompanying drawings.

[0013] like Figure 1As shown in the figure, a collaborative monitoring UAV system for public event disaster exploration safety in the air and on the ground consists of an exploration task preprocessing module, an air-ground collaborative monitoring module, an exploration terminal monitoring and warning module, and an emergency assistance and disposal module, where: The exploration task preprocessing module is used to implement the preprocessing of specific exploration tasks and data; The air-ground collaborative monitoring module is used to monitor the exploration process of exploration personnel at public event risk disaster hidden danger points in real time by integrating the monitoring information of UAV on-board equipment, terminal equipment carried by exploration personnel, and multi-source monitoring equipment, and dynamically analyze situations such as deviation from the task planning scheme and potential risks; The exploration terminal monitoring and warning module is used to provide exploration personnel with real-time monitoring status reminders and warning information, and prompt exploration personnel to carry out exploration work according to the safety plan through active response and passive response methods; The emergency assistance and disposal module is used to provide auxiliary support for exploration personnel to self-rescue from danger or for external rescue personnel to carry out rescue work in case of safety accidents of exploration personnel.

[0014] In this example, the exploration task preprocessing module consists of a spatial data preprocessing sub-module, an exploration task preprocessing sub-module, an intelligent exploration route planning sub-module, an exploration identification learning sub-module, and a full-process intelligent self-checking sub-module, as Figure 2 shown in the figure, where: The spatial data preprocessing sub-module is integrated and encapsulated based on mature GIS commercial software, and is used for the storage, management, and analysis of geographical spatial data within a certain range around the exploration task of specific public event risk disaster hidden danger points; the geographical spatial data includes information such as terrain, landform, traffic, water system, as well as buildings, structures, obstacles, etc., such as contour lines and elevation points representing elevation, and various grades of roads, highways, railways, airports, etc. representing traffic; the certain range is set according to the types of public event risk disaster hidden danger points, such as 500 meters, 1000 meters, etc.; the storage and management functions of the geographical spatial data include data import and export, data editing and modification, and data directory reorganization; the analysis functions of the geographical spatial data include buffer analysis, overlay analysis, topological analysis, visibility analysis, etc.; The exploration task preprocessing sub-module is used to preprocess data related to the exploration task of specific public event risk disaster hidden danger points, input and extract information such as exploration time, exploration route, exploration points, exploration personnel, etc. related to the exploration task of public event risk disaster hidden danger points, and store the above data; the exploration route is represented intuitively by an electronic map in the form of GIS spatial data; the exploration personnel information includes information such as personnel name, age, gender, height, weight, etc.; The intelligent exploration route planning sub-module is used to plan the inspection route and inspection scope for the inspection tasks of specific public event risk disaster hidden danger points. According to the starting and ending points of the route input by the exploration personnel, based on the spatial data processed by the spatial data preprocessing sub-module, the exploration task data processed by the exploration task preprocessing sub-module, and the GIS spatial analysis function, it uses a human-computer interaction method to plan a reasonable inspection route for the exploration personnel and set an effective exploration monitoring and early warning range, and preset a following flight plan for the monitoring UAV; The exploration identification learning sub-module is used to input, extract and automatically learn the characteristics of the exploration personnel to be monitored and warned and their attached identification elements. The basic characteristic information such as the height, weight, clothing color, and special identification worn by the exploration personnel is input through methods such as text, voice, and taking pictures. The characteristic portrait of the exploration personnel is established by extracting the characteristics, so that the UAV can track the state of the exploration personnel in real time based on the characteristic portrait when performing tasks; The full-process intelligent self-check sub-module is used to complete the preprocessing of exploration task data, and then perform a full-process simulation operation self-check according to the actual exploration process to ensure that each module can work normally when the task is actually executed.

[0015] In this example, the air-ground collaborative monitoring module is composed of a multi-mode collaborative monitoring sub-module, an environmental mutation monitoring sub-module, a multi-source monitoring data fusion sub-module, and a comprehensive analysis sub-module, as Figure 3 shown, where: The multi-mode collaborative monitoring sub-module is based on a multi-mode collaborative monitoring mode that combines feature image recognition and Beidou positioning to follow and monitor the real-time action trajectory of the exploration personnel, provide support for the risk early warning analysis of the exploration personnel, and guide and control the UAV to automatically follow; The environmental mutation monitoring sub-module monitors the changes in the surrounding environment of the exploration task through the flight state monitoring of the UAV itself and the sensor monitoring information, and provides support for the risk early warning analysis of the exploration personnel; The multi-source monitoring data fusion sub-module is used to access and fuse the real-time monitoring information of the multi-source public event risk disaster monitoring equipment already installed at the exploration hidden danger points, and provide support for the risk early warning analysis of the exploration personnel; The comprehensive analysis sub-module performs comprehensive analysis based on the monitoring data obtained by the multi-mode collaborative monitoring sub-module, the environmental mutation monitoring sub-module, and the multi-source monitoring data fusion sub-module, and outputs the corresponding risk early warning analysis results of the exploration personnel; The multi-mode collaborative monitoring sub-module calculates the position of the exploration personnel through two modes of collaboration and guides the UAV to perform follow-up monitoring. One is the feature image recognition mode. Using the pre-established characteristic portrait of the exploration personnel, the position coordinates P of the exploration personnel are obtained through a mature monocular vision method tSecondly, based on the Beidou positioning mode, the Beidou positioning function of the mobile terminal carried by the surveyors is used to obtain the real-time position coordinates P of the surveyors. b , according to the size of the confidence factor Z, calculate the real-time location coordinates of the surveyor , where the confidence factor Z = SQI / 70, where SQI ( ) is the signal quality indicator of the Beidou positioning device on the terminal equipment carried by the survey personnel. This indicator combines multiple factors such as the signal strength, signal stability, interference level, bit error rate, etc. of the Beidou positioning to measure the quality of the Beidou satellite signal received by the terminal; the guidance method of the drone following monitoring is: the first step is to calculate a circular area with the real-time position coordinates P of the survey personnel as the center and a certain distance as the radius; the second step is to calculate the terrain height based on the pre-processed geographic spatial data using the spatial calculation function of GIS, analyze the distribution of various buildings, structures, obstacles, etc., and obtain the routes within the circular area that can be used for drone flight, The third step is to extract the characteristic points of the surveyors from the images obtained by the drone camera, such as the corner points and edges of the surveyors, and compare them with the pre-established characteristic portraits of the surveyors. If the characteristic point matching rate reaches or exceeds 50%, the location is selected for follow-up monitoring. If the matching rate is lower than 50%, the position and posture of the drone in the circular area are adjusted until the matching rate reaches or exceeds 50%. If there is no area in the circular area with a matching rate of 50% or more, it means that the current surveyor's patrol route is blocked. The drone sends instructions to the terminal device carried by the surveyor, requiring the surveyor to adjust the patrol route in time. The environmental mutation monitoring submodule obtains the wind speed and direction change, temperature change, air pressure change, and precipitation change information of the current environment through the UAV's own flight status, and obtains the mutation information of the terrain, landforms and related appendages within the scope of the survey personnel's patrol route through continuous frame comparison of video images; The steps of comprehensive analysis performed by the comprehensive analysis submodule include: the first step is to use the GIS spatial computing function to match various monitoring data obtained by the multi-mode collaborative monitoring submodule, the environmental mutation monitoring submodule, and the multi-source monitoring data fusion submodule to corresponding spatial positions, and display them in the form of an electronic map; the second step is to compare the above monitoring data with the historical survey monitoring data of public event risk disaster potential points, eliminate similar areas and similar monitoring data, and retain monitoring mutation point data that have not appeared; the third step is to send the above monitoring mutation point data to the terminal equipment carried by the survey personnel in the form of early warning information, reminding the survey personnel to pay attention to protection.

[0016] In this example, the survey terminal monitoring and warning module is composed of a motion state monitoring submodule, an over-limit warning submodule, a passive response submodule, and an intervention command submodule. Figure 4as shown in the following, where: The motion state monitoring sub-module monitors the motion state of the exploration personnel during on-site inspections by using the motion sensing device of the exploration personnel's terminal device, including the motion speed and direction of the exploration personnel, and monitors the real-time position coordinates of the exploration personnel by using the Beidou positioning device; The over-limit warning sub-module gives real-time warnings and reminders for situations that exceed the pre-planned inspection route and the exploration monitoring and warning range; The passive response sub-module is used to adjust its inspection route or motion mode according to the warning information and reply in a timely manner after the exploration personnel's terminal device receives the warning information sent by the air-ground collaborative monitoring module; The intervention command sub-module is used to issue commands from the exploration personnel's terminal device to command the adjustment of the inspection route when the exploration personnel are unable to conduct inspections according to the pre-set planned route due to the complexity of the actual exploration work and many emergencies at the potential hazard points of public event risks; The steps for the intervention command sub-module to adjust the inspection route include: the first step is for the exploration personnel to re-select the inspection route on the map through the terminal device and submit it to the exploration task pre-processing module, the second step is for the exploration task pre-processing module to call the intelligent inspection route planning sub-module to optimize the new inspection route through human-computer interaction operations involved in the exploration task, and the third step is after determining the new inspection route, the exploration personnel conduct on-site inspections using the new inspection route and command the unmanned aerial vehicle to update the inspection route and conduct air-ground collaborative monitoring according to the new route.

[0017] In this example, the emergency incident auxiliary disposal module consists of an emergency incident rapid response sub-module, an unmanned aerial vehicle search and rescue sub-module, and an air-ground response sub-module, as Figure 5 shown in the following, where: The emergency incident rapid response sub-module integrates the information of the exploration personnel's terminal device and the unmanned aerial vehicle monitoring information, combines the spatial data and inspection route set by the exploration task pre-processing module, activates the emergency incident rapid response function at different levels according to the exploration personnel risk matrix analysis method, and supports the emergency incident rapid response requirements of the air-ground collaborative exploration personnel through dispatching command, air-ground information call response, and real-time summary and analysis of air-ground information through human-computer interaction; The exploration personnel risk matrix analysis method calculates the risk level of the current exploration task by using the matrix analysis method according to the different levels of monitoring of the connection status between the unmanned aerial vehicle and the exploration terminal by the air-ground collaborative monitoring module and the exploration terminal monitoring and warning module and the environmental mutation monitoring, and determines whether to activate the emergency incident rapid response function of the emergency incident rapid response sub-module according to the preset risk level threshold; The matrix analysis method is a method for semi-qualitative analysis of risks based on a two-dimensional coordinate table. The specific steps are to use the link status of the drone and the survey terminal as the monitoring accessibility index T, quantified according to a 1-5 point system as the horizontal coordinate value of the coordinate matrix, and the environmental mutation monitoring status as the potential danger index W, quantified according to a 1-5 point system as the vertical coordinate value of the coordinate matrix, and then obtain the risk level value R according to R=T×W to form a risk matrix, and then divide it into four levels of green, orange, yellow and red according to the value of R from small to large, representing no risk, low risk, medium risk and high risk status respectively; The monitoring accessibility index T can be calculated based on the link response of the drone and the survey terminal in a fixed interval polling manner such as 5 seconds, 10 seconds, etc., and according to the link response response status, for example, the index value is 1 when the response rate is 50% within 60 seconds, the index value is 2 when the response rate is 30% within 180 seconds, the index value is 4 when the response rate is 0% within 300 seconds, and the index value is 5 when the response rate is 0% within 600 seconds. Different accessibility index values ​​are calculated; The potential danger index W can calculate different index values ​​according to different states of environmental mutation monitoring. For example, for geological disaster exploration tasks, the rainfall in the climate is used as the index judgment basis, and the index value is 1 in normal weather state, the index value is 2 in light rain or 3-5 wind state, the index value is 3 in moderate rain or 5-7 wind state, the index value is 4 in heavy rain or 7-9 wind state, and the index value is 5 in torrential rain or wind state above level 9 to calculate different potential danger indicators; The four risk levels of green, orange, yellow and red can be divided according to the risk level value R. For example, R<6 means no risk, 6≦R<12 means low risk, 12≦R<18 means medium risk, and 18≦R means high risk. Assuming that the risk level threshold is set to 18, when the R value exceeds 18, the system will automatically start the emergency rapid response function of the emergency rapid response submodule; After the emergency rapid response submodule is started, the drone search and rescue submodule quickly searches and locates the on-site survey personnel in the current survey mission status according to the command of the emergency rapid response submodule, and sends drone search information to the emergency rapid response submodule in real time; The air-to-ground response submodule continuously polls and calls through wireless transmission signals such as WiFi, 5G, UHF / VHF, etc., to establish a communication link between the drone and the ground survey personnel terminal to find out the status of the emergency or eliminate and resolve the potential risk status.

[0018] The above has introduced the technical solution provided by the present invention in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can still be made to the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

Claims

1. A public event disaster investigation safety air-ground collaborative monitoring drone system, characterized by: It includes a survey task preprocessing module, an air-ground collaborative monitoring module, a survey terminal monitoring and early warning module, and an emergency auxiliary handling module, wherein: the survey task preprocessing module is used for preprocessing specific survey tasks and data; the air-ground collaborative monitoring module is used to monitor the survey process of survey personnel at public event risk disaster potential points in real time by integrating the monitoring information of UAV onboard equipment, terminal equipment carried by survey personnel, and multi-source monitoring equipment, and conduct dynamic analysis; the survey terminal monitoring and early warning module is used to provide survey personnel with real-time monitoring status reminders and early warning information, and prompt survey personnel to carry out survey work in accordance with safety plans through active response and passive response; the emergency auxiliary handling module is used to provide auxiliary support for survey personnel to escape from danger by themselves or facilitate rescue by external rescue personnel when a safety accident occurs.

2. The public event disaster investigation safety air-ground collaborative monitoring drone system according to claim 1 is characterized by: The survey task preprocessing module includes a spatial data preprocessing submodule, a survey task preprocessing submodule, a survey route intelligent planning submodule, a survey identification learning submodule, and a full-process intelligent self-checking submodule, wherein: the spatial data preprocessing submodule is based on a mature GIS commercial software integrated package, and is used for the storage, management and analysis of geographic spatial data within a certain range around a specific public event risk disaster potential point survey task; the geographic spatial data includes information such as terrain, landform, transportation, water system, and buildings, structures, obstacles, etc.; the survey task preprocessing submodule is used to preprocess the data related to the specific public event risk disaster potential point survey task, input and extract the survey time, survey route, survey point, survey personnel and other information related to the public event risk disaster potential point survey task, and store the above data; the survey route intelligent planning submodule is used to plan the inspection route and inspection range of the specific public event risk disaster potential point survey task, according to the survey The starting point and end point of the route input by the personnel are based on the spatial data processed by the spatial data preprocessing submodule, the survey task data processed by the survey task preprocessing submodule and the GIS spatial analysis function. A reasonable patrol route is planned for the survey personnel in a human-computer interactive manner and an effective survey monitoring and early warning range is set, and a follow-up flight plan is preset for the monitoring drone; the survey identification learning submodule is used to input, extract and automatically learn the features of the survey personnel and their accompanying identification elements that need to be monitored and warned, and input the basic feature information of the survey personnel such as height, weight, clothing color, and special identification worn by the survey personnel through text, voice, and taking photos. The feature portrait of the survey personnel is established by extracting the features, so that the drone can track the status of the survey personnel in real time when performing the task based on the feature portrait; the full-process intelligent self-check submodule is used to complete the preprocessing of the survey task data, and then perform a full-process simulation operation self-check according to the actual survey process to ensure that each module can work normally when the task is actually executed.

3. The public event disaster investigation safety air-ground collaborative monitoring drone system according to claim 1 is characterized by: The air-ground collaborative monitoring module includes a multi-mode collaborative monitoring submodule, an environmental mutation monitoring submodule, a multi-source monitoring data fusion submodule, and a comprehensive analysis submodule, wherein: the multi-mode collaborative monitoring submodule is based on a multi-mode collaborative monitoring mode that combines feature image recognition and Beidou positioning, and follows and monitors the real-time action trajectory of the survey personnel, provides support for the risk warning analysis of the survey personnel, and guides and controls the UAV to follow automatically; the environmental mutation monitoring submodule monitors the changes in the surrounding environment of the survey task through the UAV's own flight status monitoring and sensor monitoring information, and provides support for the risk warning analysis of the survey personnel; the multi-source monitoring data fusion submodule It is used to access and integrate the real-time monitoring information of multi-source public event risk disaster monitoring equipment that has been installed at the exploration hidden danger point, and provide support for the risk warning analysis of the exploration personnel; the comprehensive analysis submodule is based on the monitoring data obtained by the multi-mode collaborative monitoring submodule, the environmental mutation monitoring submodule, and the multi-source monitoring data fusion submodule, and performs a comprehensive analysis, and outputs the corresponding risk warning analysis results of the exploration personnel; the multi-mode collaborative monitoring submodule collaboratively calculates the location of the exploration personnel through two modes, and guides the drone to follow the monitoring. One is based on the feature image recognition mode, using the pre-established feature portrait of the exploration personnel, and obtaining the exploration personnel position coordinates P through a mature monocular vision method. t Secondly, based on the Beidou positioning mode, the Beidou positioning function of the mobile terminal carried by the surveyors is used to obtain the real-time position coordinates P of the surveyors. b , according to the size of the confidence factor Z, calculate the real-time location coordinates of the surveyor , where the confidence factor Z = SQI / 70, where SQI ( ) is the signal quality indicator of the Beidou positioning device on the terminal device carried by the surveyor. This indicator combines the signal strength, signal stability, interference degree, bit error rate and other factors of Beidou positioning to measure the quality of the Beidou satellite signal received by the terminal. The guidance method of the drone following monitoring is as follows: the first step is to calculate a circular area with the real-time position coordinate P of the surveyor as the center and a certain distance as the radius. The second step is to calculate the terrain height based on the pre-processed geographic spatial data using the spatial calculation function of GIS, analyze the distribution of various buildings, structures, obstacles, etc., and obtain the route available for drone flight in the circular area. The third step is to extract the feature points of the surveyor from the image obtained by the drone camera, such as the corner points and edges of the surveyor, and compare them with the pre-established feature portrait of the surveyor. If the feature point matching rate reaches or exceeds 50%, the position is selected for following monitoring. If the matching rate is lower than 50%, the position and posture of the drone in the circular area are adjusted until the matching rate reaches or exceeds 50%. If there is no matching rate reaching or exceeding 50 in the circular area, the drone is automatically monitored. % of the area, indicating that the current surveyor's patrol route is more obstructed, the UAV sends instructions to the terminal device carried by the surveyor, requiring the surveyor to adjust the patrol route in time; the environmental mutation monitoring submodule obtains the wind speed and wind direction changes, temperature changes, air pressure changes, and precipitation changes in the current environment through the UAV's own flight status, and obtains the mutation information of the terrain, landforms and related accessories within the surrounding area of ​​the surveyor's patrol route through continuous frame comparison of video images; the steps of comprehensive analysis by the comprehensive analysis submodule include: the first step is to use the GIS spatial calculation function to match the various monitoring data obtained by the multi-mode collaborative monitoring submodule, the environmental mutation monitoring submodule, and the multi-source monitoring data fusion submodule to the corresponding spatial position, and display them in the form of an electronic map; the second step is to compare the above monitoring data with the historical survey monitoring data of the risk disaster hidden danger points of public events, eliminate similar areas and similar monitoring data, and retain the monitoring mutation point data that have not appeared; the third step is to send the above monitoring mutation point data to the terminal device carried by the surveyor in the form of early warning information to remind the surveyor to pay attention to protection.

4. The public event disaster investigation safety air-ground collaborative monitoring drone system according to claim 1 is characterized by: The survey terminal monitoring and early warning module includes a motion status monitoring submodule, an over-limit early warning submodule, a passive response submodule, and an intervention command submodule, wherein: the motion status monitoring submodule uses the motion sensing device of the survey personnel's terminal equipment to monitor the motion status of the survey personnel during the field inspection, including the survey personnel's movement speed and direction, and uses the Beidou positioning device to monitor the survey personnel's real-time position coordinates; the over-limit early warning submodule is based on the pre-planned inspection route and the inspection monitoring and early warning range, and provides real-time early warning and reminders for situations that exceed the inspection route and the inspection monitoring and early warning range; the passive response submodule is used to adjust its own inspection route or movement mode according to the early warning information sent by the air-ground collaborative monitoring module after the survey personnel's terminal equipment receives the early warning information the intervention command submodule is used to initiate instructions from the terminal device of the surveyor to adjust the inspection route when the surveyor is unable to conduct inspections according to the pre-set planned route, aiming at the problems of complex actual inspection work and many emergencies at the risk and disaster potential points of public events. The intervention command submodule adjusts the inspection route by: the first step is for the surveyor to reselect the inspection route on the map through the terminal device and submit it to the inspection task preprocessing module; the second step is for the inspection task preprocessing module to call the inspection route intelligent planning submodule, and optimize the new inspection route through the human-computer interaction operation through the inspection task; the third step is for the surveyor to use the new inspection route for on-site inspection after determining the new inspection route, and command the drone to update the inspection route, and conduct air-ground collaborative monitoring according to the new route.

5. The public event disaster investigation safety air-ground collaborative monitoring drone system according to claim 1 is characterized by: The emergency auxiliary handling module includes an emergency rapid response submodule, an unmanned aerial vehicle search and rescue submodule, and an air-ground response submodule, wherein: the emergency rapid response submodule integrates the terminal equipment information of the survey personnel and the unmanned aerial vehicle monitoring information, combines the spatial data and the survey route set by the survey task preprocessing module, and hierarchically starts the emergency rapid response function according to the survey personnel risk matrix analysis method, and supports the air-ground collaborative survey personnel's emergency rapid response needs through human-computer interactive dispatch command, air-ground information call response, and air-ground information real-time summary and analysis; the survey personnel risk matrix analysis method is based on the air-ground collaborative monitoring module, the survey terminal monitoring and early warning module The monitoring of the link status of the unmanned aerial vehicle and the survey terminal and the different levels of environmental mutation monitoring, the matrix analysis method is used to calculate the risk level of the current survey task, and determines whether it is necessary to start the emergency rapid response function of the emergency rapid response submodule according to the preset risk level threshold; the matrix analysis method is a method for semi-qualitative analysis of risks based on a two-dimensional coordinate table. The specific steps are as follows: the link status between the UAV and the survey terminal is used as the monitoring accessibility index T, which is quantified as the horizontal coordinate value of the coordinate matrix according to a 1-5 point system; the environmental mutation monitoring status is used as the potential danger index W, which is quantified as the vertical coordinate value of the coordinate matrix according to a 1-5 point system; then the risk level value R is obtained according to R=T×W to form a risk matrix; and then it is divided into four levels of green, orange, yellow and red according to the value of R from small to large, representing no risk, low risk, medium risk and high risk status respectively; after the emergency rapid response submodule is started, the UAV search and rescue submodule, in accordance with the command of the emergency rapid response submodule, quickly searches and locates the on-site survey personnel in the current survey task status, and sends the UAV search information to the emergency rapid response submodule in real time; the air-to-ground response submodule continuously polls and calls through wireless transmission signals such as wifi, 5G, UHF / VHF, etc., to establish a communication link between the UAV and the ground survey personnel terminal to find out the emergency status or eliminate and resolve the potential risk status.

Images