A method and system for wireless transmission of information on the wounded and sick for emergency rescue.

Abstract

This application provides a method and system for wireless transmission of patient information in emergency rescue. The method involves receiving basic information and real-time vital signs data from multiple on-site first aid devices to generate a summary of the patient's condition. Based on this summary, a priority dynamic adjustment algorithm is used to predict the temporal development trend. Geographic Information System (GIS) technology is employed to accurately analyze geographical location and medical resource distribution, generating a priority information packet. This priority information packet is then encrypted using a homomorphic encryption algorithm, and aggregation operations are performed. Adaptive network transmission technology is used to dynamically adjust the transmission strategy based on real-time network conditions, generating a secure transmission scheme. Based on this secure transmission scheme, a continuous monitoring mechanism is initiated to track changes in the patient's condition, generating a wireless transmission scheme for the patient's information. The technical solution provided in this application ensures efficient and accurate information transmission in emergency rescue, enhancing the overall effectiveness of emergency rescue efforts.

Description

Technical Field

[0001] This application relates to the field of emergency communication technology, and in particular to a method and system for wireless transmission of information about the wounded and sick in emergency rescue. Background Technology

[0002] With the continuous development of modern emergency rescue systems, information transmission and processing technologies are playing an increasingly important role in improving rescue efficiency and optimizing resource allocation. This is especially true in emergency medical rescue scenarios, where the rapid and accurate acquisition and transmission of vital sign data from the injured and sick is crucial for saving lives. In emergency rescue scenarios, on-site first aid equipment needs to be able to receive and integrate basic information and vital sign data of the injured and sick in real time, possess real-time monitoring capabilities, continuously track changes in the condition of the injured and sick, predict temporal trends through priority adjustments, and accurately analyze the distribution of medical resources.

[0003] Currently, many emergency rescue systems have adopted advanced technologies and methods to process information on the injured and sick. Basic information and vital signs data of the injured and sick are collected through on-site first aid equipment and transmitted to the command center via wireless networks. Some systems use static scoring models to conduct preliminary assessments of the injured and sick to determine the order of rescue. Some systems employ traditional encryption techniques to protect data privacy, but their ability to perform aggregation operations without decryption is limited.

[0004] While existing solutions meet the needs of emergency rescue to some extent, they still have some significant shortcomings. The data transmission speed and reliability of existing systems are low, especially in complex environments where information delays or loss may occur, affecting the timeliness and accuracy of rescue decisions and resulting in inefficient information transmission during emergency rescue. Static scoring models cannot flexibly respond to dynamic changes in the condition of the injured and sick, making it difficult to achieve precise priority adjustments and resource allocation. Although traditional encryption technologies ensure data privacy, their ability to perform necessary aggregation operations without decryption is insufficient, limiting the depth and breadth of data analysis and reducing data usability. Summary of the Invention

[0005] This application provides a method and system for wireless transmission of information about the wounded and sick in emergency rescue, in order to solve the problem of inefficient information transmission in emergency rescue in the prior art.

[0006] In a first aspect, embodiments of this application provide a method for wireless transmission of information on wounded and sick personnel for emergency rescue, comprising:

[0007] Through multiple on-site emergency medical devices, the system receives and integrates basic information and real-time vital signs data of the injured and sick, and generates a summary of the injured and sick's condition.

[0008] Based on the patient status summary, a priority dynamic adjustment algorithm is used to analyze the frequency and severity of changes in the patients' vital signs, predict the time-series development trend, and use geographic information system technology to accurately analyze the geographical location and distribution of medical resources to generate priority information packages.

[0009] Based on the priority information packet, homomorphic encryption algorithm is used for encryption processing, allowing aggregation operation to be performed without decryption, ensuring data privacy and availability. Adaptive network transmission technology is adopted to dynamically adjust the transmission strategy according to real-time network conditions and generate a secure transmission scheme.

[0010] Based on the aforementioned secure transmission scheme, the receiving end performs decryption processing, initiates a continuous monitoring mechanism to track changes in the status of the wounded and sick, and generates a wireless transmission scheme for the wounded and sick information.

[0011] Optionally, based on the patient's condition summary, a priority dynamic adjustment algorithm is used to analyze the frequency and severity of changes in the patient's vital signs, predict the temporal development trend, and geographic information system technology is employed to accurately analyze geographical location and medical resource distribution, generating a priority information package, including:

[0012] Based on the patient status summary, the patient's vital signs data and environmental background information are comprehensively evaluated and processed to generate a preliminary priority score.

[0013] Based on the preliminary priority score, the priority dynamic adjustment algorithm is used to combine the historical data and current status of the wounded and sick to analyze the frequency and severity of changes in the vital signs of the wounded and sick in detail, and generate an optimized priority score.

[0014] Based on the optimized priority score, geographic information system technology is used to accurately process the location information of the wounded and sick, analyze the distribution of surrounding medical resources, determine the optimal rescue route, and generate a geographic location analysis report.

[0015] Based on the geographic location analysis report, the optimization priority score is deeply integrated to generate a priority information package.

[0016] Optionally, based on the preliminary priority score, a priority dynamic adjustment algorithm is used, combining historical data and current status of the wounded and sick, to analyze in detail the frequency and severity of changes in the wounded and sick's vital signs, and generate an optimized priority score, including:

[0017] Based on the preliminary priority score, the historical vital signs data of the wounded and sick are comprehensively compared with their current status to identify abnormal changes and generate a status difference report.

[0018] Based on the aforementioned status difference report, a priority dynamic adjustment algorithm is used to quantify the frequency of changes in the vital signs of the injured and sick within different time periods. Different dynamic weight factors are assigned according to the severity of the changes to reflect the trend of disease development and generate an assessment of the frequency and severity of changes.

[0019] Based on the aforementioned frequency of change and severity assessment, combined with the patient's historical priority score and the aforementioned preliminary priority score, the overall urgency level is comprehensively reassessed to generate a comprehensive urgency assessment.

[0020] Based on the comprehensive urgency assessment, parameters are updated regularly to adapt to changing realities, and all assessment results are integrated to generate an optimized priority score.

[0021] Optionally, based on the optimized priority score, geographic information system (GIS) technology is used to accurately process the location information of the wounded and sick, analyze the distribution of surrounding medical resources, determine the optimal rescue route, and generate a geographic location analysis report, including:

[0022] Based on the optimized priority score, the location information of the wounded and sick is accurately collected and processed to obtain the current latitude and longitude coordinates of the wounded and sick, and combined with high-precision map data to generate accurate positioning data;

[0023] Based on the precise positioning data, geographic information system technology is used to conduct a detailed analysis of the geographical environment of the location of the wounded and sick, and a geographical environment assessment is generated by comprehensively considering the topography and road network.

[0024] Based on the geographical environment assessment and the optimization priority score, the distribution of surrounding medical resources is analyzed, the service capacity and current load of nearby medical institutions are assessed, and a medical resource distribution map is generated.

[0025] Based on the aforementioned medical resource distribution map, the path planning method is used to simulate traffic flow changes over different time periods, predict potential traffic bottlenecks, and generate a geographic location analysis report.

[0026] Optionally, based on the priority information packet, homomorphic encryption is used for encryption, allowing aggregation operations to be performed without decryption, ensuring data privacy and availability. Adaptive network transmission technology is employed to dynamically adjust the transmission strategy according to real-time network conditions, generating a secure transmission scheme, including:

[0027] Based on the priority information package, a comprehensive assessment of the patient's information is conducted, and potentially missing data is supplemented through verification to ensure the accuracy and completeness of the information, thereby generating an optimized information package.

[0028] Based on the optimized information packet, a homomorphic encryption algorithm is used to ensure that the data is kept encrypted during transmission and storage, allowing necessary aggregation operations to be performed without decryption, thus ensuring data privacy and availability, and generating an encrypted information packet.

[0029] Based on the encrypted information packet, adaptive network transmission technology is used to monitor network bandwidth and packet loss rate parameters in real time, analyze network connection quality and stability, and generate a network status assessment report.

[0030] Based on the network condition assessment report and the characteristics of the encrypted information packets, data fragmentation is performed, a retransmission mechanism is constructed to ensure the reliability and integrity of information transmission, and a secure transmission scheme is generated.

[0031] Optionally, based on the optimized information packet, a homomorphic encryption algorithm is used to ensure that the data remains encrypted during transmission and storage, allowing necessary aggregation operations to be performed without decryption, thus guaranteeing data privacy and availability, and generating an encrypted information packet, including:

[0032] Based on the optimized information package, a comprehensive check and verification of the patient's information is performed. A verification information package is generated through data integrity verification and logical consistency check.

[0033] Based on the verification information packet, homomorphic encryption algorithm is used for encryption to ensure that the encryption state is maintained during data transmission and storage. An appropriate key length and encryption mode are selected to support the execution of necessary aggregation operations without decryption, and a preliminary encrypted information packet is generated.

[0034] Based on the initial encrypted information packet, the encryption strength and performance are evaluated. By simulating different scenario computing requirements, the computing power and response time are tested, and a performance optimization information packet is generated.

[0035] Based on the performance optimization information package, metadata tags are added according to actual application requirements to facilitate subsequent decryption processing and generate an encrypted information package.

[0036] Optionally, based on the secure transmission scheme, the receiving end performs decryption processing, initiates a continuous monitoring mechanism to track changes in the status of the wounded and sick, and generates a wireless transmission scheme for wounded and sick information, including:

[0037] Based on the aforementioned secure transmission scheme, the encrypted information packet is decrypted at the receiving end, and the same key as the sending end is used to reverse the homomorphic encryption algorithm to generate a decrypted information packet.

[0038] Based on the decrypted information packet, a continuous monitoring mechanism is activated, and intelligent sensors and monitoring equipment are used to track changes in the vital signs data and geographical location information of the wounded and sick in real time, and generate a real-time status update report.

[0039] Based on the real-time status update report, the urgency level is reassessed according to the frequency and severity of changes in the vital signs of the wounded and sick, combined with geographical environmental factors, and a status change assessment report is generated.

[0040] Based on the status change assessment report and the latest medical resource distribution, an additional emergency resource dispatch backup plan is configured, and a wireless transmission plan for patient information is generated.

[0041] Secondly, embodiments of this application provide a wireless transmission system for patient information in emergency rescue, comprising:

[0042] The receiving module is used to receive and integrate basic information and real-time vital signs data of the injured and sick through multiple on-site emergency medical devices, and generate a summary of the injured and sick's status.

[0043] The prediction module is used to analyze the frequency and severity of changes in the vital signs of the wounded and sick based on the summary of the wounded and sick, using a priority dynamic adjustment algorithm to predict the time-series development trend, and using geographic information system technology to accurately analyze the geographical location and distribution of medical resources to generate priority information packages.

[0044] The encryption module is used to encrypt the priority information packet using a homomorphic encryption algorithm, allowing aggregation operations to be performed without decryption, ensuring data privacy and availability, and adopting adaptive network transmission technology to dynamically adjust the transmission strategy according to real-time network conditions to generate a secure transmission scheme.

[0045] The decryption module is used to perform decryption processing at the receiving end based on the secure transmission scheme, start a continuous monitoring mechanism to track changes in the status of the wounded and sick, and generate a wireless transmission scheme for the wounded and sick information.

[0046] Thirdly, embodiments of this application provide a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement a wireless transmission method for information on the wounded and sick in emergency rescue as described in the first aspect.

[0047] Fourthly, embodiments of this application provide a computer storage medium storing a computer program, which, when executed by a computer, implements a method for wireless transmission of information on the wounded and sick for emergency rescue as described in the first aspect.

[0048] In this embodiment, multiple on-site emergency medical devices receive and integrate basic information and real-time vital sign data of the injured or sick to generate a summary of the injured or sick's condition. Based on this summary, a priority dynamic adjustment algorithm is used to analyze the frequency and severity of changes in the injured or sick's vital signs in detail, predict the temporal development trend, and geographic information system technology is used to accurately analyze the geographical location and distribution of medical resources to generate a priority information packet. Based on the priority information packet, a homomorphic encryption algorithm is used for encryption processing, allowing aggregation operations to be performed without decryption, ensuring data privacy and availability. Adaptive network transmission technology is used to dynamically adjust the transmission strategy according to the real-time network conditions to generate a secure transmission scheme. Based on the secure transmission scheme, the receiving end performs decryption processing and initiates a continuous monitoring mechanism to track changes in the injured or sick's condition, generating a wireless transmission scheme for the injured or sick's information. By collecting and integrating information on the wounded and sick through multiple devices, the comprehensiveness and accuracy of the data were ensured. Based on the patient status summary, a priority dynamic adjustment algorithm was used to analyze the frequency and severity of changes in vital signs and predict time-series development trends, which helps optimize rescue decisions and improve rescue efficiency. Geographic Information System (GIS) technology was used to accurately analyze geographical locations and the distribution of medical resources, generating priority information packages to ensure the selection of the optimal rescue route and improve resource utilization efficiency. Homomorphic encryption algorithms were used for encryption processing, allowing aggregation operations to be performed without decryption, ensuring data privacy and availability. Adaptive network transmission technology was used to dynamically adjust the transmission strategy according to real-time network conditions, generating a secure transmission scheme to ensure the security and reliability of information transmission. Decryption processing at the receiving end and the activation of a continuous monitoring mechanism to track changes in the patient status ensured the timeliness and effectiveness of the rescue operation.

[0049] Furthermore, a comprehensive assessment and processing of the vital signs data of the wounded and sick, along with environmental background information, was conducted to generate preliminary priority scores, ensuring the scientific rigor and rationality of the scores. A dynamic priority adjustment algorithm was employed, combining historical data and the current status of the wounded and sick, to meticulously analyze the frequency and severity of changes in vital signs, generating optimized priority scores and improving the accuracy and timeliness of the scoring. Geographic Information System (GIS) technology was used to precisely process the location information of the wounded and sick, analyze the distribution of surrounding medical resources, and determine the optimal rescue route, ensuring the optimality and efficiency of the rescue route selection. The optimized priority scores were deeply integrated to generate priority information packages, ensuring the completeness and authority of the information packages and providing a reliable basis for subsequent rescue operations.

[0050] Furthermore, a comprehensive assessment of the wounded and sick personnel's information was conducted. By verifying and supplementing potentially missing data, the accuracy and completeness of the information were ensured, generating optimized information packets and laying a solid foundation for subsequent encryption processing. Homomorphic encryption algorithms were employed to ensure encryption during data transmission and storage, allowing necessary aggregation operations without decryption, thus guaranteeing data privacy and availability and improving data security. Adaptive network transmission technology was used to monitor network bandwidth and packet loss rate parameters in real time, analyze network connection quality and stability, and generate network condition assessment reports, ensuring the scientific and targeted nature of the transmission strategy. Based on the network condition assessment report and the characteristics of the encrypted information packets, data fragmentation was performed, and a retransmission mechanism was constructed to ensure the reliability and integrity of information transmission, improving overall transmission efficiency and stability. The final secure transmission scheme not only included specific transmission paths and strategies but also stipulated emergency response measures to address potential emergencies, ensuring the continuity and reliability of information transmission and providing strong technical support for emergency rescue.

[0051] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 A flowchart illustrating a method for wireless transmission of patient information in emergency rescue, provided as an embodiment of this application;

[0054] Figure 2 A schematic diagram of the structure of a wireless transmission system for patient information in emergency rescue provided in an embodiment of this application;

[0055] Figure 3 This is a schematic diagram of the structure of a computing device provided in an embodiment of this application. Detailed Implementation

[0056] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0057] In some of the processes described in the specification, claims, and accompanying drawings of this application, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a chronological order, nor do they limit "first" and "second" to different types.

[0058] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0059] Figure 1 This application provides a flowchart of a method for wireless transmission of information about the wounded and sick in emergency rescue, as illustrated in the embodiments of this application. Figure 1 As shown, the method includes:

[0060] 101. Through multiple on-site emergency medical devices, receive and integrate basic information and real-time vital signs data of the injured and sick, and generate a summary of the injured and sick's condition;

[0061] In this step, basic information includes, but is not limited to, static data such as name, age, gender, and medical history. This data is used to comprehensively describe the identity and background of the injured or sick person and their personal medical history, ensuring that rescuers understand the overall situation of the injured or sick person.

[0062] Real-time vital signs data includes dynamic parameters such as heart rate, blood pressure, blood oxygen saturation, and body temperature, reflecting the immediate health status of the injured or sick. This data is used to assess the current physical function and potential risks of the injured or sick.

[0063] On-site emergency equipment can be portable medical monitoring instruments, such as smart bracelets, portable electrocardiographs, and blood glucose meters. These devices can continuously collect and upload the vital signs data of the injured and sick, ensuring the real-time nature and accuracy of the data.

[0064] The casualty status summary is a report generated after summarizing and preliminarily analyzing all collected data. This summary not only includes the latest vital signs data, but also historical trend analysis, helping rescuers quickly understand the overall health status of the casualties and providing a basis for subsequent treatment.

[0065] In this embodiment, assuming an earthquake rescue site, firstly, on-site emergency personnel use portable medical monitoring devices (such as smart bracelets or portable electrocardiographs) to collect vital sign data of the injured; secondly, these devices connect to a central processing unit via Bluetooth or Wi-Fi to upload the data to a cloud server; thirdly, the server uses big data analytics to clean, deduplicate, and integrate the data from multiple devices to ensure data consistency and accuracy; finally, the system generates a summary of the injured's condition, which includes not only the latest vital sign data but also historical trend analysis, helping rescue personnel quickly understand the overall situation of the injured.

[0066] 102. Based on the aforementioned summary of the wounded and sick, a priority dynamic adjustment algorithm is used to analyze the frequency and severity of changes in the wounded and sick's vital signs in detail, predict the temporal development trend, and use geographic information system technology to accurately analyze the geographical location and distribution of medical resources to generate a priority information package.

[0067] In this step, the priority dynamic adjustment algorithm is a mathematical model that can assess the development trend of the patient's condition based on the patient's historical data and current status, and dynamically adjust their rescue priority score. This algorithm ensures that rescue resources can be optimally allocated according to actual needs.

[0068] The frequency of changes in vital signs refers to the number or rate at which vital sign parameters (such as heart rate, blood pressure, blood oxygen saturation, body temperature, etc.) of an injured or sick person change within a specific time period.

[0069] Time series trend prediction uses time series analysis to predict changes in the vital signs of the wounded and sick over a future period. This prediction helps to prepare response measures in advance and improve rescue efficiency.

[0070] Geographic Information System (GIS) technology is used to accurately analyze the geographical location of the wounded and sick and the distribution of surrounding medical resources, determine the optimal rescue route, and provide a scientific basis for rescue operations by combining map data and spatial analysis functions.

[0071] The priority information package integrates the above analysis results to provide guidance for rescue operations. This package not only includes priority scores for the injured and sick, but also provides detailed rescue route suggestions to ensure the efficient use of rescue resources.

[0072] In this embodiment, assuming a traffic accident rescue, firstly, the system uses a machine learning model to predict the future trend of the patient's condition based on the vital signs data in the patient's status summary; secondly, it dynamically adjusts the patient's rescue priority score by combining the patient's historical medical records and current status; thirdly, the geographic information system analyzes the location of the patient and the distribution of surrounding medical resources such as hospitals and emergency stations to determine the optimal rescue route; finally, the system generates a priority information package, which not only includes the patient's priority score but also provides detailed rescue route suggestions to guide the dispatching of emergency vehicles and medical personnel.

[0073] Optionally, step 102, based on the patient's status summary, employs a priority dynamic adjustment algorithm to meticulously analyze the frequency and severity of changes in the patient's vital signs, predicts temporal development trends, and uses geographic information system (GIS) technology to accurately analyze geographical location and medical resource distribution to generate a priority information package. This includes: based on the patient's status summary, comprehensively evaluating and processing the patient's vital sign data and environmental background information to generate a preliminary priority score; based on the preliminary priority score, using a priority dynamic adjustment algorithm, combined with the patient's historical data and current status, meticulously analyzing the frequency and severity of changes in the patient's vital signs to generate an optimized priority score; based on the optimized priority score, using GIS technology to precisely process the patient's location information, analyze the distribution of surrounding medical resources to determine the optimal rescue route, and generate a geographical location analysis report; and based on the geographical location analysis report, deeply integrating the optimized priority score to generate a priority information package.

[0074] In this step, vital signs data include, but are not limited to, dynamic parameters such as heart rate, blood pressure, blood oxygen saturation, and body temperature. These data are used to assess the patient's current physical function and potential risks.

[0075] Environmental background information includes geographical location, weather conditions, and infrastructure at the accident site. This information helps to understand the impact of external factors on the injured and sick, ensuring more comprehensive rescue decisions.

[0076] The preliminary priority score is an initial score generated based on the above comprehensive assessment results. This score not only considers the frequency and severity of changes in the vital signs of the injured and sick, but also the influence of environmental background information, providing a basis for subsequent dynamic adjustments.

[0077] The optimized priority scoring is based on the initial priority scoring. It generates a more accurate score by further analyzing the historical data and current status of the injured and sick, especially the frequency and severity of changes in vital signs, so as to better guide the allocation of rescue resources.

[0078] The geolocation analysis report is a detailed report generated based on geographic information system technology. It includes the specific location information of the injured and sick, as well as the distribution of surrounding medical resources, to help determine the optimal rescue route and improve rescue efficiency.

[0079] The optimal rescue route refers to the route selected through geographic information system (GIS) technology analysis, which is the shortest in time, has the fewest obstacles, and is the safest, ensuring that emergency vehicles and medical personnel can quickly reach the location of the injured and sick to provide timely assistance.

[0080] First, a comprehensive assessment is conducted based on the vital signs data and environmental background information in the patient's status summary to generate a preliminary priority score. Second, a dynamic priority adjustment algorithm is used, combining historical data and current status of the patients, to meticulously analyze the frequency and severity of changes in vital signs and generate an optimized priority score. Third, geographic information system (GIS) technology is employed to precisely process the location information of the patients, analyze the distribution of surrounding medical resources, determine the optimal rescue route, and generate a geographic location analysis report. Finally, the optimized priority score is deeply integrated to generate a priority information package.

[0081] Optionally, the step of using a dynamic priority adjustment algorithm, combined with historical data and current status of the injured or sick, to analyze the frequency and severity of changes in vital signs and generate an optimized priority score based on the preliminary priority score includes: comprehensively comparing the historical vital sign data and current status of the injured or sick based on the preliminary priority score, identifying abnormal changes, and generating a status difference report; using the dynamic priority adjustment algorithm based on the status difference report to quantify the frequency of changes in vital signs of the injured or sick within different time periods, assigning different dynamic weight factors according to the severity of the changes to reflect the trend of disease development, and generating an assessment of change frequency and severity; based on the assessment of change frequency and severity, combining the historical priority score and the preliminary priority score of the injured or sick to comprehensively reassess the overall urgency level and generate a comprehensive urgency assessment; and based on the comprehensive urgency assessment, periodically updating parameters to adapt to changing actual situations, integrating all assessment results, and generating an optimized priority score.

[0082] The process, based on the optimized priority score, employs Geographic Information System (GIS) technology to precisely process the location information of the wounded and sick, analyze the distribution of surrounding medical resources, determine the optimal rescue route, and generate a geographic location analysis report. This includes: precisely collecting and processing the location information of the wounded and sick based on the optimized priority score to obtain their current latitude and longitude coordinates, and combining this with high-precision map data to generate precise positioning data; based on the precise positioning data, using GIS technology to conduct a detailed analysis of the geographic environment of the wounded and sick's location, comprehensively considering topography and road networks to generate a geographic environment assessment; based on the geographic environment assessment, combined with the optimized priority score, analyzing the distribution of surrounding medical resources, assessing the service capacity and current load of nearby medical institutions, and generating a medical resource distribution map; and based on the medical resource distribution map, using path planning methods to simulate traffic flow changes over different time periods, predicting potential traffic bottlenecks, and generating a geographic location analysis report.

[0083] In this step, the status difference report is generated based on the preliminary priority score and a comprehensive comparison of the patient's historical vital signs data with the current status. It is used to identify abnormal changes. This report records in detail the changes in the patient's vital signs at different time points, helping to identify trends of deterioration or improvement in the condition.

[0084] The frequency of changes in vital signs over different time periods refers to the trend of disease progression obtained by analyzing the rate of change of vital signs of the injured or sick over different time periods. Different dynamic weight factors are assigned according to the severity of the changes to reflect the trend of disease progression and ensure that the scoring can dynamically adapt to the actual situation.

[0085] The comprehensive urgency assessment combines the patient's historical priority score with the initial priority score to fully reassess the overall urgency level. This assessment not only considers the frequency and severity of current vital sign changes but also incorporates the patient's historical priority score to ensure more accurate and comprehensive scoring results.

[0086] Precise positioning data is obtained by accurately collecting and processing the location information of the wounded and sick, including their current latitude and longitude coordinates. This data is combined with high-precision maps to generate precise positioning data, ensuring that rescuers can accurately locate the wounded and sick.

[0087] High-precision map data refers to map data with high resolution and detailed geographic information. It typically includes precise road networks, building outlines, topography, and other information. This type of data can provide sub-meter or even centimeter-level accuracy, ensuring more accurate and reliable rescue route planning.

[0088] A geographical assessment is a detailed analysis of the geographical environment of the location of the injured or sick, taking into account the topography and road network. This assessment helps determine the optimal rescue route and avoid potential traffic obstacles and delays.

[0089] The medical resource distribution map is a map generated by analyzing the distribution of surrounding medical resources based on geographic information system technology. It assesses the service capacity and current load of nearby medical institutions to ensure that rescue operations can make efficient use of existing resources.

[0090] In this embodiment, firstly, based on the preliminary priority score, the historical vital sign data and current status of the injured or sick are comprehensively compared and processed to identify abnormal changes. A dynamic priority adjustment algorithm is then used to quantify the frequency of vital sign changes in different time periods, assigning different dynamic weight factors according to the severity of the changes to reflect the trend of the illness and generating an assessment of change frequency and severity. Secondly, based on the change frequency and severity assessment, combined with the historical and preliminary priority scores of the injured or sick, the overall urgency level is comprehensively reassessed. Parameters are periodically updated to adapt to changing realities, and all assessment results are integrated to generate an optimized priority score. Thirdly, the location information of the injured or sick is accurately collected and processed to obtain their current latitude and longitude coordinates. Combined with high-precision map data and using geographic information system (GIS) technology, a detailed analysis of the geographical environment of the injured or sick's location is conducted, comprehensively considering topography and road networks to generate a geographical environment assessment. Finally, based on the geographical environment assessment and combined with the optimized priority score, the distribution of surrounding medical resources is analyzed, the service capacity and current load of nearby medical institutions are assessed, and a path planning method is used to simulate traffic flow changes in different time periods, predict potential traffic bottlenecks, and generate a geographical location analysis report.

[0091] Assuming a traffic accident rescue scene in a mountainous area, the process is as follows: First, based on a preliminary priority score, the historical vital signs data of the injured person are comprehensively compared with their current status to identify abnormal changes. A dynamic priority adjustment algorithm is then used to quantify the frequency of vital sign changes over different time periods, assigning different dynamic weight factors based on the severity of the changes to reflect the trend of the condition and generate an assessment of change frequency and severity. Second, based on the change frequency and severity assessment, combined with the historical and preliminary priority scores, the overall urgency level is comprehensively reassessed. Parameters are periodically updated to adapt to changing realities, and all assessment results are integrated. Third, the location information of the injured person is accurately collected and processed to obtain their current latitude and longitude coordinates. Combined with high-precision map data and using Geographic Information System (GIS) technology, a detailed analysis of the geographical environment of the injured person's location is conducted, comprehensively considering topography and road networks to generate a geographical environment assessment. Finally, based on the geographical environment assessment and optimized priority scores, the distribution of surrounding medical resources is analyzed, the service capacity of nearby medical institutions is assessed, and traffic flow changes over different time periods are simulated using path planning methods to generate a geographical location analysis report.

[0092] This application addresses the issue that existing emergency rescue systems suffer from inaccurate resource allocation and inefficient rescue operations due to a lack of dynamic assessment of the frequency and severity of changes in the vital signs of the injured or sick. Traditional methods often rely on static priority scoring, which fails to reflect the dynamic changes in the patients' conditions in a timely manner, thus affecting the scientific rigor and accuracy of rescue decisions. Therefore, this invention proposes a further alternative solution that aims to generate an assessment of the frequency and severity of changes by quantifying the frequency of changes in the vital signs of the injured or sick over different time periods and assigning different dynamic weighting factors based on the severity of the changes to reflect the trend of disease progression.

[0093] Optionally, based on the aforementioned status difference report, a priority dynamic adjustment algorithm is used to quantify the frequency of changes in the vital signs of the injured or sick within different time periods. Different dynamic weighting factors are assigned according to the severity of the changes to reflect the trend of disease progression, generating an assessment of the frequency and severity of changes, including:

[0094] Based on the aforementioned state difference report, time series analysis is used to identify time points of abnormal fluctuations and significant changes.

[0095] Pay attention to indicators that predict disease deterioration, apply smoothing filters to reduce noise interference, and quantify the changes between each measurement using a difference method to generate the frequency of vital signs changes;

[0096] The frequency of changes in vital signs can be calculated using the following formula:

[0097]

[0098] Where F(t) is the frequency of vital sign changes at time t; w i x is the initial weighting factor for the i-th trait parameter; i (t) represents the value of the i-th characteristic parameter at time t; x i (0) represents the initial value of the i-th vital sign parameter; σ is the standard deviation used to measure the degree of change; i is the index of the vital sign parameter, from 1 to n; n is the number of vital sign parameters; η is the time influence coefficient; T is the total time span; ρ is the time nonlinearity exponent; t is the time variable, representing the time from the start of monitoring to the current moment;

[0099] Based on the frequency of changes in the vital signs, a dynamic weighting factor is introduced and dynamically adjusted according to the frequency and severity of changes in each vital sign parameter. A sine function is used to capture periodic fluctuations in the condition to assess the non-linear development trend of the condition and generate a disease development trend index.

[0100] The disease progression trend indicator can be calculated using the following formula:

[0101]

[0102] Where D(t) is an indicator of the disease progression trend at time t; w i F(t) represents the dynamic weighting factor of the i-th physical symptom parameter at time t, which is adjusted over time to reflect disease progression; α is the logarithmic amplification factor, used to emphasize subtle but persistent changes; β is the amplitude coefficient of the sine function, used to simulate periodic disease fluctuations; γ is the periodic parameter of the sine function, used to adjust the fluctuation frequency; λ is the enhancement coefficient; δ is the enhancement nonlinearity exponent; F(t) is the frequency of physical symptom changes at time t; F max τ represents the maximum frequency of changes in vital signs across all time periods; i represents the index of the vital sign parameter, from 1 to n; n represents the number of vital sign parameters; t represents the time variable, indicating the time from the start of monitoring to the current moment; and T represents the total time span.

[0103] Based on the aforementioned disease progression trend indicators, combined with the latest medical resource distribution and rescue priority scores, and taking into account external factors, the system predicts possible future trends and generates an assessment of the frequency and severity of these changes.

[0104] This method aims to identify abnormal fluctuations and significant changes in time points using time series analysis, generate the frequency of vital sign changes by quantifying the changes between each measurement, capture periodic fluctuations in the condition using a sine function, assess nonlinear development trends, and finally generate a comprehensive assessment report. These steps work together to ensure the comprehensiveness and accuracy of the assessment results and solve the problems existing in the prior art.

[0105] In the frequency of changes in vital signs, the item of severity of changes in vital signs... This section measures the drastic change in each vital sign parameter. Using an exponential decay function, it effectively captures significant changes in vital signs parameters over a short period while reducing the influence of long-term steady-state conditions, making the assessment results more sensitive and accurate. Time-related error correction term: The influence of time on changes in vital signs is considered. This correction term gradually increases as the monitoring time extends, reflecting the importance of time in disease progression. This factor ensures the validity of long-term monitoring data and avoids the excessive influence of short-term fluctuations on the overall assessment results.

[0106] Among them, w i Based on historical data and expert experience; x i (t) and x i (0) Read directly from real-time monitoring equipment; σ is calculated from the standard deviation of historical data; η and ρ are determined through experiments and simulations; T is the time length from the start to the end of monitoring.

[0107] In the indicators of disease progression trend, the term amplifying slight changes (α·ln(F(t)+1)) emphasizes slight but persistent changes. Through logarithmic function processing, it highlights vital signs and parameters that, while showing small individual changes, have a significant cumulative effect, resulting in a more detailed and comprehensive assessment. The term capturing periodic fluctuations... Simulating periodic fluctuations in patient condition, a sine function is used to capture potential periodic patterns, such as the diurnal rhythm of respiratory rate or heart rate, increasing the flexibility and adaptability of the evaluation model; nonlinear enhancement terms... Enhancing nonlinear characteristics and taking into account temporal dispersion, this term captures the complexity and uncertainty of disease progression through nonlinear exponents and Gaussian distribution functions, providing a more accurate assessment, especially in cases of rapid disease changes.

[0108] Among them, w i (t) is a weighting factor dynamically adjusted based on the frequency of changes in vital signs; α, β, γ, λ, δ, and τ are determined through experiments and simulations; F(t) is calculated from indicators of disease progression trends; F max Determined by the frequency of maximum changes in vital signs across all time periods; T is the length of time from the start to the end of monitoring.

[0109] Suppose a typhoon disaster relief site in a coastal area, a hospital emergency center needs to dynamically assess the frequency and severity of changes in the vital signs of each injured person to ensure efficient and accurate resource allocation. Assume a patient has three vital sign parameters: heart rate x1, blood pressure x2, and blood oxygen saturation x3, with initial weighting factors w1 = 0.5, w2 = 0.3, and w3 = 0.2, respectively. The monitoring time is 2 hours (T = 7200 seconds), the standard deviation σ = 4, the time influence coefficient η = 0.9, and the time nonlinearity index ρ = 0.6. Initial heart rate x1(0) = 80 beats / minute; initial blood pressure x2(0) = 120 / 80 mmHg; initial blood oxygen saturation x3(0) = 98%; real-time heart rate x1(t) = 90 beats / minute; real-time blood pressure x2(t) = 130 / 90 mmHg; real-time blood oxygen saturation x3(t) = 95%.

[0110]

[0111] Assuming a logarithmic amplification factor α = 0.85, a sinusoidal function amplitude factor β = 0.4, a period parameter γ = 0.8, an enhancement factor λ = 1.1, an enhancement nonlinearity exponent δ = 0.7, a time dispersion parameter τ = 1200, and a maximum symptom variation frequency F... max =1.2; Real-time dynamic weighting factors w1(t) = 0.6, w2(t) = 0.3, w3(t) = 0.1;

[0112]

[0113] Assuming a threshold of 1.2, the calculated result of 1.35 is greater than this threshold, indicating that the patient's condition is rapidly deteriorating and requires immediate further emergency treatment. This is because a higher disease progression indicator reflects a higher frequency and severity of changes in the patient's vital signs, suggesting a risk of a rapid deterioration in their health. Through these steps, accurate assessment and prioritization of the patient's resource needs are ensured, improving the scientific rigor and reliability of treatment decisions, thereby enhancing the accuracy and response speed of the entire health monitoring system.

[0114] 103. Based on the priority information packet, homomorphic encryption algorithm is used for encryption processing, allowing aggregation operation to be performed without decryption, ensuring data privacy and availability, and adaptive network transmission technology is adopted to dynamically adjust the transmission strategy according to the real-time network conditions to generate a secure transmission scheme.

[0115] Homomorphic encryption is an encryption method that allows aggregation operations, such as summation and average calculation, to be performed without decryption. This ensures a balance between data privacy and availability, keeping data encrypted during transmission while still allowing necessary calculations and analysis without decryption.

[0116] Aggregation operations refer to the process of combining multiple data points to generate one or more summary results. In the context of homomorphic encryption, this operation can be performed without decrypting the data, ensuring data privacy while maintaining its availability.

[0117] Adaptive network transmission technology dynamically adjusts transmission strategies based on real-time network conditions to cope with different network environments. This technology automatically selects the optimal transmission path and protocol by monitoring parameters such as network bandwidth and packet loss rate, ensuring the stability and efficiency of data transmission.

[0118] Real-time network status refers to various performance indicators of the current network environment, including but not limited to bandwidth, latency, packet loss rate, and network connection stability. These indicators reflect the network's ability and efficiency in transmitting data.

[0119] The secure transmission scheme includes selecting the optimal transmission path, protocol, and emergency response measures to ensure the stability and efficiency of data transmission. The resulting secure transmission scheme ensures the security and integrity of data during transmission, preventing information leakage or loss.

[0120] In this embodiment, assuming a rescue operation in a remote mountainous area, firstly, the system applies homomorphic encryption to sensitive data in priority information packets to ensure data security during transmission; secondly, the system dynamically adjusts the transmission strategy based on real-time network conditions, selecting the optimal transmission path and protocol; thirdly, the data remains encrypted during transmission, but the receiving end can perform aggregation operations, such as calculating averages or summations, without decryption; finally, the system generates a secure transmission scheme, which not only includes specific transmission paths and strategies but also specifies emergency response measures to address potential emergencies and ensure the continuity and reliability of information transmission.

[0121] Optionally, step 103, which involves encrypting the priority information packet using a homomorphic encryption algorithm to allow aggregation operations without decryption, ensuring data privacy and availability, and employing adaptive network transmission technology to dynamically adjust the transmission strategy based on real-time network conditions to generate a secure transmission scheme, includes: comprehensively evaluating the patient's information based on the priority information packet, supplementing any missing data through verification to ensure information accuracy and completeness, and generating an optimized information packet; using a homomorphic encryption algorithm based on the optimized information packet to ensure encryption during data transmission and storage, allowing necessary aggregation operations without decryption, ensuring data privacy and availability, and generating an encrypted information packet; using adaptive network transmission technology based on the encrypted information packet to analyze network connection quality and stability by monitoring network bandwidth and packet loss rate parameters in real time, and generating a network condition assessment report; and using the network condition assessment report, combined with the characteristics of the encrypted information packet, performing data fragmentation processing, constructing a retransmission mechanism to ensure information transmission reliability and completeness, and generating a secure transmission scheme.

[0122] The process of generating an encrypted information package based on the optimized information package, using a homomorphic encryption algorithm to ensure encryption during data transmission and storage, allowing necessary aggregation operations without decryption, and guaranteeing data privacy and availability, includes: 1) comprehensively checking and verifying the patient's information based on the optimized information package, generating a verification information package through data integrity and logical consistency checks; 2) encrypting the verification information package using a homomorphic encryption algorithm to ensure encryption during data transmission and storage, selecting an appropriate key length and encryption mode to support necessary aggregation operations without decryption, generating a preliminary encrypted information package; 3) evaluating the encryption strength and performance based on the preliminary encrypted information package, testing computing power and response time by simulating different scenario computing requirements, generating a performance-optimized information package; and 4) adding metadata tags based on the performance-optimized information package, combined with actual application requirements, to facilitate subsequent decryption processing, generating an encrypted information package.

[0123] In this step, the optimized information package is generated after a comprehensive evaluation of the patient's information, based on the priority information package. By verifying and supplementing any missing data, the accuracy and completeness of the information are ensured, providing a solid foundation for subsequent encryption processing.

[0124] Encrypted packets are generated by encrypting optimized packets using homomorphic encryption algorithms. This not only ensures the security of data transmission and storage but also supports the execution of necessary aggregation operations without decryption, thus guaranteeing data privacy and availability.

[0125] The network condition assessment report is an analysis of real-time monitoring network bandwidth and packet loss rate parameters, reflecting the current quality and stability of network connections. This report provides a scientific basis for adaptive network transmission technology, ensuring the reliability and efficiency of data transmission.

[0126] Data fragmentation refers to dividing large blocks of data into smaller data segments for more flexible management and transmission. This processing method, combined with retransmission mechanisms, ensures the reliability and integrity of information transmission, especially under poor network conditions.

[0127] The secure transmission scheme is a complete data transmission strategy built based on network condition assessment reports and the characteristics of encrypted packets. It includes selecting the optimal transmission path, protocol, and emergency response measures to ensure the security and integrity of data transmission.

[0128] The verification information package is generated by comprehensively checking and verifying the comprehensive information of the wounded and sick, based on the optimized information package. It ensures the authenticity and reliability of the information through data integrity verification and logical consistency checks.

[0129] The initial encrypted packet is generated by encrypting the verification packet using a homomorphic encryption algorithm. It ensures that the data is encrypted during transmission and storage, and selects an appropriate key length and encryption mode to support the execution of necessary aggregation operations without decryption.

[0130] The performance optimization packet is generated by evaluating the encryption strength and performance of the initial encrypted packet. By simulating different computing scenarios, it tests computing power and response time to ensure the efficiency and response speed of the encrypted data in practical applications.

[0131] Metadata tags are additional information attached to encrypted packets to facilitate subsequent decryption. These tags typically contain information such as data type, source, and purpose, helping the receiving end to quickly identify and process the data.

[0132] In this embodiment, firstly, based on the priority information packet, a comprehensive assessment of the patient's information is conducted. By verifying and supplementing potentially missing data, the accuracy and completeness of the information are ensured. Homomorphic encryption is used to ensure encryption during data transmission and storage, allowing necessary aggregation operations without decryption, thus guaranteeing data privacy and availability, and generating an encrypted information packet. Secondly, based on the encrypted information packet, adaptive network transmission technology is employed. Real-time monitoring of network bandwidth and packet loss rate parameters is used to analyze network connection quality and stability. Combined with the characteristics of the encrypted information packet, data fragmentation is performed, and a retransmission mechanism is constructed to ensure the reliability and integrity of information transmission, generating a secure transmission scheme. Thirdly, based on the optimized information packet, a comprehensive check and verification of the patient's information is conducted. Through data integrity verification and logical consistency checks, homomorphic encryption is used for encryption processing, ensuring encryption during data transmission and storage. An appropriate key length and encryption mode are selected to support necessary aggregation operations without decryption, generating a preliminary encrypted information packet. Finally, based on the preliminary encrypted information packet, encryption strength and performance are evaluated. By simulating different computational scenarios, computational capabilities and response time are tested. Metadata tags are added based on actual application requirements to facilitate subsequent decryption processing, generating an encrypted information packet.

[0133] In this embodiment, assuming a fire rescue scene in a high-rise building in a city, the process begins with: First, a comprehensive assessment of the injured and sick personnel's information is conducted based on a priority information packet. This involves verifying and supplementing any missing data to ensure accuracy and completeness. Homomorphic encryption is used to maintain encryption during data transmission and storage. Necessary aggregation operations are then performed to generate an encrypted information packet. Second, based on the encrypted information packet, adaptive network transmission technology is employed. This involves real-time monitoring of network bandwidth and packet loss rate parameters, analyzing network connection quality and stability, and, considering the characteristics of the encrypted information packet, performing data fragmentation and constructing a retransmission mechanism to ensure information transmission reliability and integrity. Third, based on an optimized information packet, a comprehensive check and verification of the injured and sick personnel's information is conducted. This includes data integrity checks and logical consistency checks, followed by encryption using a homomorphic encryption algorithm to ensure encryption during data transmission and storage. An appropriate key length and encryption mode are selected to support necessary aggregation operations without decryption, generating a preliminary encrypted information packet. Finally, based on the preliminary encrypted information packet, encryption strength and performance are evaluated. Different computational scenarios are simulated to test computational capabilities and response time. Metadata tags are added based on practical application requirements to facilitate subsequent decryption processing, generating the final encrypted information packet.

[0134] This application recognizes that in existing emergency rescue systems, the lack of effective measures to protect data security and privacy during the transmission of patient information leads to risks of data leakage and tampering. While traditional encryption methods offer a certain level of security, their efficiency and adaptability are often insufficient in complex and ever-changing rescue environments, making it difficult to meet the requirements of real-time performance and high reliability. Therefore, this invention proposes a further alternative solution that uses homomorphic encryption algorithms to ensure that data transmission and storage remain encrypted, and supports the execution of necessary aggregation operations to generate preliminary encrypted information packets without decryption.

[0135] Optionally, based on the verification information packet, a homomorphic encryption algorithm is used for encryption processing to ensure that the data transmission and storage process remains encrypted. An appropriate key length and encryption mode are selected to support the execution of necessary aggregation operations without decryption, generating a preliminary encrypted information packet, including:

[0136] Based on the verification information package, the sensitivity of each data item is assessed, and the importance and security risks of key vital signs parameters are identified.

[0137] Analyze the expected data transmission time and the number of participating nodes to ensure that the encryption algorithm can efficiently adapt to the needs of real-world application scenarios, in order to generate the selected key length;

[0138] The selected key length can be calculated using the following formula:

[0139]

[0140] Where L is the selected key length; D sensitivity ε is the data sensitivity measure; ∈ is the security margin parameter; T' is the expected data transmission time; α' is the time impact coefficient; η' is the network size impact coefficient; N is the number of nodes participating in the transmission; γ' is the non-linear adjustment index, used to adjust the key length selection to adapt to the needs of different application scenarios; C is the current network condition score, including bandwidth and latency; C avg and σ C These are the mean and standard deviation of the network condition scores, respectively.

[0141] Based on the selected key length, a dynamic adjustment coefficient and other complex functions are introduced to simulate the initial encryption process. The effects of network latency and packet loss rate are considered. Through a multi-layer nonlinear adjustment mechanism, the effectiveness and security of the current encryption scheme are evaluated to generate an encryption strength index.

[0142] The encryption strength index is calculated using the following formula:

[0143]

[0144] Where S is the encryption strength index; F i For the data features of the i-th individual characteristic parameter; μ F and σ F , i and n, represent the mean and standard deviation of the data feature, respectively; i is the index of the vital sign parameter, from 1 to n; n is the number of vital sign parameters; w j The weight factor for the j-th aggregation operation; O j (L,M) represents the result of the j-th aggregation operation based on key length L and encryption mode M; j is the index of the aggregation operation, from 1 to m; m is the number of aggregation operations; λ' is the periodic parameter of the sine function, used to introduce additional nonlinear factors to enhance the encryption effect; E k Let β be the k-th environmental factor, including network latency and packet loss rate; k is the index of the characteristic parameter, from 1 to p; p is the number of environmental factors; k δ' is the influence coefficient of environmental factors; S is the historical intensity adjustment coefficient; prev S represents the encryption strength index at the previous moment. max The maximum possible encryption strength index is used for normalization; tanh is the hyperbolic tangent function used to introduce a multi-layer nonlinear adjustment mechanism; M is the encryption mode, which can be selected as a symmetric or asymmetric encryption mode according to specific needs; L is the selected key length.

[0145] Based on the encryption strength index, the consistency of data before and after encryption is ensured by hash verification method, redundancy check is performed, error detection and correction mechanism is introduced, transmission efficiency and decryption speed in actual application scenarios are evaluated, and a preliminary encrypted information packet is generated.

[0146] This method aims to introduce a dynamic adjustment mechanism and a complex mathematical model to assess the sensitivity of each data item and identify the importance and security risks of key parameters. Secondly, it analyzes the expected data transmission time and the number of participating nodes to ensure the encryption algorithm efficiently adapts to the needs of real-world application scenarios. Finally, it ensures data consistency before and after encryption through hash verification, performs redundancy checks, introduces error detection and correction mechanisms, and evaluates transmission efficiency and decryption speed in practical application scenarios, ultimately generating a preliminary encrypted packet. These steps work together to ensure the comprehensiveness and effectiveness of the encryption scheme and solve problems existing in current technologies.

[0147] In the selected key length, the data sensitivity metric Used to measure the sensitivity of each data item, ensuring that key vital signs are adequately protected; time-effect correction term. Considering the impact of data transmission time, ensure the encryption process is completed within a finite time; network scale impact factor. Considering the number of nodes involved in the transmission, ensure that the encryption algorithm can still operate efficiently in large-scale networks; non-linear adjustment of the exponent term. Adjust the key length to suit the needs of different application scenarios and enhance encryption effectiveness;

[0148] Among them, D sensitivity The following parameters are derived from data sensitivity assessment results: ∈ represents a pre-defined security margin parameter; T' represents the expected data transmission time, estimated based on the actual application scenario; α' and η' are empirical parameter types, thus determined experimentally; N represents the number of nodes participating in the transmission, obtained from the network topology; γ' represents the nonlinear adjustment index, set according to application scenario requirements; C represents the current network condition score, including bandwidth, latency, etc., obtained from real-time monitoring data; C avg and σ C These are the mean and standard deviation of the network condition scores, calculated using historical data.

[0149] In encryption strength metrics, data feature matching items This is used to measure the degree of matching between the data characteristics of vital signs and their mean and standard deviation, ensuring the accuracy of the encryption process; aggregated calculation weight terms. Selecting appropriate aggregation operations based on key length and encryption mode ensures flexibility in the encryption process; sine period adjustment term. Introducing additional nonlinear factors to enhance encryption effectiveness; environmental factors influencing the term. Consider the impact of environmental factors such as network latency and packet loss rate on encryption effectiveness; historical strength adjustment item. A multi-layer nonlinear adjustment mechanism is introduced to ensure continuous optimization of encryption strength;

[0150] Among them, F i The data features of the i-th characteristic parameter are obtained from real-time monitoring data; μ F and σ F These are the mean and standard deviation of the data characteristics, calculated from historical data; w j The weight factor for the j-th aggregation operation is set according to the application scenario requirements; O j (L,M) represents the j-th aggregation operation result based on key length L and encryption mode M, obtained through simulation calculation; λ' is the period parameter of the sine function, set according to application scenario requirements; E k The k-th environmental factor, including network latency and packet loss rate, is obtained from real-time monitoring data; β k δ is the influence coefficient of environmental factors, determined experimentally; δ' is the historical intensity adjustment coefficient, set according to the application scenario requirements; S prev The encryption strength index for the previous moment is obtained from historical records; S maxThe maximum possible encryption strength index is obtained through simulation calculation; M is the encryption mode, which can be selected as a symmetric or asymmetric encryption mode according to specific needs; L is the pre-selected key length.

[0151] Imagine a fire rescue operation at a high-rise building in a city center, where multiple patients with burns and inhalation injuries caused by the fire are being treated. To ensure the security and privacy of patient information transmission, the system needs to encrypt the information of each patient.

[0152] Assume the data sensitivity measures are D sensitivity =0.85, safety margin parameter ∈ =0.05, estimated data transmission time is 1 hour (T' = 3600 seconds), time impact coefficient α' = 0.7, network size impact coefficient η' = 0.6, number of nodes participating in transmission N = 5, nonlinear adjustment index γ' = 1.2, current network condition score is C = 0.9, mean network condition score C avg =0.85, standard deviation σ C =0.05;

[0153]

[0154] Assume the data features of the i-th individual characteristic parameter are F1 = 90, F2 = 130 / 90, F3 = 95%, and the mean of the data features is μ. F =92, standard deviation σ F =4, the weight factor w of the j-th aggregation operation j = [0.5, 0.3, 0.2], the j-th aggregation operation result O based on key length L = 256 and encryption mode M. j (L,M)=[1.2,0.8,0.6], the periodic parameter λ'=0.8 of the sine function, the k-th environmental factor is E1=0.05 (network latency), E2=0.02 (packet loss rate), and the influence coefficient β of the environmental factor is... k = [0.5, 0.3], Historical strength adjustment coefficient δ' = 0.7, Encryption strength index S at the previous moment prev =0.8, the maximum possible encryption strength index S max =1.0;

[0155]

[0156] Assuming a threshold of 0.9 is set, the calculated result of 0.95, which is greater than this threshold, indicates that the encryption scheme for patient information has high effectiveness and security, ensuring that data is not tampered with or leaked during transmission and storage. This is because a high encryption strength index reflects that the encryption algorithm can effectively protect data security under current network conditions without affecting transmission efficiency and decryption speed. Through the above steps, the security and privacy of patient information transmission are ensured, the reliability and scientific nature of rescue operations are improved, and the accuracy and response speed of the entire health monitoring system are enhanced.

[0157] 104. Based on the aforementioned secure transmission scheme, the receiving end performs decryption processing, initiates a continuous monitoring mechanism to track changes in the status of the wounded and sick, and generates a wireless transmission scheme for the wounded and sick information.

[0158] Decryption refers to the process by which the receiving end uses the corresponding private key to recover the original information about the wounded and sick. This process ensures that the receiving end can obtain complete information about the wounded and sick for further analysis and processing.

[0159] The continuous monitoring mechanism is an automated process that periodically obtains the latest vital signs data from on-site emergency equipment and compares and analyzes it with previous data. This mechanism ensures real-time tracking and updating of the injured and sick, and timely detection of any abnormal changes.

[0160] The wireless transmission solution for patient information not only includes the latest vital signs data, but also provides detailed treatment suggestions and nursing guidelines to guide medical staff in taking the next steps.

[0161] In this embodiment, assuming a fire rescue operation in a high-rise building in a city, firstly, after receiving the encrypted data, the receiving end decrypts it using the corresponding private key to restore the original patient information; secondly, the system activates a continuous monitoring mechanism, periodically obtaining the latest vital sign data from on-site emergency equipment and comparing it with previous data; thirdly, based on the latest data analysis results, the system updates the patient status summary and priority information package to ensure the timeliness and accuracy of the information; finally, the system generates a wireless transmission scheme for patient information, which not only includes the latest vital sign data but also provides detailed treatment suggestions and nursing guidelines to guide medical personnel in the next steps.

[0162] Optionally, step 104, based on the secure transmission scheme, involves decryption processing at the receiving end, initiating a continuous monitoring mechanism to track changes in the status of the wounded and sick, and generating a wireless transmission scheme for wounded and sick information. This includes: based on the secure transmission scheme, decrypting the encrypted information packet at the receiving end using the same key as the sending end and a homomorphic encryption algorithm in reverse operation to generate a decrypted information packet; based on the decrypted information packet, initiating a continuous monitoring mechanism, using intelligent sensors and monitoring equipment to track changes in the vital signs data and geographical location information of the wounded and sick in real time, and generating a real-time status update report; based on the real-time status update report, reassessing the urgency level according to the frequency and severity of changes in the vital signs of the wounded and sick, combined with geographical environmental factors, and generating a status change assessment report; based on the status change assessment report, and combined with the latest distribution of medical resources, configuring an additional emergency resource dispatch backup plan, and generating a wireless transmission scheme for wounded and sick information.

[0163] In this step, the decryption packet is generated by the receiving end after decrypting the encrypted packet. It uses the same key as the sending end and the reverse operation of the homomorphic encryption algorithm to recover the original comprehensive information of the wounded and sick, ensuring the integrity and availability of the data.

[0164] The continuous monitoring mechanism refers to the process of using intelligent sensors and monitoring equipment to track changes in the vital signs and geographical location information of the injured and sick in real time. This mechanism can automatically acquire the latest vital sign parameters and compare and analyze them with historical data to ensure that any abnormalities are detected in a timely manner.

[0165] The real-time status update report is a detailed report generated based on a continuous monitoring mechanism. It records changes in the vital signs and geographical location information of the injured and sick. This report provides basic data for subsequent status change assessments and helps rescuers quickly understand the latest status of the injured and sick.

[0166] The status change assessment report is generated by reassessing the urgency level based on the frequency and severity of changes in the vital signs of the wounded and sick, combined with geographical environmental factors. This report not only reflects the current health status of the wounded and sick, but also takes into account the impact of the external environment, providing a scientific basis for resource allocation.

[0167] The backup emergency medical resources dispatch plan is a standby rescue plan configured based on the status change assessment report and the latest medical resource distribution. This plan ensures that additional emergency medical resources can be quickly mobilized when needed, thereby improving rescue efficiency.

[0168] In this embodiment, firstly, based on a secure transmission scheme, the encrypted information packet is decrypted at the receiving end by using the same key as the sending end and a homomorphic encryption algorithm in reverse operation to generate a decrypted information packet. Secondly, based on the decrypted information packet, a continuous monitoring mechanism is initiated, using intelligent sensors and monitoring equipment to track changes in the vital signs and geographical location information of the wounded and sick in real time, generating a real-time status update report. Thirdly, based on the real-time status update report, the urgency is reassessed according to the frequency and severity of changes in the vital signs of the wounded and sick, combined with geographical environmental factors, generating a status change assessment report. Finally, based on the status change assessment report and the latest distribution of medical resources, an additional emergency resource dispatch backup plan is configured, generating a wireless transmission scheme for the wounded and sick information.

[0169] Assuming a traffic accident rescue scene on an intercity highway, the system first decrypts the encrypted information packet at the receiving end based on a secure transmission scheme, using the same key and homomorphic encryption algorithm as the sending end to generate a decrypted information packet. Second, based on the decrypted information packet, a continuous monitoring mechanism is activated, utilizing intelligent sensors and monitoring equipment to track changes in the vital signs and geographical location information of the injured in real time, generating a real-time status update report. Third, based on the real-time status update report, the urgency is reassessed according to the frequency and severity of changes in the injured's vital signs, combined with geographical factors, generating a status change assessment report. Finally, based on the status change assessment report and the latest medical resource distribution, an additional emergency resource dispatch backup plan is configured, generating a wireless transmission scheme for the injured's information.

[0170] In summary, steps 101 to 104 cover the entire process management from patient information collection, priority assessment, encrypted transmission to continuous monitoring. The aim is to provide a comprehensive and efficient emergency rescue information processing system that meets the high demands of modern medical rescue for data accuracy, privacy protection, and real-time response. By integrating data from multiple on-site emergency medical devices and employing advanced algorithms and technologies, this system ensures optimal resource allocation and effective treatment of the injured and sick in complex and ever-changing rescue environments.

[0171] Figure 2 This application provides a schematic diagram of the structure of a wireless transmission system for information on the wounded and sick in emergency rescue, as shown in the embodiment of the present application. Figure 2 As shown, the device includes:

[0172] The receiving module 21 is used to receive and integrate basic information and real-time vital signs data of the injured and sick through multiple on-site emergency medical devices, and generate a summary of the injured and sick's status.

[0173] Prediction module 22 is used to analyze the frequency and severity of changes in vital signs of the wounded and sick based on the summary of the wounded and sick, using a priority dynamic adjustment algorithm, to predict the time-series development trend, and to accurately analyze the geographical location and distribution of medical resources using geographic information system technology to generate priority information packages.

[0174] Encryption module 23 is used to encrypt the priority information packet using a homomorphic encryption algorithm, allowing aggregation operations to be performed without decryption, ensuring data privacy and availability, and adopting adaptive network transmission technology to dynamically adjust the transmission strategy according to real-time network conditions to generate a secure transmission scheme.

[0175] The decryption module 24 is used to perform decryption processing at the receiving end based on the secure transmission scheme, start a continuous monitoring mechanism to track changes in the status of the wounded and sick, and generate a wireless transmission scheme for the wounded and sick information.

[0176] Figure 2 The aforementioned wireless transmission system for information on the wounded and sick in emergency rescue can perform... Figure 1 The implementation principle and technical effects of the wireless transmission method for wounded and sick personnel information for emergency rescue described in the illustrated embodiment will not be repeated here. The specific operation methods of each module and unit in the wireless transmission system for wounded and sick personnel information for emergency rescue described in the above embodiments have been described in detail in the embodiments related to this method, and will not be elaborated upon here.

[0177] In one possible design, Figure 2 The illustrated embodiment of a wireless transmission system for patient information in emergency rescue can be implemented as a computing device, such as... Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0178] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are invoked and executed by the processing component 32.

[0179] The processing component 32 is used to: receive and integrate basic information and real-time vital sign data of the injured and sick through multiple on-site emergency medical devices to generate a summary of the injured and sick's status; based on the summary of the injured and sick's status, use a priority dynamic adjustment algorithm to analyze the frequency and severity of changes in the injured and sick's vital signs in detail, predict the time-series development trend, and use geographic information system technology to accurately analyze the geographical location and distribution of medical resources to generate a priority information packet; based on the priority information packet, use a homomorphic encryption algorithm for encryption processing, allowing aggregation operations to be performed without decryption, ensuring data privacy and availability; use adaptive network transmission technology to dynamically adjust the transmission strategy according to the real-time network conditions to generate a secure transmission scheme; based on the secure transmission scheme, decrypt the data at the receiving end, start a continuous monitoring mechanism to track changes in the injured and sick's status, and generate a wireless transmission scheme for the injured and sick's information.

[0180] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-described method. Alternatively, the processing component may be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method.

[0181] Storage component 31 is configured to store various types of data to support operations at the terminal. The storage component 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 read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0182] Of course, computing devices may also include other components, such as input / output interfaces, display components, communication components, etc.

[0183] Input / output interfaces provide interfaces between processing components and peripheral interface modules, which can be output devices, input devices, etc.

[0184] The communication components are configured to facilitate wired or wireless communication between computing devices and other devices.

[0185] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform. In this case, the computing device can refer to a cloud server, and the aforementioned processing components, storage components, etc., can be basic server resources rented or purchased from the cloud computing platform.

[0186] This application also provides a computer storage medium storing a computer program, which, when executed by a computer, can perform the above-described functions. Figure 1 The illustrated embodiment is a method for wireless transmission of information about the wounded and sick in emergency rescue.

[0187] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0188] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0189] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0190] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for wireless transmission of information of a wounded person for emergency rescue, characterized in that, include: Through multiple on-site emergency medical devices, the system receives and integrates basic information and real-time vital signs data of the injured and sick, and generates a summary of the injured and sick's condition. Based on the patient status summary, a priority dynamic adjustment algorithm is used to analyze the frequency and severity of changes in the patients' vital signs, predict the time-series development trend, and use geographic information system technology to accurately analyze the geographical location and distribution of medical resources to generate priority information packages. Based on the priority information packet, homomorphic encryption is used for encryption, allowing aggregation operations to be performed without decryption, ensuring data privacy and availability. Adaptive network transmission technology is employed to dynamically adjust the transmission strategy according to real-time network conditions, generating a secure transmission scheme, including: Based on the priority information package, a comprehensive assessment of the patient's information is conducted, and potentially missing data is supplemented through verification to ensure the accuracy and completeness of the information, thereby generating an optimized information package. Based on the optimized information packet, a homomorphic encryption algorithm is used to ensure that the data is kept encrypted during transmission and storage, allowing necessary aggregation operations to be performed without decryption, thus guaranteeing data privacy and availability. An encrypted information packet is generated, including: Based on the optimized information package, a comprehensive check and verification of the patient's information is performed. A verification information package is generated through data integrity verification and logical consistency check. Based on the verification information packet, a homomorphic encryption algorithm is used for encryption processing to ensure that the encryption state is maintained during data transmission and storage. The key length is dynamically determined based on the data transmission time and the number of participating nodes to adapt to the needs of actual application scenarios. It supports performing aggregation operations without decryption to generate a preliminary encrypted information packet. Based on the initial encrypted information packet, the encryption strength and performance are evaluated. By simulating different scenario computing requirements, the computing power and response time are tested, and a performance optimization information packet is generated. Based on the performance optimization information package, metadata tags are added according to actual application needs to facilitate subsequent decryption processing and generate an encrypted information package. Based on the encrypted information packet, adaptive network transmission technology is used to monitor the real-time network status, obtain network bandwidth and packet loss rate parameters, analyze network connection quality and stability, and generate a network status assessment report. Based on the network condition assessment report and the characteristics of the encrypted information packet, data fragmentation is performed, a retransmission mechanism is constructed to ensure the reliability and integrity of information transmission, and a secure transmission scheme is generated. Based on the aforementioned secure transmission scheme, the receiving end performs decryption processing, initiates a continuous monitoring mechanism to track changes in the status of the wounded and sick, and generates a wireless transmission scheme for the wounded and sick information.

2. The method of claim 1, wherein, Based on the patient status summary, a priority dynamic adjustment algorithm is used to analyze the frequency and severity of changes in the patients' vital signs, predict the temporal development trend, and employ geographic information system technology to accurately analyze geographical location and medical resource distribution, generating a priority information package, including: Based on the patient status summary, the patient's vital signs data and environmental background information are comprehensively evaluated and processed to generate a preliminary priority score. Based on the preliminary priority score, the priority dynamic adjustment algorithm is used to combine the historical data and current status of the wounded and sick to analyze the frequency and severity of changes in the vital signs of the wounded and sick in detail, and generate an optimized priority score. Based on the optimized priority score, geographic information system technology is used to accurately process the location information of the wounded and sick, analyze the distribution of surrounding medical resources, determine the optimal rescue route, and generate a geographic location analysis report. Based on the geographic location analysis report, the optimization priority score is deeply integrated to generate a priority information package.

3. The method of claim 2, wherein, Based on the initial priority score, a dynamic priority adjustment algorithm is used, combining historical data and current status of the wounded and sick, to meticulously analyze the frequency and severity of changes in the wounded and sick's vital signs, generating an optimized priority score, including: Based on the preliminary priority score, the historical vital signs data of the wounded and sick are comprehensively compared with their current status to identify abnormal changes and generate a status difference report. Based on the aforementioned status difference report, a priority dynamic adjustment algorithm is used to quantify the frequency of changes in the vital signs of the injured and sick within different time periods. Different dynamic weight factors are assigned according to the severity of the changes to reflect the trend of disease development and generate an assessment of the frequency and severity of changes. Based on the aforementioned frequency of change and severity assessment, combined with the patient's historical priority score and the aforementioned preliminary priority score, the overall urgency level is comprehensively reassessed to generate a comprehensive urgency assessment. Based on the comprehensive urgency assessment, parameters are updated regularly to adapt to changing realities, and all assessment results are integrated to generate an optimized priority score.

4. The method of claim 2, wherein, Based on the optimized priority score, geographic information system (GIS) technology is used to accurately process the location information of the wounded and sick, analyze the distribution of surrounding medical resources, determine the optimal rescue route, and generate a geographic location analysis report, including: Based on the optimized priority score, the location information of the wounded and sick is accurately collected and processed to obtain the current latitude and longitude coordinates of the wounded and sick, and combined with high-precision map data to generate accurate positioning data; Based on the precise positioning data, geographic information system technology is used to conduct a detailed analysis of the geographical environment of the location of the wounded and sick, and a geographical environment assessment is generated by comprehensively considering the topography and road network. Based on the geographical environment assessment and the optimization priority score, the distribution of surrounding medical resources is analyzed, the service capacity and current load of nearby medical institutions are assessed, and a medical resource distribution map is generated. Based on the aforementioned medical resource distribution map, the path planning method is used to simulate traffic flow changes over different time periods, predict potential traffic bottlenecks, and generate a geographic location analysis report.

5. The method of claim 1, wherein, Based on the aforementioned secure transmission scheme, the receiving end performs decryption processing, initiates a continuous monitoring mechanism to track changes in the status of the wounded and sick, and generates a wireless transmission scheme for wounded and sick information, including: Based on the aforementioned secure transmission scheme, the encrypted information packet is decrypted at the receiving end, and the same key as the sending end is used to reverse the homomorphic encryption algorithm to generate a decrypted information packet. Based on the decrypted information packet, a continuous monitoring mechanism is activated, and intelligent sensors and monitoring equipment are used to track changes in the vital signs data and geographical location information of the wounded and sick in real time, and generate a real-time status update report. Based on the real-time status update report, the urgency level is reassessed according to the frequency and severity of changes in the vital signs of the wounded and sick, combined with geographical environmental factors, and a status change assessment report is generated. Based on the status change assessment report and the latest medical resource distribution, an additional emergency resource dispatch backup plan is configured, and a wireless transmission plan for patient information is generated.

6. A wireless transmission system for patient information for emergency rescue, characterized by, include: The receiving module is used to receive and integrate basic information and real-time vital signs data of the injured and sick through multiple on-site emergency medical devices, and generate a summary of the injured and sick's status. The prediction module is used to analyze the frequency and severity of changes in the vital signs of the wounded and sick based on the summary of the wounded and sick, using a priority dynamic adjustment algorithm to predict the time-series development trend, and using geographic information system technology to accurately analyze the geographical location and distribution of medical resources to generate priority information packages. The encryption module is used to encrypt the priority information packet using a homomorphic encryption algorithm, allowing aggregation operations to be performed without decryption, ensuring data privacy and availability. It employs adaptive network transmission technology to dynamically adjust the transmission strategy based on real-time network conditions, generating a secure transmission scheme, including: Based on the priority information package, a comprehensive assessment of the patient's information is conducted, and potentially missing data is supplemented through verification to ensure the accuracy and completeness of the information, thereby generating an optimized information package. Based on the optimized information packet, a homomorphic encryption algorithm is used to ensure that the data is kept encrypted during transmission and storage, allowing necessary aggregation operations to be performed without decryption, thus guaranteeing data privacy and availability. An encrypted information packet is generated, including: Based on the optimized information package, a comprehensive check and verification of the patient's information is performed. A verification information package is generated through data integrity verification and logical consistency check. Based on the verification information packet, a homomorphic encryption algorithm is used for encryption processing to ensure that the encryption state is maintained during data transmission and storage. The key length is dynamically determined based on the data transmission time and the number of participating nodes to adapt to the needs of actual application scenarios. It supports performing aggregation operations without decryption to generate a preliminary encrypted information packet. Based on the initial encrypted information packet, the encryption strength and performance are evaluated. By simulating different scenario computing requirements, the computing power and response time are tested, and a performance optimization information packet is generated. Based on the performance optimization information package, metadata tags are added according to actual application needs to facilitate subsequent decryption processing and generate an encrypted information package. Based on the encrypted information packet, adaptive network transmission technology is used to monitor the real-time network status, obtain network bandwidth and packet loss rate parameters, analyze network connection quality and stability, and generate a network status assessment report. Based on the network condition assessment report and the characteristics of the encrypted information packet, data fragmentation is performed, a retransmission mechanism is constructed to ensure the reliability and integrity of information transmission, and a secure transmission scheme is generated. The decryption module is used to perform decryption processing at the receiving end based on the secure transmission scheme, start a continuous monitoring mechanism to track changes in the status of the wounded and sick, and generate a wireless transmission scheme for the wounded and sick information.

7. A computing device, comprising: It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement a wireless transmission method for information on the wounded and sick for emergency rescue as described in any one of claims 1 to 5.

8. A computer storage medium, characterized in that The device contains a computer program that, when executed by a computer, implements a method for wireless transmission of information about the wounded and sick for emergency rescue as described in any one of claims 1 to 5.

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