Remote emergency collaborative decision-making platform based on AI drive and implementation method thereof

Abstract

The invention provides a remote first-aid collaborative decision-making platform based on AI driving and an implementation method of the remote first-aid collaborative decision-making platform. The AI-driven remote first-aid collaborative decision-making platform comprises a position acquisition module which is used for a remote first-aid collaborative cloud platform to determine the position of a current first-aid event; the hospital screening module is used for determining a target first-aid hospital according to the first-aid safety coefficient between the first-aid event position and the candidate hospitals and dispatching the target first-aid hospital to dispatch an ambulance to the first-aid event position; and the data sharing module is used for sharing the first-aid data to the hospital terminal of the target first-aid hospital in real time through the remote first-aid collaborative cloud platform. The method comprises the steps corresponding to the system module. According to the invention, the first-aid efficiency is improved, the resource configuration is optimized, and the cooperative capability is enhanced.

Description

Technical Field

[0001] The present invention provides an AI-driven remote first aid collaborative decision-making platform and an implementation method thereof, relating to the technical field of collaborative decision-making, and particularly to the technical field of AI-driven remote first aid collaborative decision-making. Background Art

[0002] Traditional remote first aid is usually based on fixed paths or rules. However, the actual traffic conditions are complex and changeable, and remote first aid is often affected by factors such as complex road traffic conditions, resulting in delays and missed first aid opportunities. In the traditional first aid process, there are also often problems such as unequal first aid information, low communication efficiency, and difficulty in intelligently selecting the optimal hospital and the optimal first aid collaborative decision, leading to low remote first aid efficiency and untimely response. Summary of the Invention

[0003] The present invention provides an AI-driven remote first aid collaborative decision-making platform and an implementation method thereof to solve the above problems:

[0004] An AI-driven remote first aid collaborative decision-making platform, the AI-driven remote first aid collaborative decision-making platform includes:

[0005] A location acquisition module, configured to determine the current first aid event location for the remote first aid collaborative cloud platform;

[0006] A hospital screening module, configured to determine a target first aid hospital according to the first aid safety factor between the first aid event location and candidate hospitals, and dispatch an ambulance from the target first aid hospital to the first aid event location;

[0007] A data sharing module, configured to share first aid data to the hospital terminal of the target first aid hospital in real time through the remote first aid collaborative cloud platform.

[0008] Further, the location acquisition module includes:

[0009] A request sending module, configured to monitor in real time whether the remote first aid collaborative cloud platform receives a first aid request sent by a first aid terminal;

[0010] A location positioning and acquisition module, configured to, when receiving the first aid request, locate the current first aid location through the first aid terminal to obtain the current first aid event location.

[0011] Further, the hospital screening module includes:

[0012] A map retrieval module, configured to retrieve a high-precision map and mark the current first aid location on the high-precision map;

[0013] A candidate hospital acquisition module, configured to obtain hospitals that meet the preset initial path distance requirement from the high-precision map as candidate hospitals;

[0014] A target emergency hospital screening module, which is used to screen out a target emergency hospital from the candidate hospitals according to the number of paths of the candidate hospitals, the traffic flow status of each path, and the communication network coverage intensity of each path.

[0015] An information feedback module, which is used for the remote emergency collaboration cloud platform to send the current emergency location to the target emergency hospital, and feed back the real-time positioning information of the ambulance to the emergency terminal after the target emergency hospital dispatches the ambulance.

[0016] Further, the target emergency hospital screening module includes:

[0017] A path number extraction module, which is used to extract the number of the radiation ranges of the communication base stations where each path corresponding to each candidate hospital is located.

[0018] A signal strength determination module, which is used to determine the signal strength radiated by the base station corresponding to the position of each path in the radiation range of each communication base station.

[0019] A communication signal strength coefficient acquisition module, which is used to obtain the communication signal strength coefficient corresponding to each path according to the signal strength radiated by the base station corresponding to the position of each path in the radiation range of each communication base station.

[0020] A traffic flow coefficient acquisition module, which is used to extract the traffic flow status corresponding to each path, and obtain the traffic flow coefficient corresponding to each path according to the traffic flow status corresponding to each path.

[0021] An emergency safety coefficient acquisition module, which is used to obtain the emergency safety coefficient corresponding to each path by using the traffic flow coefficient and the communication signal strength coefficient corresponding to each path.

[0022] A path number extraction module, which is used to extract the number of paths in each candidate hospital whose emergency safety coefficient exceeds a preset safety coefficient threshold.

[0023] A screening execution module, which is used to use the candidate hospital with the largest number of paths whose emergency safety coefficient exceeds the preset safety coefficient threshold as the target emergency hospital, or, when there is no path in all candidate hospitals whose emergency safety coefficient exceeds the preset safety coefficient threshold, select the candidate hospital with the largest emergency safety coefficient corresponding to the path as the target emergency hospital.

[0024] Further, the data sharing module includes:

[0025] A data acquisition module, which is used to collect real-time audio and video data and vital sign data of the emergency scene through real-time cameras, microphones and wearable devices when the ambulance dispatched by the target emergency hospital arrives at the emergency event location.

[0026] A data upload module for uploading the audio - video data and vital sign data to a remote first - aid collaborative cloud platform;

[0027] A data sharing execution module for sharing the audio - video data and vital sign data to the hospital terminal of the target first - aid hospital through the remote first - aid collaborative cloud platform.

[0028] A method for implementing an AI - driven remote first - aid collaborative decision - making platform, the method for implementing the AI - driven remote first - aid collaborative decision - making platform includes:

[0029] The remote first - aid collaborative cloud platform determines the location of the current first - aid event;

[0030] Determine the target first - aid hospital according to the first - aid safety factor between the location of the first - aid event and the candidate hospitals, and dispatch the target first - aid hospital to send an ambulance to the location of the first - aid event;

[0031] Share the first - aid data to the hospital terminal of the target first - aid hospital in real - time through the remote first - aid collaborative cloud platform.

[0032] Further, determining the location of the current first - aid event includes:

[0033] The remote first - aid collaborative cloud platform monitors in real - time whether it receives a first - aid request sent by the first - aid terminal;

[0034] When receiving the first - aid request, locate the current first - aid location through the first - aid terminal to obtain the location of the current first - aid event.

[0035] Further, determining the target first - aid hospital according to the location of the first - aid event and dispatching the target first - aid hospital to send an ambulance to the location of the first - aid event includes:

[0036] Retrieve a high - precision map and mark the current first - aid location on the high - precision map;

[0037] Obtain the hospitals that meet the preset initial path distance requirement from the high - precision map as candidate hospitals;

[0038] Screen out the target first - aid hospital from the candidate hospitals according to the number of paths of the candidate hospitals and the traffic flow status of each path combined with the communication network coverage intensity of each path;

[0039] The remote first - aid collaborative cloud platform sends the current first - aid location to the target first - aid hospital and feeds back the real - time positioning information of the ambulance to the first - aid terminal after the target first - aid hospital dispatches the ambulance.

[0040] Further, screening out the target first - aid hospital includes:

[0041] Extract the number of communication base station radiation ranges where each path corresponding to each candidate hospital is located;

[0042] Determine the signal strength of the base station radiation corresponding to the position of each path in the radiation range of each communication base station;

[0043] Obtain the communication signal strength coefficient corresponding to each path according to the signal strength of the base station radiation corresponding to the position of each path in the radiation range of each communication base station;

[0044] Extract the traffic flow status corresponding to each path, and obtain the traffic flow coefficient corresponding to each path according to the traffic flow status corresponding to each path;

[0045] Obtain the first aid safety coefficient corresponding to each path by using the traffic flow coefficient and the communication signal strength coefficient corresponding to each path;

[0046] Extract the number of paths in each candidate hospital whose first aid safety coefficient exceeds the preset safety coefficient threshold;

[0047] Take the candidate hospital with the largest number of paths whose first aid safety coefficient exceeds the preset safety coefficient threshold as the target first aid hospital, or, when none of the candidate hospitals have paths whose first aid safety coefficient exceeds the preset safety coefficient threshold, select the candidate hospital with the largest first aid safety coefficient corresponding to the path as the target first aid hospital.

[0048] Furthermore, the first aid data is shared in real time to the hospital terminal of the target first aid hospital through the remote first aid collaboration cloud platform, including:

[0049] When the ambulance dispatched by the target first aid hospital arrives at the first aid event location, collect the audio and video data and vital sign data of the first aid scene in real time through real-time cameras, microphones and wearable devices;

[0050] Upload the audio and video data and vital sign data to the remote first aid collaboration cloud platform;

[0051] Share the audio and video data and vital sign data to the hospital terminal of the target first aid hospital through the remote first aid collaboration cloud platform.

[0052] Advantages of the present invention: By obtaining the geographical location of the first aid event, the occurrence location of the first aid event is determined, the efficiency of the first aid response is improved, the delay caused by unclear location is reduced, and the timeliness of the first aid response is enhanced; by obtaining the first aid safety factor, a safer first aid strategy is obtained. Through the combined analysis of the first aid event location and the first aid safety factor, the most optimal choice among multiple first aid hospitals can be obtained, and the ambulance can be dispatched in a timely manner. While improving the first aid safety, the first aid efficiency is enhanced, and the optimal hospital dispatching strategy is obtained to ensure that the ambulance can reach the first aid scene safely and in a timely manner. The above first aid strategy not only optimizes the first aid efficiency, but also optimizes the allocation of medical resources and reduces the first aid delay caused by improper hospital selection. Through the cloud platform, the real-time sharing of first aid data is realized, ensuring that the target first aid hospital can obtain the relevant information of the first aid event in a timely manner and ensuring the consistency of the information, avoiding the first aid delay caused by information asymmetry or transmission delay. Through multi-party collaborative work, it is ensured that each link in the first aid process can obtain the latest information in real time, improving the overall collaborative efficiency of the first aid. Brief Description of the Drawings

[0053] Figure 1 It is a schematic diagram of a remote first aid collaborative decision-making platform driven by AI;

[0054] Figure 2 It is a schematic diagram of the implementation method of the remote first aid collaborative decision-making platform driven by AI. Detailed Embodiments

[0055] The following describes the preferred embodiments of the present invention with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and are not used to limit the present invention.

[0056] An embodiment of the present invention is a remote first aid collaborative decision-making platform driven by AI. The remote first aid collaborative decision-making platform driven by AI includes:

[0057] A location acquisition module for determining the current first aid event location by the remote first aid collaborative cloud platform;

[0058] A hospital screening module for determining the target first aid hospital according to the first aid safety factor between the first aid event location and the candidate hospitals, and dispatching the target first aid hospital to dispatch an ambulance to the first aid event location;

[0059] A data sharing module for real-time sharing of first aid data to the hospital terminal of the target first aid hospital through the remote first aid collaborative cloud platform, as Figure 1 shown.

[0060] The working principle of the above technical solution is: The remote first aid collaborative decision-making platform driven by AI includes:

[0061] A location acquisition module, which is used for the remote first-aid collaboration cloud platform to determine the location of the current first-aid event; accurately acquire the location of the current first-aid event through the location acquisition module, and use it for decision-making analysis based on the event location.

[0062] A hospital screening module, which is used to determine the target first-aid hospital according to the first-aid safety factor between the first-aid event location and the candidate hospitals, and dispatch the target first-aid hospital to send an ambulance to the first-aid event location; analyze the first-aid safety factors between hospitals through the medical screening module, and then obtain the dispatch strategy through the event location and the first-aid safety factor.

[0063] A data sharing module, which is used to share the first-aid data to the hospital terminal of the target first-aid hospital in real time through the remote first-aid collaboration cloud platform. Share the first-aid data between various platforms through the data sharing module to ensure the consistency and interoperability of the data, and prevent delays caused by information asymmetry.

[0064] The effects of the above technical solutions are as follows: The present invention determines the occurrence location of the first-aid event by obtaining the geographical location of the first-aid event, improves the efficiency of the first-aid response, reduces the delay caused by unclear location, and enhances the timeliness of the first-aid response; obtains a safer first-aid strategy by obtaining the first-aid safety factor, and through the combined analysis of the first-aid event location and the first-aid safety factor, the optimal choice among multiple first-aid hospitals can be obtained, and an ambulance can be dispatched in time. While improving the safety of the first-aid, it enhances the first-aid efficiency, obtains the optimal hospital dispatch strategy, and ensures that the ambulance can reach the first-aid scene safely and in time. The above first-aid strategy not only optimizes the first-aid efficiency, but also optimizes the allocation of medical resources, and reduces the first-aid delay caused by improper hospital selection. Real-time sharing of first-aid data is achieved through the cloud platform to ensure that the target first-aid hospital can obtain relevant information about the first-aid event in time, and the consistency of the information is guaranteed, avoiding first-aid delays caused by information asymmetry or transmission delays. Through multi-party collaborative work, it is ensured that all links in the first-aid process can obtain the latest information in real time, improving the overall collaborative efficiency of the first-aid.

[0065] In an embodiment of the present invention, the location acquisition module includes:

[0066] A request sending module, which is used for the remote first-aid collaboration cloud platform to monitor in real time whether it receives a first-aid request sent by the first-aid terminal;

[0067] A location positioning and acquisition module, which is used to locate the current first-aid location through the first-aid terminal when receiving the first-aid request, and obtain the location of the current first-aid event.

[0068] The working principle of the above technical solution is as follows: The remote first-aid collaborative cloud platform monitors in real time whether it receives a first-aid request sent by a first-aid terminal, where the first-aid terminal includes, but is not limited to, an ambulance, a vehicle automatic first-aid alarm terminal, a mobile phone APP terminal, etc.; through the request sending module, the first-aid requests sent by each first-aid terminal are obtained, so that the cloud platform can obtain the first-aid request information in the first time;

[0069] When a first-aid request is received, the current first-aid location is located through the first-aid terminal to obtain the current first-aid event location. Through the location positioning acquisition module, while receiving the first-aid request information, the first-aid event location of the first-aid request information is obtained, ensuring the binding of the request information and the time location.

[0070] The effect of the above technical solution is as follows: The remote first-aid collaborative cloud platform monitors in real time whether it receives a first-aid request sent by a first-aid terminal, where the first-aid terminal includes, but is not limited to, an ambulance, a vehicle automatic first-aid alarm terminal, a mobile phone APP terminal, etc.; through the request sending module, the first-aid requests sent by each first-aid terminal are obtained, so that the cloud platform can obtain the first-aid request information in the first time; by obtaining the first-aid request information through the cloud platform, it is ensured that each terminal can obtain the first-aid information in the first time, improving the real-time nature of the first-aid response and the information intercommunication.

[0071] When a first-aid request is received, the current first-aid location is located through the first-aid terminal to obtain the current first-aid event location. Through the location positioning acquisition module, while receiving the first-aid request information, the first-aid event location of the first-aid request information is obtained, ensuring the binding of the request information and the event location. By obtaining the first-aid event location while obtaining the first-aid request information, it is convenient to obtain the binding information of the request and the event location, reducing the possibility of data analysis errors and thus decision-making errors caused by excessive event and request information.

[0072] In an embodiment of the present invention, the hospital screening module includes:

[0073] A map retrieval module, configured to retrieve a high-precision map and mark the current first-aid location on the high-precision map;

[0074] A candidate hospital acquisition module, configured to obtain hospitals that meet the preset initial path distance requirement from the high-precision map as candidate hospitals;

[0075] A target first-aid hospital screening module, configured to screen out a target first-aid hospital from the candidate hospitals according to the number of paths of the candidate hospitals and the traffic flow status of each path in combination with the communication network coverage intensity of each path;

[0076] An information feedback module is used for the remote first aid collaboration cloud platform to send the current first aid location to the target first aid hospital, and to feedback the real-time location information of the ambulance to the first aid terminal after the target first aid hospital dispatches the ambulance.

[0077] The working principle of the above technical solution is as follows: A map retrieval module is used to retrieve a high-precision map and mark the current first aid location on the high-precision map, where the high-precision map includes but is not limited to various existing map systems; by marking the current first aid location in the high-precision map, the visualization of the current first aid location is realized, and high-precision location information can be obtained.

[0078] A candidate hospital acquisition module is used to obtain hospitals that meet the preset initial path distance requirement from the high-precision map as candidate hospitals; where the meeting the preset initial path distance requirement means that any one of the one or more paths between the hospital location planned on the high-precision map and the current first aid location is lower than the preset path distance threshold; first, a qualified path distance is obtained as the initial path distance for comparison with other paths.

[0079] A target first aid hospital screening module is used to screen out the target first aid hospital from the candidate hospitals according to the number of paths of the candidate hospitals, the traffic flow status of each path, and the communication network coverage intensity of each path; obtain a first aid hospital that meets the requirements of the number of paths, traffic flow status, and communication network coverage intensity, so that the first aid hospital meets the basic requirements of first aid.

[0080] An information feedback module is used for the remote first aid collaboration cloud platform to send the current first aid location to the target first aid hospital, and to feedback the real-time location information of the ambulance to the first aid terminal after the target first aid hospital dispatches the ambulance. The first aid location is sent through the cloud platform, and the feedback information of the target first aid hospital is obtained to integrate and analyze the first aid dispatching information.

[0081] The effect of the above technical solution is as follows: Through the high-precision map, real-time location, path data, and traffic flow status, the present invention selects the optimal hospital considering the above factors, realizes the optimization of the first aid response, obtains the optimal selection of the hospital, and greatly shortens the first aid response time; through the multi-dimensional screening of the above multiple factors, it ensures to obtain the most suitable first aid hospital, greatly improves the first aid success rate; the cloud platform realizes the two-way real-time transmission of first aid information by sending the first aid location and obtaining the feedback data of the hospital, improves the synchronization of data transmission, and avoids delays caused by information lag. Ensure the cooperation efficiency of each link in the first aid process, thereby improving the overall first aid efficiency and the safety of first aid services in case of emergencies.

[0082] In an embodiment of the present invention, the target first aid hospital screening module includes:

[0083] A path number extraction module is used to extract the number of communication base stations within the radiation range of each path corresponding to each candidate hospital;

[0084] A signal strength determination module is used to determine the signal strength of the base station radiation corresponding to the position of each path within the radiation range of each communication base station;

[0085] A communication signal strength coefficient acquisition module is used to obtain the communication signal strength coefficient corresponding to each path according to the signal strength of the base station radiation corresponding to the position of each communication base station within the radiation range of each path;

[0086] The communication signal strength coefficient is obtained by the following formula:

[0087]

[0088] Where S represents the communication signal strength coefficient; n represents the number of communication base stations within each path’s radiation range; A i represents the overlapping path area where the radiation range of the i-th communication base station overlaps with the path; A represents the total area of the path; B i B represents the signal strength of the base station radiation at the location of the path within the radiation range of the i-th communication base station; e represents the communication signal strength transmitted by the i-th communication base station;

[0089] A traffic flow coefficient acquisition module is used to extract the traffic flow state corresponding to each path, and obtain the traffic flow coefficient corresponding to each path according to the traffic flow state corresponding to each path;

[0090] An emergency safety factor acquisition module, configured to acquire an emergency safety factor corresponding to each path using the vehicle flow coefficient and the communication signal strength coefficient corresponding to each path;

[0091] The first aid safety factor is obtained by the following formula:

[0092]

[0093] Among them, R represents the emergency safety factor; S represents the communication signal strength coefficient; K represents the traffic flow coefficient;

[0094] A path number extraction module is used to extract the number of paths in each candidate hospital whose emergency safety factor exceeds a preset safety factor threshold;

[0095] The screening execution module is used to select the candidate hospital with the largest number of paths whose first-aid safety factor exceeds the preset safety factor threshold as the target first-aid hospital, or, when none of the candidate hospitals have paths with a first-aid safety factor exceeding the preset safety factor threshold, select the candidate hospital with the largest first-aid safety factor corresponding to the path as the target first-aid hospital.

[0096] The technical effects of the above technical solution are as follows: Traditional path planning only considers distance or time, ignoring communication stability and traffic dynamics, and has strong limitations in path planning. The above technical solution of this embodiment uses the communication signal strength coefficient (S) to quantify the communication quality of the path, ensuring that the ambulance can maintain stable contact with the hospital during the journey (such as transmitting patient data and receiving remote guidance), and avoiding communication interruption due to weak signals. Combining with the traffic flow coefficient (K) to reflect the risk of path congestion, preferentially select routes with low traffic flow to reduce the risk of delay. Finally, by synthesizing the two to obtain the first-aid safety factor (R), it can scientifically evaluate the overall safety of the path and guide the ambulance to select a path that is both unobstructed and has stable signals. At the same time, the traffic flow and signal strength can be dynamically updated (such as combining real-time traffic data and base station load) to make the path selection adapt to emergencies (such as traffic accidents and network congestion). By counting the number of qualified paths in the candidate hospitals, preferentially select hospitals with multiple reliable paths to avoid the failure of the first-aid task due to the failure of a single path. In addition, automatically screen the optimal target among multiple candidate hospitals to reduce human decision-making errors and improve the scheduling efficiency. When the paths around a certain hospital are all congested or have poor signals, the system can quickly switch to the sub-optimal hospital to balance the overall first-aid demand.

[0097] Specifically, the traffic flow coefficient acquisition module includes:

[0098] The first data extraction module is used to extract the number of road segments corresponding to each path;

[0099] The second data extraction module is used to extract the current traffic flow of each road segment and the traffic flow capacity of the road segment;

[0100] The third data extraction module is used to extract the free space path loss of the base station radiation signal corresponding to the location of each road segment;

[0101] The traffic flow coefficient determination module is used to obtain the traffic flow coefficient according to the number of road segments corresponding to each path and the traffic flow capacity of the road segment in combination with the free space path loss of the base station radiation signal corresponding to the location of each road segment;

[0102] Among them, the traffic flow coefficient is obtained through the following formula:

[0103]

[0104] Among them, K represents the traffic flow coefficient; m represents the number of road segments corresponding to each path; Li represents the traffic flow corresponding to the i-th road segment; F i represents the traffic capacity corresponding to the i-th road segment; σ i represents the free space path loss of the base station radiation signal corresponding to the i-th road segment; σ ci represents the additional loss caused by the traffic flow corresponding to the i-th road segment, and the additional loss caused by the traffic flow is obtained through the following formula:

[0105] σ ci = μ i · ρ i + δ i · v i + λ i

[0106] where σ ci represents the additional loss caused by the traffic flow corresponding to the i-th road segment; ρ i represents the vehicle density per unit area (vehicles per square kilometer) corresponding to the i-th road segment; v i represents the average vehicle speed (km / h) corresponding to the i-th road segment; μ i represents the vehicle density coefficient corresponding to the average vehicle speed of the i-th road segment, with the unit of dB / (vehicles per square kilometer), which is used to quantify the additional path loss caused by the reflection and shielding effects of the metal vehicle body when the vehicle density increases; δ i represents the vehicle speed coefficient of the average vehicle speed of the i-th road segment, with the unit of dB / (km / h), which is used to measure the impact of the vehicle moving speed on the signal stability. High-speed vehicles will cause rapid signal fluctuations (fast fading) and increase the instantaneous loss. λ represents the environmental compensation coefficient of the i-th road segment, with the unit of dB, which is directly superimposed on the total additional loss as a fixed offset to correct the fixed environmental interference not considered by the model.

[0107] The traffic flow coefficient obtained in the above manner is obtained by using the actual conditions of each road segment of the path and the relationship between the traffic flow of each road segment and the loss of the wireless communication signal. It can effectively improve the accuracy of obtaining the traffic flow coefficient and its evaluation matching with the wireless communication quality. Furthermore, while effectively improving the accuracy of the traffic flow coefficient in evaluating the traffic flow of the path, it maximally improves the representativeness of the impact of the traffic flow on the loss of the wireless signal transmission, thereby improving the evaluation accuracy of the impact of the traffic flow coefficient on the communication signal strength, and further improving the accuracy of the subsequent path screening.

[0108] And the determination methods of the vehicle density coefficient, the vehicle speed coefficient, and the environmental compensation coefficient are as follows:

[0109] Under different traffic flow rates (ρ) and vehicle speeds (v), measure the actual path loss, and synchronously record environmental characteristics (such as building density, base station height). Then, use multiple linear regression or machine learning algorithms to solve for the optimal solutions of μ, δ, and λ.

[0110] The working principle of the above technical solution is: obtain information related to the communication capabilities of a communication base station, and further obtain information on the communication capabilities of base stations near the path;

[0111] The calculated communication signal strength coefficient comprehensively considers the influences of the radiation range, path area, and signal strength, and further considers the communication signal strength coefficient affected by the correlation among the radiation range, path area, and signal strength.

[0112] Obtain information on the influence of the traffic flow state. The traffic flow coefficient considers the influencing factors of data such as the number of road segments, traffic flow capacity, free space path loss, additional loss, etc., and conducts a comprehensive analysis of the traffic flow coefficient;

[0113] Calculate the first aid safety coefficient by combining the traffic flow coefficient with the communication signal strength coefficient. The first aid safety coefficient considers the traffic flow coefficient affected by the above-mentioned influencing factors of data such as the number of road segments, traffic flow capacity, free space path loss, additional loss, etc., and the first aid safety quantification data affected by the communication signal strength coefficient influenced by the radiation range, path area, and signal strength.

[0114] Extract the paths that exceed the safety coefficient threshold, and then realize the data security analysis of the safe paths for each candidate hospital;

[0115] By obtaining the number of paths that exceed the safety coefficient threshold, further obtain the safest hospital on the path as the target first aid hospital, and realize the optimal selection of the target first aid hospital in path consideration.

[0116] The effects of the above technical solutions are as follows: By obtaining data information that takes into account the associated impacts of radiation range, path area, and signal strength, the comprehensiveness and accuracy of the identification of communication quality on the path are improved. Furthermore, the guarantee ability of real-time communication on the path is obtained, the stability of the communication connection is enhanced, and the delay of first aid caused by communication interruption is avoided. By calculating the traffic flow coefficient to consider the impact of traffic condition information on the first aid path, the accurate identification of the path clearance ability is improved, a path with higher passing efficiency is accurately obtained, and the vehicle passing efficiency is increased; By combining the communication signal strength coefficient and the traffic flow coefficient, the first aid safety coefficient is calculated. This coefficient comprehensively considers the impacts of communication quality and traffic conditions on the first aid path and can quantify the safety of the path. This calculation of the safety coefficient provides a quantitative standard for path screening, ensuring that the selected path is not only communication-stable but also traffic-unblocked, maximizing the first aid efficiency. At the same time, by extracting paths that exceed the safety coefficient threshold, the hospital with the safest path is selected as the target first aid hospital. Ensuring that the path of the target hospital has high communication quality and good traffic conditions can minimize the first aid response time and greatly improve the first aid efficiency; Through the synergistic effect of the above content, the remote first aid collaborative cloud platform can improve the quality of first aid services in emergency situations.

[0117] In one embodiment of the present invention, the data sharing module includes:

[0118] A data acquisition module, which is used to, when the ambulance dispatched by the target first aid hospital arrives at the first aid event location, collect real-time audio and video data and vital sign data of the first aid scene through real-time cameras, microphones, and wearable devices;

[0119] A data upload module, which is used to upload the audio and video data and vital sign data to the remote first aid collaborative cloud platform;

[0120] A data sharing execution module, which is used to share the audio and video data and vital sign data to the hospital terminal of the target first aid hospital through the remote first aid collaborative cloud platform.

[0121] The working principle of the above technical solution is as follows: When the ambulance dispatched by the target first aid hospital arrives at the first aid event location, the devices on the ambulance and the wearable devices carried by the first aid personnel (such as heart rate sensors, blood oxygen sensors) start to collect real-time audio and video data of the first aid scene and the patient's vital sign data (such as heart rate, blood oxygen saturation, etc.).

[0122] The collected audio and video data and vital sign data are uploaded to the remote first aid collaborative cloud platform in real time through the communication devices on the ambulance (such as 5G / 4G modules).

[0123] After receiving the data, the remote first-aid collaboration cloud platform shares it in real time to the hospital terminal of the target first-aid hospital. The hospital terminal views the audio and video data of the first-aid scene and the vital sign data of the patient through a dedicated software or system to ensure that the patient can receive treatment immediately after arriving at the hospital.

[0124] The effects of the above technical solution are as follows: By transmitting the audio and video data and vital sign data of the first-aid event location to the hospital terminal in real time through the remote first-aid collaboration cloud platform, the timeliness of data acquisition is guaranteed, first-aid preparations are made in advance, the first-aid response time is shortened, and the first-aid efficiency is improved.

[0125] Through the real-time sharing of data, waste or delay caused by information asymmetry is avoided.

[0126] Efficient collaboration is achieved through audio and video data and vital sign data to ensure seamless connection of all links in the first-aid process and improve the overall first-aid success rate.

[0127] Through real-time data sharing and remote collaboration, the first-aid time can be minimized, thereby increasing the survival rate of patients.

[0128] In one embodiment of the present invention, the implementation method of the AI-driven remote first-aid collaboration decision-making platform includes:

[0129] The remote first-aid collaboration cloud platform determines the location of the current first-aid event;

[0130] Determine the target first-aid hospital according to the first-aid safety factor between the first-aid event location and the candidate hospitals, and dispatch the target first-aid hospital to send an ambulance to the first-aid event location;

[0131] Share the first-aid data to the hospital terminal of the target first-aid hospital in real time through the remote first-aid collaboration cloud platform, as Figure 2 shown.

[0132] The working principle of the above technical solution is as follows: The remote first-aid collaboration cloud platform determines the location of the current first-aid event; accurately obtains the location of the current first-aid event through the location acquisition module for decision-making and analysis through the event location;

[0133] Determine the target first-aid hospital according to the first-aid safety factor between the first-aid event location and the candidate hospitals, and dispatch the target first-aid hospital to send an ambulance to the first-aid event location; analyze the first-aid safety factor between hospitals through the medical screening module, and then obtain the dispatch strategy through the event location and the first-aid safety factor;

[0134] Share the first-aid data to the hospital terminal of the target first-aid hospital in real time through the remote first-aid collaboration cloud platform. Perform the first-aid data sharing between each platform through the data sharing module to ensure the consistency and interoperability of the data and prevent delays caused by information asymmetry.

[0135] The effects of the above technical solution are as follows: By obtaining the geographical location of the first aid event, the occurrence location of the first aid event is determined, improving the efficiency of the first aid response, reducing the delay caused by unclear location, and enhancing the timeliness of the first aid response; By obtaining the first aid safety factor, a safer first aid strategy is obtained. Through the combined analysis of the first aid event location and the first aid safety factor, the most optimal option among multiple first aid hospitals can be obtained, and the ambulance can be dispatched in a timely manner. While improving the safety of the first aid, the first aid efficiency is enhanced, and the optimal hospital dispatching strategy is obtained to ensure that the ambulance can reach the first aid scene safely and in a timely manner. The above first aid strategy not only optimizes the first aid efficiency, but also optimizes the allocation of medical resources, reducing the first aid delay caused by improper hospital selection. Through the cloud platform, the real-time sharing of first aid data is realized, ensuring that the target first aid hospital can obtain the relevant information of the first aid event in a timely manner, and ensuring the consistency of the information, avoiding the first aid delay caused by information asymmetry or transmission delay. Through multi-party collaborative work, it is ensured that all links in the first aid process can obtain the latest information in real time, improving the overall collaborative efficiency of the first aid.

[0136] In one embodiment of the present invention, determining the current first aid event location includes:

[0137] The remote first aid collaborative cloud platform monitors in real time whether it receives a first aid request sent by a first aid terminal, where the first aid terminal includes but is not limited to a first aid vehicle, a vehicle automatic first aid alarm terminal, a mobile phone APP terminal, etc.;

[0138] When a first aid request is received, the current first aid location is located through the first aid terminal to obtain the current first aid event location.

[0139] The working principle of the above technical solution is as follows: The remote first aid collaborative cloud platform monitors in real time whether it receives a first aid request sent by a first aid terminal, where the first aid terminal includes but is not limited to a first aid vehicle, a vehicle automatic first aid alarm terminal, a mobile phone APP terminal, etc.; The first aid request sent by each first aid terminal is obtained through the request sending module, so that the cloud platform can obtain the first aid request information in the first time;

[0140] When a first aid request is received, the current first aid location is located through the first aid terminal to obtain the current first aid event location. When the location positioning acquisition module receives the first aid request information, it obtains the first aid event location of the first aid request information, ensuring the binding of the request information and the time location.

[0141] The effects of the above technical solutions are as follows: The remote first-aid collaboration cloud platform monitors in real time whether it has received a first-aid request sent by a first-aid terminal, where the first-aid terminal includes but is not limited to an ambulance, a vehicle automatic first-aid alarm terminal, a mobile phone APP terminal, etc.; the request sending module obtains the first-aid requests sent by each first-aid terminal, enabling the cloud platform to obtain the first-aid request information in the first time; by obtaining the first-aid request information through the cloud platform, it is ensured that each terminal can obtain the first-aid information in the first time, improving the real-time nature of the first-aid response and the information interoperability.

[0142] When a first-aid request is received, the current first-aid location is located through the first-aid terminal to obtain the current first-aid event location. The location positioning acquisition module obtains the first-aid event location of the first-aid request information while receiving the first-aid request information, ensuring the binding of the request information and the event location. By obtaining the first-aid event location while obtaining the first-aid request information, it is convenient to obtain the binding information of the request and the event location, reducing the possibility of data analysis errors and subsequent decision-making errors caused by excessive event and request information.

[0143] In an embodiment of the present invention, a target first-aid hospital is determined according to the first-aid event location, and the target first-aid hospital is dispatched to send an ambulance to the first-aid event location, including:

[0144] Retrieve a high-precision map and mark the current first-aid location on the high-precision map;

[0145] Obtain hospitals that meet the preset initial path distance requirements from the high-precision map as candidate hospitals;

[0146] Screen out the target first-aid hospital from the candidate hospitals according to the number of paths of the candidate hospitals, the traffic flow status of each path, and the communication network coverage intensity of each path;

[0147] The remote first-aid collaboration cloud platform sends the current first-aid location to the target first-aid hospital, and feeds back the real-time positioning information of the ambulance to the first-aid terminal after the target first-aid hospital dispatches the ambulance.

[0148] The working principle of the above technical solutions is as follows: Retrieve a high-precision map and mark the current first-aid location on the high-precision map, where the high-precision map includes but is not limited to various existing map systems; by marking the current first-aid location on the high-precision map, the visualization of the current first-aid location is realized, and high-precision location information can be obtained;

[0149] Obtain hospitals that meet the preset initial path distance requirement from the high-precision map; wherein, the meeting the preset initial path distance requirement means that any one of the one or more paths between the hospital location planned by the high-precision map and the current first-aid location is lower than the preset path distance threshold; first, obtain a path distance that meets the requirements as the initial path distance for comparison with other paths.

[0150] Screen out the target first-aid hospital from the candidate hospitals according to the number of paths of the candidate hospitals, the traffic flow status of each path, and the communication network coverage intensity of each path; obtain the first-aid hospital that meets the requirements of the number of paths, traffic flow status, and communication network coverage intensity, so that the first-aid hospital meets the basic first-aid requirements.

[0151] The information feedback module is used for the remote first-aid collaborative cloud platform to send the current first-aid location to the target first-aid hospital, and feedback the real-time positioning information of the ambulance to the first-aid terminal after the ambulance is dispatched by the target first-aid hospital. Send the first-aid location through the cloud platform, and obtain the feedback information of the target first-aid hospital to integrate and analyze the first-aid dispatching information.

[0152] The effects of the above technical solutions are as follows: The present invention selects the optimal hospital considering the above factors through high-precision maps, real-time locations, path data, and traffic flow status, realizes the optimization of first-aid response, and obtains the optimal selection of the hospital, greatly shortening the first-aid response time; through multi-dimensional screening of the above multiple factors, it ensures to obtain the most suitable first-aid hospital, greatly improving the first-aid success rate; the cloud platform realizes two-way real-time transmission of first-aid information by sending the first-aid location and obtaining the feedback data of the hospital, improves the synchronization of data transmission, and avoids delays caused by information lag. Ensure the cooperation efficiency of each link in the first-aid process, thereby improving the overall first-aid efficiency and the safety of first-aid services in case of emergencies.

[0153] An embodiment of the present invention, screening out the target first-aid hospital, includes:

[0154] Extract the number of radiation ranges of the communication base stations where each path corresponding to each candidate hospital is located;

[0155] Determine the signal strength of the base station radiation corresponding to the position of each path in the radiation range of each communication base station;

[0156] Obtain the communication signal strength coefficient corresponding to each path according to the signal strength of the base station radiation corresponding to the position of each path in the radiation range of each communication base station;

[0157] Wherein, the communication signal strength coefficient is obtained through the following formula:

[0158]

[0159] Among them, S represents the communication signal strength coefficient; n represents the number of radiation ranges of communication base stations where each path is located; A i represents the overlapping path area where the radiation range of the i-th communication base station overlaps with the path; A represents the total area of the path; B i represents the signal strength of the base station radiation at the location of the path within the radiation range of the i-th communication base station; B e represents the communication signal strength transmitted by the i-th communication base station;

[0160] Extract the traffic flow status corresponding to each path, and obtain the traffic flow coefficient corresponding to each path according to the traffic flow status corresponding to each path;

[0161] Use the traffic flow coefficient and communication signal strength coefficient corresponding to each path to obtain the first aid safety coefficient corresponding to each path;

[0162] Among them, the first aid safety coefficient is obtained through the following formula:

[0163]

[0164] Among them, R represents the first aid safety coefficient; S represents the communication signal strength coefficient; K represents the traffic flow coefficient;

[0165] Extract the number of paths in each candidate hospital whose first aid safety coefficient exceeds the preset safety coefficient threshold;

[0166] Take the candidate hospital with the largest number of paths whose first aid safety coefficient exceeds the preset safety coefficient threshold as the target first aid hospital, or, when none of the candidate hospitals have paths whose first aid safety coefficient exceeds the preset safety coefficient threshold, select the candidate hospital with the largest first aid safety coefficient corresponding to the path as the target first aid hospital.

[0167] Among them, extracting the traffic flow status corresponding to each path and obtaining the traffic flow coefficient corresponding to each path according to the traffic flow status corresponding to each path includes:

[0168] Extract the number of road segments corresponding to each path;

[0169] Extract the current traffic flow of each road segment and the traffic flow capacity of the road segment;

[0170] Extract the free space path loss of the base station radiation signal corresponding to the location of each road segment;

[0171] Obtain the traffic flow coefficient according to the number of road segments and the traffic flow capacity corresponding to each path in combination with the free space path loss of the base station radiation signal corresponding to the location of each road segment;

[0172] Among them, the traffic flow coefficient is obtained through the following formula:

[0173]

[0174] Among them, K represents the traffic flow coefficient; m represents the number of road segments corresponding to each path; L i represents the traffic flow corresponding to the i-th road segment; F i represents the traffic capacity corresponding to the i-th road segment; σ i represents the free space path loss of the base station radiation signal corresponding to the i-th road segment; σ ci represents the additional loss caused by the traffic flow corresponding to the i-th road segment, and the additional loss caused by the traffic flow is obtained through the following formula:

[0175] σ ci = μ i · ρ i + δ i · v i + λ i

[0176] Among them, σ ci represents the additional loss caused by the traffic flow corresponding to the i-th road segment; ρ i represents the vehicle density per unit area (vehicles per square kilometer) corresponding to the i-th road segment; v i represents the average vehicle speed (km / h) corresponding to the i-th road segment; μ i represents the vehicle density coefficient corresponding to the average vehicle speed of the i-th road segment, with the unit of dB / (vehicles per square kilometer), which is used to quantify the additional path loss caused by the reflection and occlusion effects of the vehicle metal body when the vehicle density increases; δ i represents the vehicle speed coefficient of the average vehicle speed of the i-th road segment, with the unit of dB / (km / h), which is used to measure the impact of the vehicle moving speed on the signal stability. High-speed vehicles will cause rapid signal fluctuations (fast fading) and increase the instantaneous loss. λ represents the environmental compensation coefficient of the i-th road segment, with the unit of dB, which is directly superimposed on the total additional loss as a fixed offset to correct the fixed environmental interference not considered by the model.

[0177] Moreover, the determination methods of the vehicle density coefficient, the vehicle speed coefficient, and the environmental compensation coefficient are as follows:

[0178] Under different traffic flow (ρ) and vehicle speed (v) conditions, measure the actual path loss, synchronously record the environmental characteristics (such as building density, base station height), and then use the multiple linear regression or machine learning algorithm to solve the optimal solutions of μ, δ, and λ.

[0179] The working principle of the above technical solution is as follows: Obtain information related to the communication capabilities of communication base stations, and further obtain the communication capability information of the base stations near the path;

[0180] The calculated communication signal strength coefficient comprehensively considers the influence of the radiation range, path area, and signal strength, and further considers the communication signal strength coefficient affected by the correlation between the radiation range, path area, and signal strength.

[0181] Obtain the influence information of the traffic flow status. The traffic flow coefficient considers the influencing factors of data such as the number of road segments, traffic flow capacity, free space path loss, additional loss, etc., and conducts a comprehensive analysis of the traffic flow coefficient;

[0182] Calculate the first aid safety coefficient by combining the traffic flow coefficient with the communication signal strength coefficient. The first aid safety coefficient considers the traffic flow coefficient affected by the above-mentioned influencing factors of data such as the number of road segments, traffic flow capacity, free space path loss, additional loss, etc., and the first aid safety quantification data affected by the communication signal strength coefficient affected by the radiation range, path area, and signal strength;

[0183] Extract the paths that exceed the safety coefficient threshold, and then realize the data security analysis of the safe paths for each candidate hospital;

[0184] By obtaining the number of paths that exceed the safety coefficient threshold, and then obtaining the safest hospital on the path as the target first aid hospital, realizing the optimal selection of the target first aid hospital in the path consideration.

[0185] The effect of the above technical solution is as follows: By obtaining data information that considers the correlated influence of the radiation range, path area, and signal strength, the comprehensiveness and accuracy of the identification of the communication quality on the path are improved. Furthermore, the guarantee ability of real-time communication on the path is obtained, the stability of the communication connection is improved, and the first aid delay caused by communication interruption is avoided. By calculating the traffic flow coefficient and considering the influence of traffic condition information on the first aid path, the accurate identification of the path smoothness ability is improved, the path with higher traffic efficiency is accurately obtained, and the vehicle passing efficiency is improved; By combining the communication signal strength coefficient and the traffic flow coefficient, the first aid safety coefficient is calculated. This coefficient comprehensively considers the influence of communication quality and traffic conditions on the first aid path and can quantify the safety of the path. This calculation of the safety coefficient provides a quantitative standard for path screening, ensuring that the selected path is not only communication stable but also traffic unobstructed, maximizing the first aid efficiency. At the same time, by extracting the paths that exceed the safety coefficient threshold, the hospital with the safest path is selected as the target first aid hospital. Ensure that the path of the target hospital has high communication quality and good traffic conditions, which can minimize the first aid response time and greatly improve the first aid efficiency; Through the synergistic effect of the above content, the remote first aid collaborative cloud platform can improve the quality of first aid services in emergency situations.

[0186] In one embodiment of the present invention, first aid data is shared in real time to the hospital terminal of the target first aid hospital through a remote first aid collaboration cloud platform, including:

[0187] When the ambulance dispatched by the target first aid hospital arrives at the location of the first aid incident, audio and video data and vital sign data at the first aid scene are collected in real time through a real-time collection camera, microphone and wearable devices (such as heart rate and blood oxygen sensors);

[0188] The audio and video data and vital sign data are uploaded to the remote first aid collaboration cloud platform;

[0189] The audio and video data and vital sign data are shared to the hospital terminal of the target first aid hospital through the remote first aid collaboration cloud platform.

[0190] The working principle of the above technical solution is: When the ambulance dispatched by the target first aid hospital arrives at the location of the first aid incident, the devices on the ambulance and the wearable devices (such as heart rate sensors and blood oxygen sensors) carried by the first aid personnel start to collect the audio and video data at the first aid scene and the vital signs of the patient (such as heart rate, blood oxygen saturation, etc.) in real time.

[0191] The collected audio and video data and vital sign data are uploaded to the remote first aid collaboration cloud platform in real time through the communication device (such as 5G / 4G module) on the ambulance.

[0192] After receiving the data, the remote first aid collaboration cloud platform shares it in real time to the hospital terminal of the target first aid hospital. The hospital terminal views the audio and video data at the first aid scene and the vital signs of the patient through a dedicated software or system to ensure that the patient can receive treatment immediately after arriving at the hospital.

[0193] The effect of the above technical solution is: The audio and video data and vital sign data at the location of the first aid incident are transmitted to the hospital terminal in real time through the remote first aid collaboration cloud platform, ensuring the timeliness of data acquisition, making first aid preparations in advance, shortening the first aid response time, and improving the first aid efficiency.

[0194] Through the real-time sharing of data, waste or delay caused by information asymmetry is avoided.

[0195] Efficient collaboration is achieved through audio and video data and vital sign data to ensure seamless connection of all links in the first aid process and improve the overall first aid success rate.

[0196] Through real-time data sharing and remote collaboration, the first aid time can be minimized to improve the survival rate of patients.

[0197] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. An AI-driven remote first aid collaborative decision-making platform, characterized in that, The AI-driven remote first aid collaborative decision-making platform includes: A location acquisition module, which is used for the remote first aid collaborative cloud platform to determine the location of the current first aid event; A hospital screening module, which is used to determine the target first aid hospital according to the first aid safety factor between the location of the first aid event and the candidate hospitals, and dispatch the target first aid hospital to send an ambulance to the location of the first aid event; A data sharing module, which is used to share the first aid data to the hospital terminal of the target first aid hospital in real time through the remote first aid collaborative cloud platform.

2. The AI-driven remote first aid collaborative decision-making platform according to claim 1, wherein The location acquisition module includes: A request sending module, which is used for the remote first aid collaborative cloud platform to monitor in real time whether it receives a first aid request sent by the first aid terminal; A location positioning and acquisition module, which is used to locate the current first aid location through the first aid terminal when receiving the first aid request, and acquire the location of the current first aid event.

3. The AI-driven remote first aid collaborative decision-making platform according to claim 1, characterized in that, The hospital screening module includes: A map retrieval module, which is used to retrieve a high-precision map and mark the current first aid location on the high-precision map; A candidate hospital acquisition module, which is used to obtain the hospitals that meet the preset initial path distance requirement from the high-precision map as candidate hospitals; A target first aid hospital screening module, which is used to screen out the target first aid hospital from the candidate hospitals according to the number of paths of the candidate hospitals and the traffic flow status of each path combined with the communication network coverage intensity of each path; An information feedback module, which is used for the remote first aid collaborative cloud platform to send the current first aid location to the target first aid hospital, and feedback the real-time positioning information of the ambulance to the first aid terminal after the target first aid hospital dispatches the ambulance.

4. The AI-driven remote first aid collaborative decision-making platform according to claim 3, characterized in that, The target first aid hospital screening module includes: A path number extraction module, which is used to extract the number of the radiation ranges of the communication base stations where each path corresponding to each candidate hospital is located; A signal strength determination module, which is used to determine the signal strength of the base station radiation corresponding to the position of each path in the radiation range of each communication base station; A communication signal strength coefficient acquisition module, which is used to acquire the communication signal strength coefficient corresponding to each path according to the signal strength of the base station radiation corresponding to the position of each path in the radiation range of each communication base station; A traffic flow coefficient acquisition module, which is used to extract the traffic flow status corresponding to each path, and acquire the traffic flow coefficient corresponding to each path according to the traffic flow status corresponding to each path; A first aid safety factor acquisition module, which is used to acquire the first aid safety factor corresponding to each path by using the traffic flow coefficient and the communication signal strength coefficient corresponding to each path; A path number extraction module, which is used to extract the number of paths in each candidate hospital whose first aid safety factor exceeds the preset safety factor threshold; A screening execution module, which is used to take the candidate hospital with the largest number of paths whose first aid safety factor exceeds the preset safety factor threshold as the target first aid hospital, or, when there is no path in all candidate hospitals whose first aid safety factor exceeds the preset safety factor threshold, select the candidate hospital with the largest first aid safety factor corresponding to the path as the target first aid hospital.

5. The AI-driven remote first aid collaborative decision-making platform according to claim 1, wherein The data sharing module includes: A data acquisition module, which is used to, when the ambulance dispatched by the target emergency hospital arrives at the location of the emergency event, collect real-time audio and video data and vital sign data of the emergency scene through a real-time acquisition camera, microphone, and wearable device; A data upload module, which is used to upload the audio and video data and vital sign data to a remote emergency collaboration cloud platform; A data sharing execution module, which is used to share the audio and video data and vital sign data to the hospital terminal of the target emergency hospital through the remote emergency collaboration cloud platform.

6. An implementation method of an AI-driven remote first aid collaborative decision-making platform, characterized in that, The implementation method of the AI-driven remote emergency collaboration decision-making platform includes: The remote emergency collaboration cloud platform determines the current emergency event location; Determine the target emergency hospital according to the emergency safety factor between the emergency event location and the candidate hospitals, and dispatch the target emergency hospital to send an ambulance to the emergency event location; The emergency data is shared to the hospital terminal of the target emergency hospital in real time through the remote emergency collaboration cloud platform.

7. The implementation method of the AI-driven remote first aid collaborative decision-making platform according to claim 6, characterized in that, Determining the current emergency event location includes: The remote emergency collaboration cloud platform monitors in real time whether it receives an emergency request sent by an emergency terminal; When an emergency request is received, the current emergency location is located through the emergency terminal to obtain the current emergency event location.

8. The implementation method of the AI-driven remote first aid collaborative decision-making platform according to claim 6, characterized in that, Determining the target emergency hospital according to the emergency event location and dispatching the target emergency hospital to send an ambulance to the emergency event location includes: Retrieve a high-precision map and mark the current emergency location on the high-precision map; Obtain the hospitals that meet the preset initial path distance requirements from the high-precision map as candidate hospitals; Screen out the target emergency hospital from the candidate hospitals according to the number of paths of the candidate hospitals and the traffic flow status of each path in combination with the communication network coverage intensity of each path; The remote emergency collaboration cloud platform sends the current emergency location to the target emergency hospital and feeds back the real-time positioning information of the ambulance to the emergency terminal after the target emergency hospital dispatches the ambulance.

9. The implementation method of the AI-driven remote first aid collaborative decision-making platform according to claim 8, characterized in that Screening out the target emergency hospital includes: Extract the number of radiation ranges of communication base stations where each path corresponding to each candidate hospital is located; Determine the signal intensity of the base station radiation corresponding to the position of each path in the radiation range of each communication base station; Obtain the communication signal intensity coefficient corresponding to each path according to the signal intensity of the base station radiation corresponding to the position of each path in the radiation range of each communication base station; Extract the traffic flow status corresponding to each path, and obtain the traffic flow coefficient corresponding to each path according to the traffic flow status corresponding to each path; Use the traffic flow coefficient and communication signal intensity coefficient corresponding to each path to obtain the emergency safety coefficient corresponding to each path; Extract the number of paths in each candidate hospital whose emergency safety coefficient exceeds the preset safety coefficient threshold; Use the candidate hospital with the largest number of paths whose emergency safety coefficient exceeds the preset safety coefficient threshold as the target emergency hospital, or, when none of the candidate hospitals have paths whose emergency safety coefficient exceeds the preset safety coefficient threshold, select the candidate hospital with the largest emergency safety coefficient corresponding to the path as the target emergency hospital.

10. The implementation method of the AI-driven remote first aid collaborative decision-making platform according to claim 6, wherein, Sharing the emergency data to the hospital terminal of the target emergency hospital in real time through the remote emergency collaboration cloud platform includes: When the ambulance dispatched by the target emergency hospital arrives at the location of the emergency, the audio-visual data and vital sign data of the emergency scene are collected in real time through the real-time collection of cameras, microphones, and wearable devices; Upload the audio-visual data and vital sign data to the remote emergency collaboration cloud platform; Share the audio-visual data and vital sign data to the hospital terminal of the target emergency hospital through the remote emergency collaboration cloud platform.

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