An emergency rescue dynamic coordination system and method integrated with a Beidou SOS wrist watch

Abstract

This invention discloses an emergency rescue dynamic collaborative system and method integrating a Beidou SOS wristwatch, belonging to the field of intelligent emergency rescue technology. It includes modules for multi-dimensional data acquisition, dynamic assessment, dynamic matching, collaborative planning, command coordination, and closed-loop optimization. The method involves collecting and uploading multi-dimensional situational data when the wristwatch triggers SOS; the command center calculates a rescue urgency index using a dynamic rescue priority self-learning model; based on the index, dynamic resource matching is initiated to form a task allocation scheme; a collaborative optimal path integrating environmental resistance and multi-body obstacle avoidance is generated; the path is issued and an adaptive heartbeat command is sent to the wristwatch; the rescue process is monitored, and model parameters are optimized using task data to achieve closed-loop self-evolution. This invention achieves accurate hazard assessment, efficient resource scheduling, and collaborative path planning, significantly improving the intelligence level and execution efficiency of emergency rescue in complex sea conditions.

Description

Technical Field

[0001] This invention relates to the field of intelligent emergency rescue technology, and in particular to an emergency rescue dynamic collaborative system and method integrating a Beidou SOS wristwatch. Background Technology

[0002] In recent years, with the maturity and widespread application of the BeiDou Navigation Satellite System, emergency rescue devices based on BeiDou short message communication, such as SOS wristwatches, have been initially applied in fields such as maritime rescue and field operations. Related technologies mainly focus on improving the positioning accuracy, communication reliability, and environmental adaptability of these devices, achieving alarm information transmission from scratch and forming the information foundation layer of the emergency rescue system. Existing solutions mostly follow a linear process of "trigger-reporting-response," initially establishing a one-way information link between individuals in distress and the command center.

[0003] Existing technologies have significant limitations. Rescue decisions largely rely on human experience or fixed rules, making it difficult to uniformly process and quantify risks based on multi-dimensional situational information such as location, environment, and attitude, resulting in low efficiency in prioritizing alarm events. Resource scheduling often employs static assignment or proximity principles, lacking collaborative consideration of the status of rescue units, dynamic environmental resistance, and concurrent path conflicts of multiple tasks, hindering efficient integration of rescue forces and collaborative path planning. Furthermore, the systems generally lack model optimization mechanisms based on completed rescue mission data and struggle to dynamically adjust the information reporting frequency of wristwatches according to the rescue progress, restricting the continuous improvement of overall rescue efficiency. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides an emergency rescue dynamic coordination method integrating a Beidou SOS wristwatch to address the problems of existing maritime emergency rescue methods, such as inaccurate risk assessment due to the simplistic nature of alarm information, low scheduling efficiency due to static allocation of rescue resources, and how to achieve self-optimization and closed-loop evolution of the system in complex dynamic environments.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides an emergency rescue dynamic coordination method integrating a Beidou SOS wristwatch, characterized by comprising the following steps: When the wristwatch triggers an SOS alarm, it collects multi-dimensional situational data including location information and sensor data, and uploads the multi-dimensional situational data to the command center; The command center's server receives the multi-dimensional situational data and uses a calculation model to calculate the urgency of the rescue, outputting the urgency value of the rescue for the corresponding alarm event. Based on the rescue urgency value, the command center's server sorts the alarm events, sends task invitations containing task location and urgency level to multiple rescue units, and receives the execution cost value reported by each rescue unit to form a preliminary task allocation plan. Based on the preliminary task allocation scheme, the command center's server generates a collaborative planning path for each assigned rescue unit, taking into account real-time environmental resistance and the planned paths of other rescue units. The command center's server will send the collaboratively planned path to the corresponding rescue unit, and at the same time send a location reporting frequency adjustment command to the target wristwatch that is associated with the expected arrival time of the corresponding rescue unit; The command center's server monitors the rescue execution process and collects mission data after a successful rescue. The mission data is then used to optimize the parameters of the calculation model, completing a closed-loop self-evolution.

[0007] As a preferred embodiment of the emergency rescue dynamic coordination method for the integrated Beidou SOS wristwatch described in this invention, the wristwatch, upon triggering an SOS alarm, collects multi-dimensional situational data including location information and sensor data, and uploads the multi-dimensional situational data to the command center. The specific steps are as follows: The watch's main control chip simultaneously activates the Beidou positioning chip and the set of miniature environmental sensors to acquire latitude and longitude coordinates, as well as raw environmental and attitude data including temperature, air pressure, and three-dimensional acceleration. The main control chip verifies and encapsulates the latitude and longitude coordinates and the original environmental and attitude data to form a multi-dimensional situational data frame with a standard format. The multi-dimensional situational data frame is divided into a positioning data area, an environmental data area, and an attitude data area. The main control chip controls the BeiDou short message communication unit to call the BeiDou short message communication function and upload the multi-dimensional situational data frame as the primary sending object; The watch enters an alarm standby state, and its indicator light switches to a slow flashing mode to confirm that the multi-dimensional situational data frame has been successfully transmitted.

[0008] As a preferred embodiment of the emergency rescue dynamic coordination method integrating a Beidou SOS wristwatch as described in this invention, the server of the command center receives the multi-dimensional situational data and uses a calculation model for calculating the urgency of rescue to calculate and output the urgency value of rescue corresponding to the alarm event. The specific steps are as follows: The command center's server parses and standardizes the received multi-dimensional situational data frames, separating out positioning data, environmental data, and attitude data, and assigns a unified timestamp and event ID to the positioning data, environmental data, and attitude data. The command center's server inputs the parsed standardized data and real-time acquired macro-oceanic meteorological data into the calculation model; The computational model identifies water-falling event tags or ship capsizing event tags based on the violent motion characteristics in the attitude data and the sudden changes in temperature data. The calculation model integrates the tags of the drowning incident or the capsizing incident, the severity of the weather, and the overall load of surrounding rescue resources, and outputs a quantitative value of the urgency of the rescue according to a preset weight calculation method.

[0009] As a preferred embodiment of the emergency rescue dynamic coordination method integrating the Beidou SOS wristwatch described in this invention, the following steps are taken: Based on the rescue urgency value, the command center server sorts the alarm events, sends task invitations containing task location and urgency level to multiple rescue units, and receives the execution cost values ​​fed back by each rescue unit to form a preliminary task allocation plan. The specific steps are as follows: The command center's server sorts all alarm events according to their urgency level and generates a queue of tasks to be rescued. The command center's server broadcasts an invitation message containing the mission location and urgency level to all available rescue units based on the queue of missions awaiting rescue. The command center's server receives execution cost values ​​calculated based on the location, speed, and mission type of each rescue unit. The command center's server runs a many-to-many matching algorithm to match the rescue missions with the rescue units, aiming to minimize the total global execution cost, and outputs a preliminary mission allocation plan.

[0010] As a preferred embodiment of the emergency rescue dynamic coordination method integrating Beidou SOS wristwatches described in this invention, wherein: based on the preliminary task allocation scheme, the server of the command center generates a collaborative planning path for each assigned rescue unit, taking into account real-time environmental resistance and the planned paths of other rescue units. The specific steps are as follows: The command center's server obtains the preliminary task allocation plan and initializes an initial path from the current location to the task point for each assigned rescue unit; The command center's server receives real-time ocean current data and wind field data, and quantifies the real-time ocean current data and wind field data into a dynamically changing resistance field, which is then overlaid on the electronic nautical chart. The command center's server performs collaborative path conflict detection, treating the planned paths of other rescue units as moving obstacles, detecting whether there are spatiotemporal risks of route intersection or close-range navigation risks, and generating conflict detection results that include route intersection risk points and close-range navigation risk points. Based on the dynamically changing resistance field and the conflict detection results, the command center's server replans a collaborative planning path for each rescue unit to avoid high-resistance areas, route intersection risk points, and close-range navigation risk points.

[0011] As a preferred embodiment of the emergency rescue dynamic coordination method for the integrated Beidou SOS wristwatch described in this invention, the server of the command center distributes the coordinated planning path to the corresponding rescue unit, and simultaneously sends a location reporting frequency adjustment command associated with the expected arrival time of the corresponding rescue unit to the target wristwatch. The specific steps are as follows: The command center's server will send the generated collaborative planning path data packets to the smart terminals of the corresponding rescue units via the BeiDou downlink; The command center's server calculates dynamically updated estimated arrival times for each rescue unit based on the collaboratively planned routes; Based on the dynamically updated estimated arrival time, the command center's server generates a location reporting frequency adjustment instruction for the corresponding target wristwatch. The location reporting frequency adjustment instruction includes reporting frequency parameters that change over time. The command center's server sends the location reporting frequency adjustment instruction to the target wristwatch via BeiDou short message. Upon receiving the instruction, the target wristwatch adjusts its location reporting frequency accordingly.

[0012] As a preferred embodiment of the emergency rescue dynamic coordination method integrating a Beidou SOS wristwatch as described in this invention, the server of the command center monitors the rescue execution process and collects task data after a successful rescue. The task data is then used to optimize the parameters of the computational model, completing a closed-loop self-evolution. The specific steps are as follows: The command center's server continuously tracks and records the actual navigation trajectory of the rescue units, compares the actual navigation trajectory with the collaboratively planned path, and calculates the path following deviation of the actual navigation trajectory relative to the collaboratively planned path. When a rescue unit reports a successful rescue signal through its terminal, the command center's server automatically tags the alarm event as successful and records the total response time from alarm to success. The command center's server stores the complete data packet for this mission in a structured manner. The complete data packet includes initial multidimensional situational data, rescue urgency values, path following deviations, and total response time. The command center's server inputs the complete data packet into the computational model to trigger incremental learning and fine-tuning of the model parameters, thereby completing closed-loop optimization based on actual rescue results.

[0013] Secondly, the present invention provides an emergency rescue dynamic collaborative system integrating a Beidou SOS wristwatch, characterized in that it includes a wristwatch, a command center server, and a smart terminal for rescue units; The wristwatch includes a main control chip, a Beidou positioning chip, a temperature sensor, a barometric pressure sensor, a three-dimensional accelerometer, and a Beidou short message communication unit. The main control chip is used to control the Beidou positioning chip to obtain latitude and longitude coordinates, control the temperature sensor, barometric pressure sensor, and three-dimensional accelerometer to obtain raw environmental and attitude data when the wristwatch triggers an SOS alarm, and encapsulate the latitude and longitude coordinates and the raw environmental and attitude data into a multi-dimensional situational data frame. The Beidou short message communication unit is used to upload the multi-dimensional situational data frame to the command center server. The command center server is used to receive the multi-dimensional situational data frames, parse them to obtain positioning data, environmental data and attitude data, and combine them with macro-oceanic meteorological data to calculate the urgency of the rescue for the alarm event. The command center server is also used to sort alarm events based on the rescue urgency value, send task invitations containing task location and urgency level to multiple rescue unit smart terminals, and receive execution cost values ​​fed back by each rescue unit smart terminal to form a preliminary task allocation plan. The command center server is also used to generate a collaborative planning path for the corresponding rescue units based on the preliminary task allocation plan, combined with real-time ocean current data, wind field data, and the planned paths of other rescue units. The intelligent terminal of the rescue unit is used to receive the collaboratively planned path and to feed back the location data and rescue success signal during the rescue execution process to the command center server. The command center server is also used to calculate the estimated arrival time of the rescue unit based on the collaborative planning path, send a location reporting frequency adjustment instruction to the target wristwatch, and optimize the parameters of the calculation model used to calculate the rescue urgency value using mission data after the rescue is successful.

[0014] Thirdly, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the emergency rescue dynamic coordination method of the integrated Beidou SOS wristwatch as described in the first aspect of the present invention.

[0015] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the emergency rescue dynamic coordination method for an integrated Beidou SOS wristwatch as described in the first aspect of the present invention.

[0016] The beneficial effects of this invention are as follows: By constructing a processing flow from wristwatch information collection, command center risk calculation, rescue unit task matching, collaborative path planning to task data feedback optimization, dynamic collaboration in the emergency rescue process is achieved. When the wristwatch triggers an SOS alarm, it uploads multi-dimensional situational data containing location, environmental, and attitude information, enabling the command center to calculate the urgency of the alarm event based on the on-site status and macro-oceanic meteorological data, thus improving the efficiency of alarm event priority determination; dynamic matching between rescue tasks and rescue units is achieved through task sorting, task invitation, and execution cost feedback based on the urgency value; collaborative planning paths that can avoid high-resistance areas and path conflict risks are generated by incorporating real-time ocean current data, wind field data, and other rescue unit planned paths into the path planning process; the information reporting process of the wristwatch is adapted to the rescue progress by adjusting the location reporting frequency of the target wristwatch according to the expected arrival time; and the system can continuously improve the urgency calculation process based on completed rescue tasks by collecting task data and optimizing calculation model parameters after a successful rescue, thereby improving the overall collaborative efficiency of emergency rescue. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of an emergency rescue dynamic coordination method integrating a Beidou SOS wristwatch in one embodiment. Detailed Implementation

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0020] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0021] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0022] Reference Figure 1 This is the first embodiment of the present invention, which provides an emergency rescue dynamic coordination method integrating a Beidou SOS wristwatch, characterized by the following steps: When the wristwatch triggers an SOS alarm, it collects multi-dimensional situational data, including location information and sensor data, and uploads the multi-dimensional situational data to the command center. The command center's server receives multi-dimensional situational data and uses a calculation model to calculate the urgency of the rescue, outputting the urgency value of the rescue for the corresponding alarm event. Based on the urgency level of the rescue, the command center's server sorts the alarm events, sends task invitations containing task location and urgency level to multiple rescue units, and receives the execution cost values ​​from each rescue unit to form a preliminary task allocation plan. Based on the preliminary task allocation plan, the command center's server generates a collaborative planning path for each assigned rescue unit, taking into account real-time environmental resistance and the planned paths of other rescue units. The command center's server will coordinate and plan the route and send it to the corresponding rescue unit, while simultaneously sending a location reporting frequency adjustment instruction to the target wristwatch that is associated with the expected arrival time of the corresponding rescue unit. The command center's server monitors the rescue execution process and collects mission data after a successful rescue. It then uses the mission data to optimize the parameters of the calculation model, completing a closed-loop self-evolution.

[0023] It should be noted that by synchronously collecting positioning information, environmental information, and attitude information through the wristwatch, the single alarm reporting is expanded into multi-dimensional situational data reporting. This enables the command center to obtain the location of the alarm event, the status of the on-site environment, and the movement status of the wristwatch, providing a structured data foundation for subsequent rescue urgency calculations.

[0024] By analyzing multi-dimensional situational data through the command center's server and combining it with macro-level marine meteorological data to calculate the urgency of the rescue, alarm events can be quantified according to their risk level, reducing processing delays caused by relying solely on human experience or fixed rules for judgment.

[0025] By prioritizing tasks based on their urgency, inviting tasks, and providing feedback on execution costs, rescue tasks can be allocated based on the rescue unit's current location, speed, task type, and workload, avoiding uneven resource allocation caused by simply using static assignment or proximity principles.

[0026] By incorporating real-time ocean current data, wind field data, and other rescue unit planned routes into the route planning process, the command center's server can simultaneously consider environmental resistance and route conflicts between multiple rescue units when planning rescue routes, thereby reducing the risk of route interference in multi-task concurrent scenarios.

[0027] By adjusting the location reporting frequency of the target wristwatch according to the expected arrival time of the rescue unit, the wristwatch can increase the density of location information reporting in the approaching stage of the rescue and reduce the communication frequency in the non-approaching stage, thereby adapting the information acquisition process to the rescue process.

[0028] By collecting multi-dimensional situational data, rescue urgency values, path following deviations, and total response time after a successful rescue, and using the aforementioned task data to optimize the parameters of the calculation model, the system can continuously improve the urgency calculation process of alarm events based on completed rescue tasks.

[0029] Specifically, when the wristwatch triggers an SOS alarm, it collects multi-dimensional situational data including location information and sensor data, and uploads this data to the command center. The specific steps are as follows: The watch's main control chip simultaneously activates the Beidou positioning chip and the set of miniature environmental sensors to acquire latitude and longitude coordinates, as well as raw environmental and attitude data including temperature, air pressure, and three-dimensional acceleration. The main control chip verifies and encapsulates latitude and longitude coordinates as well as raw environmental and attitude data to form a multi-dimensional situational data frame with a standard format. The multi-dimensional situational data frame is divided into a positioning data area, an environmental data area, and an attitude data area. The main control chip controls the Beidou short message communication unit to call the Beidou short message communication function and upload multi-dimensional situational data frames as the primary transmission target; The watch enters alarm standby mode, and its indicator light switches to a slow flashing mode to confirm that the multidimensional situational data frame has been successfully transmitted.

[0030] It should be noted that when the watch's SOS button is triggered, the watch's main control chip sends a positioning start command to the Beidou positioning chip and controls the temperature sensor, barometric pressure sensor, and 3D accelerometer to enter data acquisition mode. The Beidou positioning chip acquires the latitude and longitude coordinates of the watch's location, the temperature sensor acquires the current ambient temperature, the barometric pressure sensor acquires the current ambient air pressure, and the 3D accelerometer acquires the acceleration change data of the watch in three axes. The latitude and longitude coordinates, ambient temperature, ambient air pressure, and 3D acceleration change data together constitute the raw environmental and attitude data.

[0031] By synchronously controlling the Beidou positioning chip and various sensors through the main control chip, the watch can simultaneously obtain location data, environmental data, and attitude data when the SOS alarm is triggered, avoiding the problem that the alarm information only contains location information and cannot reflect the on-site status.

[0032] After receiving latitude and longitude coordinates, as well as raw environmental and attitude data, the main control chip performs integrity verification and format conversion on the data. Upon successful verification, the main control chip generates a multi-dimensional situational data frame according to a preset data frame format. The positioning data area contains latitude and longitude coordinates, the environmental data area contains temperature and air pressure data, and the attitude data area contains three-dimensional acceleration data. The multi-dimensional situational data frame also includes the wristwatch device number, alarm trigger time, frame length, and a verification field, enabling the command center's server to identify the alarm source and verify data integrity.

[0033] By encapsulating data from different sources into multi-dimensional situational data frames with a unified format, the command center's server can parse alarm data according to fixed fields, reducing the parsing difficulties caused by directly uploading heterogeneous data.

[0034] After generating a multi-dimensional situational data frame, the main control chip controls the BeiDou short message communication unit to enter alarm reporting mode and writes the multi-dimensional situational data frame into the BeiDou short message communication unit's transmission buffer. The BeiDou short message communication unit then sends the multi-dimensional situational data frame to the command center based on the command center address pre-configured on the wristwatch.

[0035] By uploading multi-dimensional situational data frames through the BeiDou short message communication unit, the wristwatch can transmit alarm information in environments with insufficient mobile communication network coverage or at sea, thereby improving the applicability of alarm reporting.

[0036] After the multi-dimensional situational data frame is transmitted, the main control chip of the watch switches the indicator light from its normal state to a slow flashing mode to indicate to the wearer that the alarm data has been sent and the watch has entered a waiting-for-rescue state. At the same time, the main control chip reduces the operating frequency of non-essential functions to reduce the watch's power consumption.

[0037] The indicator light status changes allow the wearer to confirm the alarm reporting status; by reducing the frequency of non-essential functions, the watch can maintain a longer working time while waiting for rescue.

[0038] Specifically, the command center's server receives multi-dimensional situational data and uses a calculation model to calculate the urgency of the rescue operation, outputting the urgency value for the corresponding alarm event. The specific steps are as follows: The command center's server parses and standardizes the received multi-dimensional situational data frames, separating the positioning data, environmental data, and attitude data, and assigning a unified timestamp and event ID to the positioning data, environmental data, and attitude data. The command center's server inputs the parsed standardized data and real-time acquired macro-oceanic meteorological data into the calculation model; The computational model identifies water-falling event labels or ship capsizing event labels based on violent motion features in attitude data and sudden changes in temperature data. The calculation model integrates the tags of the drowning incident or the capsizing incident, the severity of the weather, and the overall load of surrounding rescue resources, and outputs a quantitative value of the urgency of the rescue according to a preset calculation method.

[0039] It should be noted that after the command center's server receives the multi-dimensional situational data frame uploaded by the wristwatch via the BeiDou communication link, it first determines whether the data frame is complete based on the frame length and check fields. Then, it extracts the wristwatch's device number, latitude and longitude coordinates, ambient temperature, ambient air pressure, and three-dimensional acceleration data according to a preset field order. The command center's server uses the latitude and longitude coordinates as positioning data, the temperature and air pressure data as environmental data, and the three-dimensional acceleration data as attitude data, and assigns a unified timestamp and event ID to the above data.

[0040] By parsing and standardizing multi-dimensional situational data frames, the location data, environmental data, and attitude data corresponding to the same alarm event can be associated under a unified event ID, which facilitates subsequent risk quantification.

[0041] After obtaining standardized data, the command center's server determines the sea area where the alarm event occurred based on the location data and acquires the corresponding macro-level marine meteorological data. This macro-level marine meteorological data includes wind field data, ocean current data, wave height data, and data indicating the severity of weather conditions in the area. The command center's server then inputs the location data, environmental data, attitude data, and macro-level marine meteorological data into the calculation model.

[0042] It should be noted that before the system was put into use, the initial parameters of the calculation model were determined based on historical rescue mission data and rescue drill data. This historical data includes location data, environmental data, attitude data, macro-level marine meteorological data, rescue unit status data, actual response time, rescue completion results, and manually labeled event risk levels corresponding to alarm events. The command center's server uses this data as sample data to establish a correspondence between multi-dimensional situational data, weather severity, resource load, and rescue urgency values ​​in the calculation model. After subsequent rescue missions are completed, the command center's server uses newly generated mission data to incrementally adjust the parameters of the calculation model.

[0043] By clearly defining the source of the initial data for the computational model, the initial parameters of the computational model and the subsequent incremental optimization process have a data foundation, thus avoiding a disconnect between the generation process of the computational model and the subsequent parameter optimization process.

[0044] By inputting the on-site data uploaded by the wristwatch into the calculation model along with macro-oceanic meteorological data, the urgency of the rescue can simultaneously reflect the individual's distress status and the risks of the external environment.

[0045] After receiving attitude and environmental data, the computational model extracts change features from the three-dimensional acceleration data to identify any sudden, violent movements, continuous rolling, or abnormal stillness. Simultaneously, it analyzes the temperature data to determine trends and identify any sudden temperature drops. Based on the attitude change features and temperature fluctuations, the computational model determines the corresponding water-falling event tag or ship capsizing event tag for the alarm event.

[0046] By combining attitude data and temperature data, the command center's server can make a preliminary identification of the alarm event type, avoiding reliance solely on manual communication or location reporting to determine the type of danger.

[0047] After obtaining tags for a fall-over incident or a capsizing incident, the command center's server inputs the confidence level corresponding to the incident tag, acceleration changes in the attitude data, the severity of weather conditions in the current sea area, temperature changes, and the global load of surrounding rescue resources into the calculation model. The calculation model then calculates the rescue urgency value according to a preset method. The rescue urgency value, as a standardized quantitative output, is used to represent the rescue priority of the alarm event under the current global situation.

[0048] To more accurately quantify the urgency of the rescue effort, the following mathematical formula is introduced for calculation: ; in As a rescue urgency index, The time from when the alarm started. For model calibration coefficients, For time The confidence function for high-risk events. For time The magnitude of the acceleration vector, It is the stability constant. Meteorological influencing factors, For time The weather severity function, The temperature change sensitivity coefficient, The current temperature. The initial temperature, For resource load weight, The current resource load rate, This is a smoothing constant. Its range is (0,1), with values ​​closer to 1 indicating higher urgency, and 0.5 representing a medium urgency threshold.

[0049] The above calculation method allows the urgency of the rescue to be affected by the event confidence level, the severity of the situation, the severity of the weather, the temperature change, and the resource load, thus avoiding the need to rely solely on fixed manual rules to determine the priority of alarm events.

[0050] Specifically, based on the urgency level of the rescue operation, the command center's server sorts the alarm events, sends task invitations containing task location and urgency level to multiple rescue units, and receives execution cost values ​​from each rescue unit to form a preliminary task allocation plan. The specific steps are as follows: The command center's server sorts all alarm events according to their urgency level and generates a queue of tasks to be rescued. The command center's server broadcasts invitation information, including mission location and urgency level, to all available rescue units based on the queue of missions awaiting rescue. The command center's server receives execution cost values ​​calculated based on the location, speed, and mission type of each rescue unit. The command center's server runs a many-to-many matching algorithm to match the rescue missions with the rescue units, aiming to minimize the total global execution cost, and outputs a preliminary mission allocation plan.

[0051] It should be noted that when multiple alarm events occur, the command center's server first obtains the rescue urgency value calculated by the calculation model for each alarm event, and then arranges the alarm events in descending order of rescue urgency value to generate a queue of tasks awaiting rescue. Each task node in the queue of tasks awaiting rescue includes an event ID, task location, rescue urgency value, and urgency level.

[0052] By generating a queue of tasks to be rescued based on the urgency of the rescue, alarm events can be entered into the subsequent resource allocation process according to their risk level, avoiding delays in response to high-risk events caused by simply processing them in the order of alarm time.

[0053] The command center's server filters available rescue units from the queue of pending rescue missions and sends mission invitation information to the smart terminals of these units. The mission invitation information includes mission location, urgency level, event ID, and mission type. Upon receiving the mission invitation information, the rescue unit's smart terminal calculates the execution cost required to carry out the mission, taking into account its current location, speed, equipment capabilities, current mission load, and mission type, and then feeds this cost back to the command center's server.

[0054] By having rescue units provide feedback on execution costs via their smart terminals, the command center's server can obtain the actual workload of each rescue unit when performing different tasks, thus avoiding resource allocation based solely on distance.

[0055] The execution cost is determined by the distance from the rescue unit's current location to the mission location, the rescue unit's speed, the rescue unit's current mission load status, and the degree of mission type matching. The greater the distance, the lower the speed, the higher the current mission load, or the lower the degree of mission type matching, the higher the corresponding execution cost.

[0056] To optimize the calculation of execution costs, the following mathematical formula is introduced: ; in To commit to costs, To estimate the sailing time, The time decay coefficient, The attenuation rate, For time The speed function, Distance weights For the location vector of the rescue unit, The task location vector, It is a smoothing constant. As the load impact factor, The current load rate of the rescue unit, This is a scaling factor for task urgency. Sensitivity coefficient This is the task urgency index. The value range is (0,∞). The lower the cost, the more suitable it is. It is usually evaluated on a logarithmic scale, and a value less than 1 indicates a high degree of matching.

[0057] By incorporating estimated travel time, speed, location of rescue units, mission location, current load factor, and mission urgency into the calculation of execution costs, mission allocation can simultaneously consider the spatial location and execution capabilities of rescue units, thereby improving the rationality of resource matching.

[0058] After receiving execution cost values ​​from the smart terminals of multiple rescue units, the command center's server runs a many-to-many matching algorithm. This algorithm calculates the matching relationship between the tasks to be rescued and the rescue units, aiming to minimize the total global execution cost. Under the conditions of satisfying the availability of rescue units and task requirements, it determines the correspondence between the tasks to be rescued and the rescue units, forming a preliminary task allocation plan.

[0059] By using a many-to-many matching algorithm for task allocation, multiple alarm events and multiple rescue units can be matched as a whole, reducing the adverse impact of local optimal allocation of a single task on the overall rescue efficiency.

[0060] Specifically, based on the preliminary task allocation plan, the command center's server generates a collaborative planning path for each assigned rescue unit, taking into account real-time environmental resistance and the planned paths of other rescue units. The specific steps are as follows: The command center's server obtains the preliminary task allocation plan and initializes an initial path from the current location to the task point for each assigned rescue unit; The command center's server accesses real-time ocean current data and wind field data, and quantifies the real-time ocean current data and wind field data into a dynamically changing resistance field, which is then overlaid on the electronic nautical chart. The command center's server performs collaborative path conflict detection, treating the planned paths of other rescue units as moving obstacles, detecting whether there are spatiotemporal risks of route intersection or close-range navigation risks, and generating conflict detection results that include route intersection risk points and close-range navigation risk points. Based on the dynamically changing resistance field and conflict detection results, the command center's server re-plans a collaborative planning path for each rescue unit to avoid high-resistance areas, route intersection risk points, and close-range navigation risk points.

[0061] It should be noted that after receiving the initial task allocation plan, the command center's server reads the current location of each assigned rescue unit and the corresponding task location, and generates an initial path from the rescue unit's current location to the task location on the electronic nautical chart. This initial path serves as the basis for subsequent path adjustments.

[0062] By first generating an initial path, the command center's server can continue to incorporate environmental and conflict factors after determining the basic direction of travel, thereby reducing the computational complexity of path planning.

[0063] The command center's server accesses real-time ocean current and wind field data for the current sea area and divides the electronic nautical chart into multiple grid areas based on ocean current direction, current speed, wind direction, and wind speed. The command center's server calculates the corresponding resistance value for each grid area, forming a dynamically changing resistance field. The resistance value represents the magnitude of environmental resistance encountered by rescue units when passing through the corresponding grid area.

[0064] By quantifying ocean current and wind field data into drag fields, abstract marine meteorological data can be transformed into computable parameters in the path planning process, thereby enabling collaboratively planned paths to avoid high-drag areas.

[0065] The command center's server treats the planned paths of other rescue units as moving obstacles and, based on the predicted locations of each rescue unit at different times, determines whether there is a risk of course intersection or close-range navigation between the current rescue unit's initial path and the planned paths of other rescue units. If two paths arrive at the same area at similar times, a course intersection risk is identified; if the distance between the two paths is less than a preset safe distance at similar times, a close-range navigation risk is identified. The command center's server generates a conflict detection result that includes both course intersection and close-range navigation risk points based on the detection results.

[0066] By using the planned paths of other rescue units as moving obstacles for spatiotemporal detection, the command center's server can detect potential interference between multiple rescue units in advance during the path planning stage, reducing the risk of flight path conflicts in concurrent rescue scenarios.

[0067] The command center's server adjusts the initial path based on the dynamically changing drag field and conflict detection results. During the adjustment process, the server avoids areas where the drag value exceeds a preset drag threshold, and avoids route intersection risk points and close-range navigation risk points identified in the conflict detection results, while maintaining path continuity and generating a collaboratively planned path.

[0068] To quantify path optimization, the following mathematical formula is introduced to evaluate path cost: ; in For path cost, This is the total path length. As environmental resistance weight, path point The environmental resistance value at that location, To avoid conflict weights, The coordinate vector of the current path point. For the first The path point coordinate vectors of other rescue units, For collision detection range parameters, For speed-affecting factors, path point Recommended speed at the location, This is a smoothing constant. Its range is (0,∞). The lower the cost, the better the path. Usually, 10 is used as the threshold, and a value below 10 indicates that the path is feasible.

[0069] By avoiding high-resistance areas, route intersection risk points, and close-range navigation risk points, the final collaborative planning path can simultaneously take into account environmental adaptability and the coordination of multiple rescue units.

[0070] Specifically, the command center's server will coordinate and plan the route and send it to the corresponding rescue unit. Simultaneously, it will send a location reporting frequency adjustment command to the target wristwatch, linked to the estimated arrival time of the corresponding rescue unit. The specific steps are as follows: The command center's server will send the generated collaborative planning path data packets to the smart terminals of the corresponding rescue units via the BeiDou downlink; The command center's server calculates dynamically updated estimated arrival times for each rescue unit based on the collaboratively planned routes; Based on the dynamically updated estimated arrival time, the command center's server generates a location reporting frequency adjustment instruction for the corresponding target wristwatch. The location reporting frequency adjustment instruction includes reporting frequency parameters that change over time. The command center's server sends the location reporting frequency adjustment command to the target wristwatch via BeiDou short message. After receiving the command, the target wristwatch adjusts its location reporting frequency accordingly.

[0071] It should be noted that the command center's server matches the collaboratively planned path according to the rescue unit's identity information, generating a corresponding collaboratively planned path data packet. This data packet includes the mission location, path nodes, path node order, expected direction of travel, and corresponding event ID. The command center's server then sends the collaboratively planned path data packet to the corresponding rescue unit's smart terminal via the BeiDou downlink. The rescue unit's smart terminal receives, displays, or stores the collaboratively planned path.

[0072] By distributing collaboratively planned routes to the smart terminals of the corresponding rescue units, the rescue units can execute rescue missions according to the routes generated by the command center's server, reducing information discrepancies caused by manual relaying.

[0073] The command center's server calculates the estimated arrival time of the rescue unit at the mission location based on the path length of the collaboratively planned route, the resistance values ​​corresponding to each path segment, and the current speed of the rescue unit. The rescue unit continuously uploads its current location during its journey, and the command center's server updates the remaining path length based on the rescue unit's real-time location and recalculates the estimated arrival time.

[0074] By dynamically updating the estimated arrival time, the command center's server can adjust subsequent control strategies based on the actual progress of the rescue units, avoiding delays caused by relying solely on the initial estimated time.

[0075] The command center's server generates a location reporting frequency adjustment instruction based on the remaining time corresponding to the estimated arrival time. This instruction includes the target wristwatch device number, frequency adjustment time, reporting frequency parameters, and event ID. When the remaining time corresponding to the estimated arrival time is longer, a lower location reporting frequency is used; conversely, when the remaining time corresponding to the estimated arrival time is shorter, a higher location reporting frequency is used.

[0076] To dynamically adjust the reporting frequency, the following mathematical formula is introduced: ; in For time Heart rate reporting frequency, The maximum frequency value, For scaling parameters, For growth rate, For estimated arrival time, Weighting for the impact of environmental change. The environmental change sensitivity coefficient This represents the rate of temperature change. Its range is (0, A+D], and its frequency increases as the arrival time approaches, adjusting to changes in the environment. Set to 10Hz. Set to 5Hz, the actual value is between 0.1Hz and 15Hz.

[0077] By adjusting the reporting frequency parameter according to the expected arrival time, the watch can increase the location update density when rescue is imminent and reduce the communication frequency when rescue is not imminent, thus balancing the needs of location updates and the watch's power consumption.

[0078] The command center's server sends a location reporting frequency adjustment command to the target wristwatch via BeiDou short message service. After receiving the command, the target wristwatch's main control chip parses the wristwatch's device number, frequency adjustment time, and reporting frequency parameters, and adjusts the location reporting timer according to the parameters, thereby changing the wristwatch's location reporting frequency.

[0079] By remotely sending location reporting frequency adjustment commands, the command center's server can control the information reporting rhythm of the wristwatches according to the rescue progress, thereby improving the coordination between the front-end wristwatches and the back-end rescue process.

[0080] Specifically, the command center's server monitors the rescue execution process and collects mission data after a successful rescue. This data is then used to optimize the computational model's parameters, completing a closed-loop self-evolution. The specific steps are as follows: The command center's server continuously tracks and records the actual navigation trajectory of the rescue units, compares the actual navigation trajectory with the collaboratively planned path, and calculates the path following deviation of the actual navigation trajectory relative to the collaboratively planned path. When a rescue unit reports a successful rescue signal through its terminal, the command center's server automatically tags the alarm event as successful and records the total response time from alarm to success. The command center's server stores the complete data packet for this mission in a structured manner. The complete data packet includes initial multidimensional situational data, rescue urgency values, path following deviations, and total response time. The command center's server inputs the complete data packet into the computational model to trigger incremental learning and fine-tuning of the model parameters, thereby completing closed-loop optimization based on actual rescue results.

[0081] It should be noted that during the rescue mission, the rescue unit's smart terminal continuously uploads its current location data to the command center's server. The command center's server records the rescue unit's location points in chronological order, forming the actual navigation trajectory. The command center's server matches the actual navigation trajectory with the issued collaboratively planned path, calculates the deviation of the actual navigation trajectory from the collaboratively planned path, and obtains the path following deviation. The path following deviation includes the average deviation, the maximum deviation, and the number of deviations.

[0082] By recording the actual navigation trajectory and calculating the path following deviation, the command center's server can quantitatively evaluate the execution of the collaboratively planned path during the actual rescue process, providing execution result data for subsequent model optimization.

[0083] Once the rescue unit completes the rescue, its smart terminal sends a rescue success signal to the command center's server. Upon receiving the signal, the command center's server marks the corresponding alarm event as completed and calculates the difference between the rescue success time and the alarm trigger time to obtain the total response time from alarm to success.

[0084] By recording the successful rescue signal and total response time, the system can obtain the actual completion result and response efficiency of this rescue mission, which is convenient for subsequent mission effectiveness evaluation.

[0085] The command center's server stores the complete data packet for this mission in a structured format. The complete data packet includes the multi-dimensional situational data initially uploaded by the wristwatch, the rescue urgency value calculated by the command center's server, the path-following deviations formed by the rescue units during the execution process, the total response time from alarm to success, and the rescue success tag.

[0086] By forming the above data into a complete data package, each completed rescue mission can serve as a data source for subsequent calculation model optimization.

[0087] The command center's server inputs the complete data packet into the calculation model, and incrementally learns and fine-tunes the parameters in the model. If the rescue urgency value corresponding to a certain type of alarm event is low but the actual total response time is long, or the path following deviation is large, the command center's server adjusts the relevant parameters so that subsequent similar alarm events can obtain outputs that more accurately reflect actual rescue results when calculating the rescue urgency value.

[0088] By using data from completed rescue missions to optimize the parameters of the calculation model, the model can continuously adjust the calculation process of the urgency of the rescue based on the actual rescue results, thus forming a data closed loop from alarm processing, task allocation, route planning, rescue execution to model optimization.

[0089] This embodiment also provides an emergency rescue dynamic collaborative system integrating a Beidou SOS wristwatch, including: The wristwatch includes a main control chip, a Beidou positioning chip, a temperature sensor, a barometric pressure sensor, a three-dimensional accelerometer, and a Beidou short message communication unit. When the wristwatch triggers an SOS alarm, the main control chip controls the Beidou positioning chip to obtain latitude and longitude coordinates, controls the temperature sensor, barometric pressure sensor, and three-dimensional accelerometer to obtain raw environmental and attitude data, and encapsulates the latitude and longitude coordinates and the raw environmental and attitude data into a multi-dimensional situational data frame. The BeiDou short message communication unit is used to upload multi-dimensional situational data frames to the command center server; The command center server is used to receive multi-dimensional situational data frames, parse them to obtain positioning data, environmental data and attitude data, and combine them with macro-oceanic meteorological data to calculate the urgency of rescue for alarm events. The command center server is also used to sort alarm events based on the urgency value of the rescue, send task invitations containing task location and urgency level to multiple rescue unit smart terminals, and receive the execution cost value fed back by each rescue unit smart terminal to form a preliminary task allocation plan. The command center server is also used to generate collaborative planning paths for corresponding rescue units based on the preliminary task allocation plan, combined with real-time ocean current data, wind field data, and other rescue unit planned paths; The intelligent terminal of the rescue unit is used to receive collaboratively planned routes and to send location data and rescue success signals back to the command center server during the rescue process. The command center server is also used to calculate the estimated arrival time of rescue units based on the collaboratively planned path, send location reporting frequency adjustment instructions to the target wristwatch, and optimize the parameters of the calculation model used to calculate the urgency of the rescue after the rescue is successful, using mission data.

[0090] This embodiment also provides a computer device applicable to the emergency rescue dynamic coordination method integrating a Beidou SOS wristwatch, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the emergency rescue dynamic coordination method integrating a Beidou SOS wristwatch as proposed in the above embodiment.

[0091] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0092] This embodiment also provides a storage medium storing a computer program. When executed by a processor, the program implements the emergency rescue dynamic coordination method for integrating a Beidou SOS wristwatch as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0093] In summary, this invention achieves dynamic collaboration in emergency rescue processes by constructing a processing flow encompassing wristwatch information collection, command center risk calculation, rescue unit task matching, collaborative path planning, and task data feedback optimization. When a wristwatch triggers an SOS alarm, it uploads multi-dimensional situational data including location, environmental, and attitude information, enabling the command center to calculate the urgency of the alarm event based on the on-site situation and macro-oceanic meteorological data, thus improving the efficiency of alarm event priority determination. Dynamic matching between rescue tasks and rescue units is achieved through task sorting, task invitation, and execution cost feedback based on the urgency value. Collaboratively planned paths that avoid high-resistance areas and path conflict risks are generated by incorporating real-time ocean current data, wind field data, and other rescue unit planned paths into the path planning process. The wristwatch's information reporting frequency is adjusted according to the estimated arrival time, ensuring the information reporting process aligns with the rescue progress. After a successful rescue, task data is collected and calculation model parameters are optimized, allowing the system to continuously improve the urgency calculation process based on completed rescue tasks, thereby enhancing the overall collaborative efficiency of emergency rescue.

[0094] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A dynamic collaborative emergency rescue method integrating a Beidou SOS wristwatch, characterized in that, Includes the following steps: When the wristwatch triggers an SOS alarm, it collects multi-dimensional situational data including location information and sensor data, and uploads the multi-dimensional situational data to the command center; The command center's server receives the multi-dimensional situational data and uses a calculation model to calculate the urgency of the rescue, outputting the urgency value of the rescue for the corresponding alarm event. Based on the rescue urgency value, the command center's server sorts the alarm events, sends task invitations containing task location and urgency level to multiple rescue units, and receives the execution cost value reported by each rescue unit to form a preliminary task allocation plan. Based on the preliminary task allocation scheme, the command center's server generates a collaborative planning path for each assigned rescue unit, taking into account real-time environmental resistance and the planned paths of other rescue units. The command center's server will send the collaboratively planned path to the corresponding rescue unit, and at the same time send a location reporting frequency adjustment command to the target wristwatch that is associated with the expected arrival time of the corresponding rescue unit; The command center's server monitors the rescue execution process and collects mission data after a successful rescue. The mission data is then used to optimize the parameters of the calculation model, completing a closed-loop self-evolution.

2. The emergency rescue dynamic coordination method integrating a Beidou SOS wristwatch as described in claim 1, characterized in that: When the wristwatch triggers an SOS alarm, it collects multi-dimensional situational data including location information and sensor data, and uploads the multi-dimensional situational data to the command center. The specific steps are as follows: The watch's main control chip simultaneously activates the Beidou positioning chip and the set of miniature environmental sensors to acquire latitude and longitude coordinates, as well as raw environmental and attitude data including temperature, air pressure, and three-dimensional acceleration. The main control chip verifies and encapsulates the latitude and longitude coordinates and the original environmental and attitude data to form a multi-dimensional situational data frame with a standard format. The multi-dimensional situational data frame is divided into a positioning data area, an environmental data area, and an attitude data area. The main control chip controls the BeiDou short message communication unit to call the BeiDou short message communication function and upload the multi-dimensional situational data frame as the primary sending object; The watch enters an alarm standby state, and its indicator light switches to a slow flashing mode to confirm that the multi-dimensional situational data frame has been successfully transmitted.

3. The emergency rescue dynamic coordination method for integrated Beidou SOS wristwatches as described in claim 2, characterized in that: The server in the command center receives the multi-dimensional situational data and uses a calculation model to calculate the urgency of the rescue, outputting the urgency value of the rescue corresponding to the alarm event. The specific steps are as follows: The command center's server parses and standardizes the received multi-dimensional situational data frames, separating out positioning data, environmental data, and attitude data, and assigns a unified timestamp and event ID to the positioning data, environmental data, and attitude data. The command center's server inputs the parsed standardized data and real-time acquired macro-oceanic meteorological data into the calculation model; The computational model identifies water-falling event tags or ship capsizing event tags based on the violent motion characteristics in the attitude data and the sudden changes in temperature data. The calculation model integrates the tags of the drowning incident or the capsizing incident, the severity of the weather, and the overall load of surrounding rescue resources, and outputs a quantitative value of the urgency of the rescue according to a preset weight calculation method.

4. The emergency rescue dynamic coordination method for integrated Beidou SOS wristwatches as described in claim 3, characterized in that: Based on the rescue urgency value, the command center's server sorts the alarm events, sends task invitations containing task location and urgency level to multiple rescue units, and receives execution cost values ​​from each rescue unit to form a preliminary task allocation plan. The specific steps are as follows: The command center's server sorts all alarm events according to their urgency level and generates a queue of tasks to be rescued. The command center's server broadcasts an invitation message containing the mission location and urgency level to all available rescue units based on the queue of missions awaiting rescue. The command center's server receives execution cost values ​​calculated based on the location, speed, and mission type of each rescue unit. The command center's server runs a many-to-many matching algorithm to match the rescue missions with the rescue units, aiming to minimize the total global execution cost, and outputs a preliminary mission allocation plan.

5. The emergency rescue dynamic coordination method for integrated Beidou SOS wristwatches as described in claim 4, characterized in that: Based on the preliminary task allocation scheme, the command center's server generates a collaborative planning path for each assigned rescue unit, taking into account real-time environmental resistance and the planned paths of other rescue units. The specific steps are as follows: The command center's server obtains the preliminary task allocation plan and initializes an initial path from the current location to the task point for each assigned rescue unit; The command center's server receives real-time ocean current data and wind field data, and quantifies the real-time ocean current data and wind field data into a dynamically changing resistance field, which is then overlaid on the electronic nautical chart. The command center's server performs collaborative path conflict detection, treating the planned paths of other rescue units as moving obstacles, detecting whether there are spatiotemporal risks of route intersection or close-range navigation risks, and generating conflict detection results that include route intersection risk points and close-range navigation risk points. Based on the dynamically changing resistance field and the conflict detection results, the command center's server replans a collaborative planning path for each rescue unit to avoid high-resistance areas, route intersection risk points, and close-range navigation risk points.

6. The emergency rescue dynamic coordination method for integrated Beidou SOS wristwatches as described in claim 5, characterized in that: The command center's server will coordinate and plan the route and send it to the corresponding rescue unit. Simultaneously, it will send a location reporting frequency adjustment command to the target wristwatch, which is associated with the estimated arrival time of the corresponding rescue unit. The specific steps are as follows: The command center's server will send the generated collaborative planning path data packets to the smart terminals of the corresponding rescue units via the BeiDou downlink; The command center's server calculates dynamically updated estimated arrival times for each rescue unit based on the collaboratively planned routes; Based on the dynamically updated estimated arrival time, the command center's server generates a location reporting frequency adjustment instruction for the corresponding target wristwatch. The location reporting frequency adjustment instruction includes reporting frequency parameters that change over time. The command center's server sends the location reporting frequency adjustment instruction to the target wristwatch via BeiDou short message. Upon receiving the instruction, the target wristwatch adjusts its location reporting frequency accordingly.

7. The emergency rescue dynamic coordination method for integrated Beidou SOS wristwatches as described in claim 6, characterized in that: The command center's server monitors the rescue execution process and collects mission data after a successful rescue. It then uses this mission data to optimize the parameters of the computational model, completing a closed-loop self-evolution. The specific steps are as follows: The command center's server continuously tracks and records the actual navigation trajectory of the rescue units, compares the actual navigation trajectory with the collaboratively planned path, and calculates the path following deviation of the actual navigation trajectory relative to the collaboratively planned path. When a rescue unit reports a successful rescue signal through its terminal, the command center's server automatically tags the alarm event as successful and records the total response time from alarm to success. The command center's server stores the complete data packet for this mission in a structured manner. The complete data packet includes initial multidimensional situational data, rescue urgency values, path following deviations, and total response time. The command center's server inputs the complete data packet into the computational model to trigger incremental learning and fine-tuning of the model parameters, thereby completing closed-loop optimization based on actual rescue results.

8. An emergency rescue dynamic collaborative system integrating a Beidou SOS wristwatch, characterized in that, This includes wristwatches, command center servers, and smart terminals for rescue units; The wristwatch includes a main control chip, a Beidou positioning chip, a temperature sensor, a barometric pressure sensor, a three-dimensional accelerometer, and a Beidou short message communication unit. The main control chip is used to control the Beidou positioning chip to obtain latitude and longitude coordinates, control the temperature sensor, barometric pressure sensor, and three-dimensional accelerometer to obtain raw environmental and attitude data when the wristwatch triggers an SOS alarm, and encapsulate the latitude and longitude coordinates and the raw environmental and attitude data into a multi-dimensional situational data frame. The Beidou short message communication unit is used to upload the multi-dimensional situational data frame to the command center server. The command center server is used to receive the multi-dimensional situational data frames, parse them to obtain positioning data, environmental data and attitude data, and combine them with macro-oceanic meteorological data to calculate the urgency of the rescue for the alarm event. The command center server is also used to sort alarm events based on the rescue urgency value, send task invitations containing task location and urgency level to multiple rescue unit smart terminals, and receive execution cost values ​​fed back by each rescue unit smart terminal to form a preliminary task allocation plan. The command center server is also used to generate a collaborative planning path for the corresponding rescue units based on the preliminary task allocation plan, combined with real-time ocean current data, wind field data, and the planned paths of other rescue units. The intelligent terminal of the rescue unit is used to receive the collaboratively planned path and to feed back the location data and rescue success signal during the rescue execution process to the command center server. The command center server is also used to calculate the estimated arrival time of the rescue unit based on the collaborative planning path, send a location reporting frequency adjustment instruction to the target wristwatch, and optimize the parameters of the calculation model used to calculate the rescue urgency value using mission data after the rescue is successful.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the emergency rescue dynamic coordination method of the integrated Beidou SOS wristwatch as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the emergency rescue dynamic coordination method of the integrated Beidou SOS wristwatch as described in any one of claims 1 to 7.

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