A multi-network fusion-based remote rescue command and dispatch system

Abstract

This invention discloses a remote emergency rescue command and dispatch system based on multi-network convergence, including a traffic accident scene perception module, a multi-network converged communication module, an intelligent information processing module, and a remote command and dispatch module. The traffic accident scene perception module is used to capture video, vehicle speed, and location information of the monitored scene in real time and identify whether a traffic accident has occurred at the monitored scene. The multi-network converged communication module is used to integrate communication networks to ensure the real-time and stable transmission of monitoring scene information to the remote emergency rescue command and dispatch system. The communication network includes mobile communication networks, satellite communication networks, and wired networks. The intelligent information processing module is used to quickly analyze, process, and identify the received information and extract key rescue information. The remote command and dispatch module is used to dispatch and command rescue resources based on the information provided by the traffic accident scene perception module and the intelligent information processing module. This invention has the characteristics of strong practicality and high rescue efficiency.

Description

Technical Field

[0001] This invention relates to the field of communication technology, specifically to a remote emergency command and dispatch system based on multi-network convergence. Background Technology

[0002] In the critical moments of traffic accident emergency response, every minute of delay can mean the loss of a life. Traditional traffic accident handling relies on people at the scene making emergency calls, followed by dispatchers gathering information over the phone. The time consumed in this process is often a key factor delaying rescue efforts. From making the call to confirming information, and then to dispatching and arriving at the scene, delays at each stage can have irreversible consequences for the injured. Firstly, making and receiving calls takes time, especially in the chaotic and panicked atmosphere at an accident scene, affecting both accuracy and efficiency. Secondly, communication barriers can exist during the dispatcher's information gathering process, such as noise at the scene and emotionally charged individuals, leading to inaccurate and delayed information transmission. This information lag and gaps make it difficult to accurately and efficiently dispatch and allocate rescue resources, resulting in delays, wasted resources, and potentially missing the optimal rescue window, worsening the injured's condition or even endangering their lives. Therefore, designing a highly practical and efficient remote emergency command and dispatch system based on multi-network integration is essential. Summary of the Invention

[0003] The purpose of this invention is to provide a remote emergency command and dispatch system based on multi-network convergence to solve the problems mentioned in the background art.

[0004] To address the aforementioned technical problems, this invention provides the following technical solution: a remote emergency rescue command and dispatch system based on multi-network convergence, comprising a traffic accident scene perception module, a multi-network converged communication module, an intelligent information processing module, and a remote command and dispatch module. The traffic accident scene perception module is used to capture video, vehicle speed, and location information of the monitored scene in real time and identify whether a traffic accident has occurred at the monitored scene. The multi-network converged communication module is used to integrate communication networks to ensure the real-time and stable transmission of monitoring scene information to the remote emergency rescue command and dispatch system. The communication networks include mobile communication networks, satellite communication networks, and wired networks. The intelligent information processing module is used to quickly analyze, process, and identify the received information and extract key rescue information. The remote command and dispatch module is used to dispatch and command rescue resources based on the information provided by the traffic accident scene perception module and the intelligent information processing module. The traffic accident scene perception module, the intelligent information processing module, and the remote command and dispatch module are connected through the multi-network converged communication module.

[0005] According to the above technical solution, the traffic accident scene perception module includes a data acquisition module, a box selection module, an overlap tracking module, and a comprehensive judgment submodule. The data acquisition module is used to collect traffic condition-related data at the monitoring scene. The data acquisition module is electrically connected to the box selection module, which is used to select the collected vehicles. The box selection module is electrically connected to the overlap tracking module, which is used to further track and identify vehicles with overlapping connections. The comprehensive judgment submodule is used to comprehensively judge whether a traffic accident has occurred at the perception and monitoring scene.

[0006] The data acquisition module further includes a camera module, a radar speed measurement unit, and a perception information acquisition submodule. The camera module is used to acquire images of the monitoring site, the radar speed measurement unit is used to monitor the vehicle speed at the monitoring site, and the perception information acquisition submodule is used to acquire the geographical location of the monitoring site and the real-time time of the output information.

[0007] According to the above technical solution, the intelligent information processing module includes a collision injury analysis module and a traffic accident scale judgment module. The collision injury analysis module is used to analyze the severity of injuries and fatalities caused by the collision between the two parties involved in the traffic accident. The traffic accident scale judgment module is used to identify and judge the total scale of the traffic accident caused by the vehicle collision that occurred at the monitoring site.

[0008] According to the above technical solution, the remote command and dispatch module includes a data receiving module, an emergency dispatch module, and a flexible dispatch processing module. The data receiving module is used to receive data from the sensed accident scene and data processed by the intelligent information processing module. The emergency dispatch module is electrically connected to the data receiving module and is used to dispatch emergency medical resources to the sensed accident scene based on the received data. The flexible dispatch processing module is used to receive continuously transmitted information from the sensed accident scene, allowing staff to perform calibration and verification based on the continuously transmitted information and flexibly dispatch medical resources.

[0009] According to the above technical solution, the collision injury analysis module further includes an image capture submodule, a relative speed recognition submodule, and a relative magnitude recognition submodule. The image capture submodule is used to capture the image of the moment of collision between vehicles. The relative speed recognition submodule is used to identify and capture the relative speed between the two vehicles at the moment of collision. The relative magnitude recognition submodule is used to identify and capture the relative vehicle size level between the two vehicles at the moment of collision.

[0010] According to the above technical solution, the operation method of the traffic accident scene perception module includes the following steps:

[0011] Step S1: Select the monitoring site to be deployed, deploy the camera module and radar speed measurement unit, and collect the images of the monitoring site and the vehicle speed at the monitoring site respectively;

[0012] Step S2: Simultaneously, the sensing information acquisition submodule acquires the geographical location of the monitored site and the time value corresponding to the real-time collected data;

[0013] Step S3: Identify vehicles in the monitoring scene and, based on the monitoring scene perspective, select all identified vehicles along the vehicle edge outline. In conjunction with the radar speed measurement unit, measure the speed of vehicles entering the monitoring scene. The speed measurement result is marked and displayed in the upper right corner of the selected vehicle frame.

[0014] Step S4: Repeat step S3 to identify vehicles in each frame of the monitored scene in real time. When the frames of two vehicles overlap or the vehicle frames are connected at the edges, the electrical signal triggers the overlap tracking module to start and further track and identify the vehicles with overlapping frames.

[0015] Step S5: Set the tracking and identification period T. When at least one of the two selected vehicles is still in the monitoring scene after one period T from the start of the tracking and identification, proceed to step S6 to continue tracking and identification. Otherwise, when both selected vehicles leave the monitoring scene after one period T from the start of the tracking and identification, the tracking and identification ends. The comprehensive judgment submodule determines that no traffic accident has been detected.

[0016] Step S6: For the vehicles still being tracked at the monitoring site, calculate the average speed of the identified vehicles within the time period T. And the average speed of the traffic flow before the start of the monitoring. ,Compare and ,when At that time, the comprehensive judgment submodule detects that a car accident has occurred, and then transmits the sensed signal from the monitoring site to the remote rescue command and dispatch system through the multi-network converged communication module.

[0017] According to the above technical solution, the operation method of the intelligent information processing module includes the following steps:

[0018] Step A1: After receiving the accident detection signal from the accident scene perception module, the remote emergency command and dispatch system activates the intelligent information processing module via electrical signal control.

[0019] Step A2: First, retrieve the surveillance footage and capture the moment the edges of the two vehicle frames come into contact. Then, read the speed values ​​displayed in the upper right corner of the two vehicle frames where the collision was detected. and ;

[0020] Step A3: Using the captured moment when the edges of the two vehicle frames came into contact as a reference, rewind 5 frames of the monitoring scene along the timeline, mark the positions of the two vehicle frames that were detected to have collided in the monitoring scene, and connect the position change trajectories of the two vehicle frames in chronological order to draw the direction of travel of the two vehicles before the collision, and take the angle between the direction of travel of the two vehicles before the collision. ;

[0021] Step A4: Using the formula Calculate and output the relative velocity recognition result of the two vehicle bounding boxes at the instant their edges come into contact. ;

[0022] Step A5: Further capture the moment when the edges of the two vehicle frames touch, compare the proportions of the selected areas of the two vehicle frames in the image, and use a formula... Calculate and output the relative magnitude ratio between the two vehicles at the instant of the collision, where , These represent the pixel areas of the vehicle bounding boxes for the two vehicles, respectively.

[0023] Step A6: The collision injury analysis module analyzes and calculates the collision injury index R based on the relative speed and magnitude ratio of the two vehicles involved in the collision.

[0024] According to the above technical solution, in step A6, the formula for calculating the collision casualty index R is:

[0025] ;

[0026] in, For coefficients, These are preset fixed constant values, all of which are constants greater than 0, and .

[0027] According to the above technical solution, the operation method of the intelligent information processing module further includes the following steps:

[0028] Step A7: The accident scale judgment module continuously acquires the perception results of the same accident scene perception module. When the accident perception signal is received again, steps A2-A6 are repeated.

[0029] Step A8: Real-time acquisition of the number of received traffic accident detection signals (n) and all corresponding injury and fatality indices calculated. ;

[0030] Step A9: Calculate the average casualty index and using the formula Calculate and output the traffic accident scale index, where , These are preset coefficients.

[0031] According to the above technical solution, the operation method of the traffic accident scene perception module includes the following steps:

[0032] Step B1: The remote command and dispatch module extracts key rescue information, which includes all analyzed and calculated single-collision casualty indices. And the current accident scale index G;

[0033] Step B2: Establish a historical emergency dispatch and medical resource database, storing the historical maximum casualty index, the corresponding medical resource preparedness standards for historical traffic accident scales, and the scope of medical resource dispatch into the historical emergency dispatch and medical resource database;

[0034] Step B3: Select the maximum single-collision casualty index Activate the emergency dispatch module and input the maximum single-collision casualty index into the historical emergency dispatch medical resource database. The system matches the current accident scale index G with the corresponding medical resource preparation standards and medical resource dispatch range. Then, based on the location of the monitoring scene image perceived by the sensing information acquisition submodule, it remotely commands and dispatches the system to go to the scene for rescue as soon as possible.

[0035] Step B4: After the emergency dispatch is completed, the monitoring scene and its corresponding time are transmitted to the remote rescue command and dispatch system through the multi-network converged communication module. The dispatch staff read the information continuously transmitted from the accident scene, calibrate and verify the accident scene in real time, and change the emergency dispatch resources of the emergency dispatch module at any time through the flexible dispatch processing module.

[0036] Compared with existing technologies, the beneficial effects achieved by this invention are as follows: By incorporating a traffic accident scene perception module, a multi-network converged communication module, an intelligent information processing module, and a remote command and dispatch module, this invention can utilize real-time monitoring and data acquisition technologies to quickly identify the accident scene situation, intelligently analyze and assess the degree of injury and the scale of the accident, and automatically dispatch rescue resources. This not only significantly shortens the time for information acquisition and transmission but also enables precise dispatch and coordinated action of rescue resources, thereby providing effective rescue to the injured in the shortest possible time. Attached Figure Description

[0037] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0038] Figure 1 This is a schematic diagram of the system module composition of the present invention. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] Please see Figure 1 This invention provides a technical solution: a remote emergency rescue command and dispatch system based on multi-network convergence, comprising a traffic accident scene perception module, a multi-network converged communication module, an intelligent information processing module, and a remote command and dispatch module. The traffic accident scene perception module is used to capture video, vehicle speed, and location information of the monitored scene in real time and identify whether a traffic accident has occurred at the monitored scene. The multi-network converged communication module is used to integrate communication networks to ensure the real-time and stable transmission of monitoring scene information to the remote emergency rescue command and dispatch system. The communication network includes mobile communication networks, satellite communication networks, and wired networks. The intelligent information processing module is used to quickly analyze, process, and identify the received information and extract key rescue information. The remote command and dispatch module is used to dispatch and command rescue resources based on the information provided by the traffic accident scene perception module and the intelligent information processing module. The traffic accident scene perception module, the intelligent information processing module, and the remote command and dispatch module are connected through the multi-network converged communication module. By setting up the traffic accident scene perception module, the multi-network converged communication module, the intelligent information processing module, and the remote command and dispatch module, this system can utilize real-time monitoring and data acquisition technology to quickly identify the situation at the accident scene, intelligently analyze and judge the degree of injury and the scale of the accident, and automatically dispatch rescue resources. This system not only significantly reduces the time for information acquisition and transmission but also enables precise dispatch and coordinated action of rescue resources, thus providing effective rescue to the injured in the shortest possible time. Compared to the traditional method of reporting accidents by phone, the remote emergency command and dispatch system based on multi-network integration has significant advantages. This system can automatically trigger the rescue process the moment an accident occurs, without waiting for on-site personnel to make emergency calls, thereby greatly shortening the rescue response time. Simultaneously, through intelligent analysis and judgment functions, the system can more accurately assess the situation at the accident scene, providing a scientific basis for the dispatch and allocation of rescue resources, further improving rescue efficiency and success rate.

[0041] The traffic accident scene perception module includes a data acquisition module, a bounding box selection module, an overlap tracking module, and a comprehensive judgment submodule. The data acquisition module is used to collect traffic condition data related to the monitored scene. The data acquisition module is electrically connected to the bounding box selection module, which is used to select the collected vehicles. The bounding box selection module is also electrically connected to the overlap tracking module, which is used to further track and identify vehicles with overlapping bounding boxes. The comprehensive judgment submodule is used to comprehensively judge whether a traffic accident has occurred at the monitored scene.

[0042] The data acquisition module further includes a camera module, a radar speed measurement unit, and a perception information acquisition submodule. The camera module is used to acquire images of the monitoring site, the radar speed measurement unit is used to monitor the vehicle speed at the monitoring site, and the perception information acquisition submodule is used to acquire the geographical location of the monitoring site and the real-time time of the output information.

[0043] The intelligent information processing module includes a collision injury analysis module and a traffic accident scale judgment module. The collision injury analysis module is used to analyze the severity of injuries and fatalities caused by the collision between the two parties involved in the traffic accident, while the traffic accident scale judgment module is used to identify and judge the total scale of the traffic accident caused by the vehicle collision that occurred at the monitoring site.

[0044] The remote command and dispatch module includes a data receiving module, an emergency dispatch module, and a flexible dispatch processing module. The data receiving module receives data from the sensed accident scene and the processed data from the intelligent information processing module. The emergency dispatch module is electrically connected to the data receiving module and is used to dispatch emergency medical resources to the sensed accident scene based on the received data. The flexible dispatch processing module receives continuously transmitted information from the sensed accident scene, allowing staff to perform calibration and verification based on the continuously transmitted information and flexibly dispatch medical resources.

[0045] The collision injury analysis module further includes an image capture submodule, a relative speed recognition submodule, and a relative magnitude recognition submodule. The image capture submodule is used to capture the moment of contact between vehicles during a collision. The relative speed recognition submodule is used to identify and capture the relative speed between the two vehicles at the moment of the collision. The relative magnitude recognition submodule is used to identify and capture the relative vehicle size level between the two vehicles at the moment of the collision.

[0046] The operation method of the traffic accident scene perception module includes the following steps:

[0047] Step S1: Select the monitoring site to be deployed, deploy camera modules and radar speed measurement units to collect images of the monitoring site and the speed of vehicles traveling at the monitoring site, respectively. Generally, the deployment is carried out at traffic intersections in the core of the city, accident-prone road sections, and some urban traffic arteries. This allows command and dispatch personnel to quickly identify the accident scene situation when facing accident-prone road sections or road sections where traffic accidents have a significant impact. The deployed accident scene perception module can intelligently analyze and judge the degree of injury and the scale of the accident, and automatically dispatch rescue resources. This greatly shortens the time for information acquisition and transmission, and also realizes the precise dispatch and coordinated action of rescue resources, thereby providing effective rescue to the injured in the shortest possible time and avoiding significant impact on traffic.

[0048] Step S2: Simultaneously, the sensing information acquisition submodule acquires the geographical location of the monitored site and the time value corresponding to the real-time collected data;

[0049] Step S3: Identify vehicles in the monitoring scene and, based on the monitoring scene perspective, select all identified vehicles along the vehicle edge outline. In conjunction with the radar speed measurement unit, measure the speed of vehicles entering the monitoring scene. The speed measurement result is marked and displayed in the upper right corner of the selected vehicle frame.

[0050] Step S4: Repeat step S3 to identify vehicles in each frame of the monitored scene in real time. When the frames of two vehicles overlap or the vehicle frames are connected at the edges, the electrical signal triggers the overlap tracking module to start and further track and identify the vehicles with overlapping frames.

[0051] Step S5: Set the tracking and identification period T. When at least one of the two selected vehicles is still in the monitoring scene after one period T from the start of the tracking and identification, proceed to step S6 to continue tracking and identification. Otherwise, when both selected vehicles leave the monitoring scene after one period T from the start of the tracking and identification, the tracking and identification ends. The comprehensive judgment submodule determines that no traffic accident has been detected.

[0052] Step S6: For the vehicles still being tracked at the monitoring site, calculate the average speed of the identified vehicles within the time period T. And the average speed of the traffic flow before the start of the monitoring. ,Compare and ,when When a collision occurs, the comprehensive judgment submodule detects that a car accident has occurred and then transmits the perceived signal from the monitoring site to the remote emergency command and dispatch system via the multi-network converged communication module. In the event of a vehicle-to-vehicle collision, even if one party flees the scene, at least one of the vehicles involved must remain at the accident scene. Therefore, the system first analyzes whether at least one of the overlapping connected vehicles has not left the monitoring site within the period T. If this condition is not met (i.e., all vehicles have left the monitoring site), it is judged as a false identification or merely a minor collision, not constituting a car accident, and therefore no further in-depth analysis or remote emergency command and dispatch is required. If at least one vehicle involved is present at the monitoring site within the period T, the system further tracks and compares the involved vehicle with the entire monitoring site before the start time. If the speed of the vehicle in question is significantly lower than the speed of the previous overall traffic flow, it is identified as a possible accident. Conversely, if the speed of the vehicle in question is higher than the speed of the previous overall traffic flow, it may be due to a traffic jam caused by the slow speed of the overall traffic flow. If a traffic jam existed before the start of the incident, even if the two vehicles collided, the lack of sufficient space for acceleration due to the traffic jam would make it difficult to constitute a serious accident requiring emergency medical resources. Therefore, it is not considered an accident. Through the above steps, a hierarchical analysis can be performed to determine whether an accident has occurred at the monitoring site, effectively avoiding false alarms and missed alarms, improving the stability and reliability of the system, and enabling rapid perception and accurate judgment of the accident scene, providing a valuable time window for rescue operations.

[0053] The operation method of the intelligent information processing module includes the following steps:

[0054] Step A1: After receiving the accident detection signal from the accident scene perception module, the remote emergency command and dispatch system activates the intelligent information processing module via electrical signal control.

[0055] Step A2: First, retrieve the surveillance footage and capture the moment the edges of the two vehicle frames come into contact. Then, read the speed values ​​displayed in the upper right corner of the two vehicle frames where the collision was detected. and ;

[0056] Step A3: Using the captured moment when the edges of the two vehicle frames came into contact as a reference, rewind 5 frames of the monitoring scene along the timeline, mark the positions of the two vehicle frames that were detected to have collided in the monitoring scene, and connect the position change trajectories of the two vehicle frames in chronological order to draw the direction of travel of the two vehicles before the collision, and take the angle between the direction of travel of the two vehicles before the collision. ;

[0057] Step A4: Using the formula Calculate and output the relative velocity recognition result of the two vehicle bounding boxes at the instant their edges come into contact. When a car accident occurs due to a collision between two vehicles, the relative speeds will differ because the vehicles are traveling in different directions at the time of the collision. For example, if the two vehicles are traveling in opposite directions and collide, the relative speed is the sum of the speeds of both vehicles. If the collision occurs in the same direction, i.e., a rear-end collision, the relative speed is the speed of the rear vehicle minus the speed of the front vehicle. When the collision occurs at an intersection where the two vehicles are traveling at a 90° angle, the relative speed is equal to the speed of the faster vehicle. Therefore, by fully considering the travel directions of the two vehicles at the time of the collision, the formula can effectively calculate the different relative speeds due to the angle between the two travel directions, thus addressing the complex and ever-changing car accident situations at the monitoring site.

[0058] Step A5: Further capture the moment when the edges of the two vehicle frames touch, compare the proportions of the selected areas of the two vehicle frames in the image, and use a formula... Calculate and output the relative magnitude ratio between the two vehicles at the instant of the collision, where , These represent the pixel areas of the vehicle bounding boxes for the two vehicles, respectively.

[0059] Step A6: The collision injury analysis module analyzes and calculates the collision injury index R based on the relative speed and magnitude ratio of the two vehicles involved in the collision.

[0060] In step A6, the formula for calculating the collision injury index R is:

[0061] ;

[0062] in, For coefficients, These are preset fixed constant values, all of which are constants greater than 0, and ;

[0063] As can be seen from the above formula, the collision casualty index R is related to the relative magnitude ratio p and the relative speed. Relatedly, the smaller the relative magnitude ratio p, the larger the collision injury index R. This is because a smaller relative magnitude ratio p indicates a greater difference in the vehicle classes involved in the collision. For example, a collision between a truck and a motorcycle is more likely to cause severe injuries or fatalities at the same speed compared to a collision between two cars due to the greater difference in vehicle classes. When the relative speed... The larger the value, the greater the casualty index R. As speed increases, the casualty index shows an exponential growth relationship relative to the relative speed.

[0064] The operation method of the intelligent information processing module also includes the following steps:

[0065] Step A7: The accident scale judgment module continuously acquires the perception results of the same accident scene perception module. When the accident perception signal is received again, steps A2-A6 are repeated.

[0066] Step A8: Real-time acquisition of the number of received traffic accident detection signals (n) and all corresponding injury and fatality indices calculated. ;

[0067] Step A9: Calculate the average casualty index and using the formula Calculate and output the traffic accident scale index, where , The coefficients are preset; through continuous perception and repeated analysis, all casualties at the scene of a traffic accident can be captured more comprehensively, thereby more accurately assessing the scale of the accident.

[0068] The operation method of the traffic accident scene perception module includes the following steps:

[0069] Step B1: The remote command and dispatch module extracts key rescue information, which includes all analyzed and calculated single-collision casualty indices. And the current accident scale index G;

[0070] Step B2: Establish a historical emergency dispatch and medical resource database, storing the historical maximum casualty index, the corresponding medical resource preparedness standards for historical traffic accident scales, and the scope of medical resource dispatch into the historical emergency dispatch and medical resource database;

[0071] Step B3: Select the maximum single-collision casualty index Activate the emergency dispatch module and input the maximum single-collision casualty index into the historical emergency dispatch medical resource database. The system matches the current accident scale index G with the corresponding medical resource preparation standards and medical resource dispatch range. Then, based on the location of the monitoring scene image perceived by the sensing information acquisition submodule, it remotely commands and dispatches the system to go to the scene for rescue as soon as possible.

[0072] Step B4: After the emergency dispatch is completed, the monitoring scene and its corresponding time are transmitted to the remote rescue command and dispatch system through the multi-network converged communication module. The dispatch staff read the information continuously transmitted from the accident scene, calibrate and verify the accident scene in real time, and change the emergency dispatch resources of the emergency dispatch module at any time through the flexible dispatch processing module.

[0073] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0074] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A remote emergency medical command and dispatch system based on multi-network convergence, characterized in that: The remote emergency command and dispatch system includes a vehicle accident scene perception module, a multi-network converged communication module, an intelligent information processing module, and a remote command and dispatch module. The vehicle accident scene perception module is used to capture video, vehicle speed, and location information of the monitoring scene in real time and identify whether a vehicle accident has occurred at the monitoring scene. The multi-network converged communication module is used to integrate the communication network to ensure the real-time and stable transmission of monitoring scene information to the remote emergency command and dispatch system. The communication network includes mobile communication network, satellite communication network, and wired network. The intelligent information processing module is used to quickly analyze, process, and identify the received information and extract key rescue information. The remote command and dispatch module is used to dispatch and command rescue resources based on the information provided by the vehicle accident scene perception module and the intelligent information processing module. The vehicle accident scene perception module, the intelligent information processing module, and the remote command and dispatch module are connected through the multi-network converged communication module. The operation method of the traffic accident scene perception module includes the following steps: Step S1: Select the monitoring site to be deployed, deploy the camera module and radar speed measurement unit, and collect the images of the monitoring site and the vehicle speed at the monitoring site respectively; Step S2: Simultaneously, the sensing information acquisition submodule acquires the geographical location of the monitored site and the time value corresponding to the real-time collected data; Step S3: Identify vehicles in the monitoring scene and, based on the monitoring scene perspective, select all identified vehicles along the vehicle edge outline. In conjunction with the radar speed measurement unit, measure the speed of vehicles entering the monitoring scene. The speed measurement result is marked and displayed in the upper right corner of the selected vehicle frame. Step S4: Repeat step S3 to identify vehicles in each frame of the monitored scene in real time. When the frames of two vehicles overlap or the vehicle frames are connected at the edges, the electrical signal triggers the overlap tracking module to start and further track and identify the vehicles with overlapping frames. Step S5: Set the tracking and identification period T. When at least one of the two selected vehicles is still in the monitoring scene after one period T from the start of the tracking and identification, proceed to step S6 to continue tracking and identification. Otherwise, when both selected vehicles leave the monitoring scene after one period T from the start of the tracking and identification, the tracking and identification ends. The comprehensive judgment submodule determines that no traffic accident has been detected. Step S6: For the vehicles still being tracked at the monitoring site, calculate the average speed of the identified vehicles within the time period T. And the average speed of the traffic flow before the start of the monitoring. ,Compare and ,when At that time, the comprehensive judgment submodule detects that a car accident has occurred, and then transmits the sensed signal from the monitoring site to the remote rescue command and dispatch system through the multi-network converged communication module.

2. The remote emergency medical command and dispatch system based on multi-network convergence according to claim 1, characterized in that: The traffic accident scene perception module includes a data acquisition module, a frame selection module, an overlap tracking module, and a comprehensive judgment submodule. The data acquisition module is used to collect traffic condition-related data at the monitoring scene. The data acquisition module is electrically connected to the frame selection module, which is used to select the collected vehicles. The frame selection module is also electrically connected to the overlap tracking module, which is used to further track and identify vehicles with overlapping frames. The comprehensive judgment submodule is used to comprehensively judge whether a traffic accident has occurred at the perception and monitoring scene. The data acquisition module further includes a camera module, a radar speed measurement unit, and a perception information acquisition submodule. The camera module is used to acquire images of the monitoring site, the radar speed measurement unit is used to monitor the vehicle speed at the monitoring site, and the perception information acquisition submodule is used to acquire the geographical location of the monitoring site and the real-time time of the output information.

3. The remote emergency medical command and dispatch system based on multi-network convergence according to claim 1, characterized in that: The intelligent information processing module includes a collision injury analysis module and a traffic accident scale judgment module. The collision injury analysis module is used to analyze the severity of injuries and fatalities caused by the collision between the two parties involved in the traffic accident. The traffic accident scale judgment module is used to identify and judge the total scale of the traffic accident caused by the vehicle collision that occurred at the monitoring site.

4. The remote emergency medical command and dispatch system based on multi-network convergence according to claim 1, characterized in that: The remote command and dispatch module includes a data receiving module, an emergency dispatch module, and a flexible dispatch processing module. The data receiving module receives data from the sensed accident scene and data processed by the intelligent information processing module. The emergency dispatch module is electrically connected to the data receiving module and is used to dispatch emergency medical resources to the sensed accident scene based on the received data. The flexible dispatch processing module receives continuously transmitted information from the sensed accident scene, allowing staff to perform calibration and verification based on the continuously transmitted information and flexibly dispatch medical resources.

5. A remote emergency medical command and dispatch system based on multi-network convergence according to claim 3, characterized in that: The collision injury analysis module further includes an image capture submodule, a relative speed recognition submodule, and a relative magnitude recognition submodule. The image capture submodule is used to capture the image of the moment of collision between vehicles. The relative speed recognition submodule is used to identify and capture the relative speed between the two vehicles at the moment of collision. The relative magnitude recognition submodule is used to identify and capture the relative vehicle size level between the two vehicles at the moment of collision.

6. A remote emergency medical command and dispatch system based on multi-network convergence according to claim 3, characterized in that: The operation method of the intelligent information processing module includes the following steps: Step A1: After receiving the accident detection signal from the accident scene perception module, the remote emergency command and dispatch system activates the intelligent information processing module via electrical signal control. Step A2: First, retrieve the surveillance footage and capture the moment the edges of the two vehicle frames come into contact. Then, read the speed values ​​displayed in the upper right corner of the two vehicle frames where the collision was detected. and ; Step A3: Using the captured moment when the edges of the two vehicle frames came into contact as a reference, rewind 5 frames of the monitoring scene along the timeline, mark the positions of the two vehicle frames that were detected to have collided in the monitoring scene, and connect the position change trajectories of the two vehicle frames in chronological order to draw the direction of travel of the two vehicles before the collision, and take the angle between the direction of travel of the two vehicles before the collision. ; Step A4: Using the formula Calculate and output the relative velocity recognition result of the two vehicle bounding boxes at the instant their edges come into contact. ; Step A5: Further capture the moment when the edges of the two vehicle frames touch, compare the proportions of the selected areas of the two vehicle frames in the image, and use a formula... Calculate and output the relative magnitude ratio between the two vehicles at the instant of the collision, where , These represent the pixel areas of the vehicle bounding boxes for the two vehicles, respectively. Step A6: The collision injury analysis module analyzes and calculates the collision injury index R based on the relative speed and magnitude ratio of the two vehicles involved in the collision.

7. A remote emergency medical command and dispatch system based on multi-network convergence according to claim 6, characterized in that: In step A6, the formula for calculating the collision casualty index R is: ； in, For coefficients, These are preset fixed constant values, all of which are constants greater than 0, and .

8. A remote emergency medical command and dispatch system based on multi-network convergence according to claim 6, characterized in that: The operation method of the intelligent information processing module further includes the following steps: Step A7: The accident scale judgment module continuously acquires the perception results of the same accident scene perception module. When the accident perception signal is received again, steps A2-A6 are repeated. Step A8: Real-time acquisition of the number of received traffic accident detection signals (n) and all corresponding injury and fatality indices calculated. ; Step A9: Calculate the average casualty index and using the formula Calculate and output the traffic accident scale index, where , These are preset coefficients.

9. A remote emergency medical command and dispatch system based on multi-network convergence according to claim 4, characterized in that: The operation method of the traffic accident scene perception module includes the following steps: Step B1: The remote command and dispatch module extracts key rescue information, which includes all analyzed and calculated single-collision casualty indices. And the current accident scale index G; Step B2: Establish a historical emergency dispatch and medical resource database, storing the historical maximum casualty index, the corresponding medical resource preparedness standards for historical traffic accident scales, and the scope of medical resource dispatch into the historical emergency dispatch and medical resource database; Step B3: Select the maximum single-collision casualty index Activate the emergency dispatch module and input the maximum single-collision casualty index into the historical emergency dispatch medical resource database. The system matches the current accident scale index G with the corresponding medical resource preparation standards and medical resource dispatch range. Then, based on the location of the monitoring scene image perceived by the sensing information acquisition submodule, it remotely commands and dispatches the system to go to the scene for rescue as soon as possible. Step B4: After the emergency dispatch is completed, the monitoring scene and its corresponding time are transmitted to the remote rescue command and dispatch system through the multi-network converged communication module. The dispatch staff read the information continuously transmitted from the accident scene, calibrate and verify the accident scene in real time, and change the emergency dispatch resources of the emergency dispatch module at any time through the flexible dispatch processing module.

Images