Emergency rescue cabin intelligent management and control platform integrating environment regulation and control and life support

Abstract

The invention discloses an emergency rescue cabin intelligent management and control platform integrating environment regulation and control and life support, relates to the technical field of rescue cabin management and control, and solves the technical problems of lack of data linkage and cause positioning and lack of regulation and control accuracy and safety. Through environment-sign correlation verification of the normal condition monitoring and analyzing module, originally split environment data and sign data are bound and analyzed, inducements of sign abnormity can be judged in a short time, the abnormal condition monitoring and analyzing module can automatically complete historical data comparison, abnormity classification and strategy matching, and the abnormal condition monitoring and analyzing module can automatically complete abnormal condition monitoring and analyzing. Early warning of single-person emergency abnormity and multi-person same-type abnormity in a short time is achieved, a comprehensive regulation and control analysis module introduces a dynamic monitoring and layered regulation and control mechanism, when a similar environment regulation and control strategy is adopted, normal person signs are synchronously monitored, chain discomfort is avoided, meanwhile, local regulation and control are preferentially adopted, interference to the whole cabin is reduced, and the safety of the whole cabin is improved. The resource utilization rate is improved.

Description

Technical Field

[0001] This invention relates to the field of rescue cabin control technology, specifically to an intelligent control platform for emergency rescue cabins that integrates environmental regulation and life support. Background Technology

[0002] Emergency rescue cabins are core support facilities in natural disasters, public health emergencies, and special environmental operations. Their core requirement is to ensure the safety of personnel inside the cabin and support the efficient conduct of rescue work by maintaining a suitable environment and monitoring their vital signs in real time.

[0003] Currently, the existing emergency rescue cabin control systems have the following limitations. First, the data is fragmented. Environmental monitoring and personnel vital sign monitoring are mostly operated by independent systems, and the data are not linked for analysis, making it impossible to determine whether abnormal vital signs are related to environmental changes. Second, the control is extensive and lacks a dynamic verification mechanism. Environmental control strategies are mostly fixed patterns and do not consider local anomalies and local control, which may lead to waste of resources or affect normal personnel. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an intelligent management and control platform for emergency rescue cabins that integrates environmental control and life support, solving the problems of lack of data linkage and cause localization, as well as insufficient control accuracy and safety.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an intelligent control platform for emergency rescue cabins integrating environmental regulation and life support, comprising:

[0006] The normal condition monitoring and analysis module is used to analyze the monitoring of normal signals, retrieve the historical vital sign data of the personnel currently under monitoring, generate normal monitoring information if there is no change, lock the period of change and the corresponding cabin environment data if there is a change, mark the candidate related data and verify it, generate an environment-vital sign association report, and if the environmental data does not change, retrieve the data of the non-change period to check for anomalies and generate anomaly analysis results.

[0007] The abnormal situation monitoring and analysis module processes the monitored abnormal signals, identifies the number of abnormal personnel in the rescue area of ​​the abnormal cabin, and generates a single person abnormality identifier or a multiple person abnormality identifier. In the case of a single abnormality, if it is the first time it has occurred, a single abnormality handling signal is generated. If it is not the first time, a similar environmental control strategy is adopted. If there are no normal personnel abnormalities after monitoring, environmental parameter control information is generated. Otherwise, a single abnormality handling signal is generated. In the case of multiple personnel abnormalities, historical data is compared. If the same type of abnormality is generated, a group abnormality handling signal is generated. Otherwise, a single abnormality signal is generated.

[0008] The comprehensive control and analysis module is used to process single and group anomaly signals. For single anomaly signals, if they are caused by environmental factors, control is applied based on environmental-vital sign correlation parameters. If they are not caused by environmental factors, the anomaly level is determined based on abnormal vital sign parameters, and control is applied accordingly, generating single anomaly information. For group anomaly signals, if they are caused by common environmental factors, relevant environmental parameters are adjusted to a safe range and group vital signs are monitored. If multiple factors are involved, a multi-dimensional analysis process is initiated to predict the development trend of group anomalies and dynamically adjust the priority of control strategies based on the prediction results, generating group anomaly information.

[0009] As a further embodiment of the present invention, it also includes a cabin information analysis module, which is used to analyze the collected cabin data, divide the emergency rescue cabin into cabin rescue areas according to the area, match the vital signs data of the personnel in the cabin rescue area with the pre-stored normal data, and output the monitoring normal signal or monitoring abnormal signal.

[0010] The control information output module is used to display normal monitoring information, anomaly analysis results, single anomaly handling information, and group anomaly handling information to the corresponding management personnel.

[0011] As a further aspect of the present invention, the method of outputting a normal monitoring signal or an abnormal monitoring signal is as follows:

[0012] Acquire cabin data, including cabin environment data and personnel vital signs data, and clean it. Divide the emergency rescue cabin into areas to obtain cabin rescue areas. At the same time, acquire the personnel vital signs data corresponding to the cabin rescue areas and match them with the pre-stored normal monitoring data range.

[0013] If all personnel vital signs data are within their corresponding normal monitoring data range, the vital signs are judged to be normal, and a normal monitoring signal is generated. Conversely, if any personnel vital signs data is outside its corresponding normal monitoring data range, the vital signs are judged to be abnormal, and an abnormal monitoring signal is generated.

[0014] As a further aspect of the present invention, the normal condition monitoring and analysis module analyzes the monitored normal signals in the following way:

[0015] Retrieve historical data of currently monitored normal personnel, and further define significant change criteria based on the normal monitoring data range set by medical staff. If the threshold is not reached, it is determined that there is no significant change, and normal monitoring information is generated and directly transmitted to the control information output module.

[0016] If a single indicator does not reach the threshold for significant change, but there is a continuous unidirectional trend, it is also determined that there is a change. At the same time, the change period is automatically locked, the cabin environment data within the change period is retrieved, the type of environmental parameter change, the magnitude of change and the start time are recorded, and the start time of environmental change is compared with the start time of vital sign change.

[0017] As a further aspect of the present invention, the method for comparing the start time of environmental change with the start time of vital sign change is as follows:

[0018] If the time difference between the two is ≤ t minutes and the trend of change is consistent, the changed cabin environment data and the changed personnel vital signs data are marked as candidate related data; if the environmental data does not change, the time difference is > t1 minutes, or the trend of change is not logically related, the abnormality verification and investigation stage is directly entered, and the specific values ​​of t and t1 are set by the operator.

[0019] Retrieve cabin environmental data and personnel vital signs data during non-change periods, where the non-change period is the period after the change period and the period when the environmental data has stabilized. If the personnel vital signs data recover to the normal level before the change during the non-change period, the candidate related data is deemed to be correctly verified, and an environment-vital signs association report is generated. If the personnel vital signs data do not recover during the non-change period, investigate the cause of the anomaly and record the specific manifestation of the anomaly.

[0020] As a further aspect of the present invention, the abnormal situation monitoring module processes a single abnormal signal in the following manner:

[0021] Retrieve the historical vital sign data of the abnormal individual and compare it with the current abnormal vital sign data. If the abnormal vital sign is the first occurrence, mark it as an emergency abnormality, trigger the emergency response mechanism, and generate a single abnormality handling signal. If the abnormal vital sign is similar to an abnormality in the historical data, analyze the handling result and recovery status of that abnormality. If the previous abnormality was alleviated by adjusting environmental parameters, try to adopt a similar environmental control strategy and monitor the vital sign data of other normal individuals. If the vital signs of other normal individuals do not fluctuate abnormally, maintain the current control strategy and generate environmental parameter control information. If the vital signs of other normal individuals show abnormal changes or the vital signs of the abnormal individual do not improve, stop the current control strategy and generate a single abnormality handling signal.

[0022] As a further aspect of the present invention, the abnormal situation monitoring module processes group abnormal processing signals in the following way:

[0023] Batch retrieve historical vital sign data of all abnormal personnel, compare it with the current abnormal vital sign data, and determine whether they are of the same type of abnormality. If they are of the same type of abnormality, activate the group abnormality early warning mechanism and generate a group abnormality handling signal; if they are not of the same type of abnormality, operate according to the single person abnormality handling procedure for each abnormal person and generate the corresponding single abnormality handling signal.

[0024] As a further aspect of the present invention, the processing method of the comprehensive control and analysis module for a single abnormal processing signal is as follows:

[0025] Analyze the abnormal factors. If they are caused by environmental factors, adjust the control based on the environmental-vital sign correlation parameters. If they are caused by non-environmental factors, match the abnormal vital sign parameters with the abnormality level range to determine the abnormality level. For emergency levels, activate the emergency control mode; for less emergency levels, activate the regular control mode. Monitor the abnormal vital sign parameters in real time. If the vital signs improve and stabilize, maintain the current mode until the vital signs recover. If the vital signs do not improve, upgrade the control mode, trigger a higher-level emergency response mechanism, and generate a single abnormality handling information.

[0026] As a further aspect of the present invention, the processing method of the integrated control and analysis module for the group anomaly processing signal is as follows:

[0027] Assess the severity and scope of the group anomaly. If it is caused by a common environmental factor, adjust relevant environmental parameters to a safe range and monitor the group's vital signs. If multiple factors are involved, initiate a multi-dimensional analysis process to investigate cabin environmental data during the period of the anomaly, identify sudden changes in environmental parameters, retrieve the activity trajectories of the abnormal personnel, and analyze whether there are common exposure areas or operating procedures. If the sudden change in environmental parameters is significantly correlated with the personnel anomaly in time and space, prioritize the control of that environmental parameter and monitor its stability. If the correlation is weak or the factors are intertwined, combine the dynamic changes in the personnel's vital signs to predict the development trend of the group anomaly and dynamically adjust the priority of the control strategy to generate group anomaly handling information.

[0028] This invention provides an intelligent management and control platform for emergency rescue cabins that integrates environmental control and life support. Compared with existing technologies, it has the following advantages:

[0029] This invention binds and analyzes previously fragmented environmental and vital sign data by using a cabin information analysis module for data cleaning and format standardization, and an environmental-vital sign correlation verification module for normal condition monitoring and analysis. This allows for the rapid identification of the causes of abnormal vital signs. The abnormal condition monitoring and analysis module automatically performs historical data comparison, abnormal classification, and strategy matching, enabling early warning of single-person emergency abnormalities and multiple personnel with the same type of abnormality within a short period, thus improving response speed. The comprehensive control and analysis module introduces a dynamic monitoring and hierarchical control mechanism. When using similar environmental control strategies, it simultaneously monitors the vital signs of normal personnel to avoid chain reactions of discomfort. At the same time, it prioritizes local control to reduce interference with the entire cabin and improve resource utilization. Attached Figure Description

[0030] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] First Embodiment

[0033] Please see Figure 1 This application provides an intelligent management and control platform for emergency rescue cabins integrating environmental control and life support, including: a cabin information analysis module, a normal condition monitoring and analysis module, an abnormal condition monitoring and analysis module, a comprehensive control and analysis module, and a control information output module, and combined with... Figure 1 It can be seen that the information between the above functional modules is transmitted in one direction only.

[0034] The cabin information analysis module analyzes the collected cabin data, including environmental and personnel vital signs data. Environmental data includes temperature, humidity, oxygen concentration, CO2 concentration, and PM2.5 concentration, while vital signs data includes heart rate, blood pressure, and pulse oximetry. Environmental data is collected via IoT sensors deployed throughout the cabin, while vital signs data is collected via wearable or portable medical devices. The module cleans and verifies the raw data, removing outliers, correcting missing values, and standardizing the data format. It also divides the emergency rescue cabin into rescue zones and monitors the vital signs of personnel within each zone. The module has a built-in dynamic benchmark database storing normal monitoring data ranges set by medical professionals based on medical standards, and matches the personnel vital signs data with these normal monitoring data.

[0035] If all personnel vital signs data are within their corresponding normal monitoring data range, the vital signs are determined to be normal, a normal monitoring signal is generated, along with the personnel ID, location, current personnel vital signs data, and environmental data. Conversely, if any personnel vital signs data is outside its corresponding normal monitoring data range, the vital signs are determined to be abnormal, a monitoring abnormal signal is generated, and the generated signal is transmitted to the corresponding analysis module.

[0036] The normal condition monitoring and analysis module analyzes the acquired normal monitoring signals. By default, it retrieves the historical data of the personnel currently under monitoring for the past 24 hours. The data granularity is consistent with the real-time acquisition frequency. Each historical data is associated with the personnel ID, the rescue area ID of the cabin, the acquisition timestamp, and the cabin environmental data for the corresponding time period. It automatically removes outliers from the historical data and uses a moving average method to correct data fluctuations. Based on the normal monitoring data range set by medical staff, it further defines the criteria for significant changes, such as: heart rate fluctuations exceeding 10 beats / min within 10 minutes, systolic blood pressure fluctuations exceeding 15 mmHg, and blood oxygen saturation fluctuations exceeding 3%. If the threshold is not reached, it is judged as no significant change. Normal monitoring information is generated, including personnel ID, monitoring time period, average vital signs data, and average corresponding environmental data, which is directly transmitted to the control information output module.

[0037] If a single indicator does not reach the threshold for significant change, but there is a continuous unidirectional trend, for example, the heart rate continuously increases from 70 beats / min to 85 beats / min. Although the single fluctuation does not exceed 10 beats / min, the cumulative increase is 15 beats / min within 1 hour. This is also considered a change. At the same time, the change period is automatically locked, the cabin environment data during the change period is retrieved, the presence of significant changes in environmental parameters is identified, the type of environmental parameter change, the magnitude of change, and the start time are recorded, and the start time of the environmental change is compared with the start time of the vital signs change.

[0038] If the time difference between the two is ≤ t minutes and the trends are consistent, such as temperature increase → heart rate slightly increase, CO2 increase → blood oxygen slightly decrease, then it is preliminarily determined that there is a correlation between the environment and vital signs. The environmental data and vital sign data that change in this group are marked as candidate correlation data. If the environmental data does not change, or the time difference between the environmental change and the vital sign change is > t1 minutes, or the trends are not logically related, then no correlation is marked for the time being, and the abnormal verification and investigation stage is directly entered. The specific numbers of t and t1 are set by the operator.

[0039] Acquire candidate correlation data and simultaneously acquire the non-change period, which represents the time after the change period when the environmental data has stabilized and lasted for more than 30 minutes. If the personnel vital signs data recover to the normal level before the change within the non-change period, the candidate correlation data verification result is determined to be correct. At this time, an environment-vital signs correlation report is generated, the correlation parameters are recorded, and it is transmitted to the control information output module. If the personnel vital signs data still do not recover within the non-change period, the correlation data verification result is determined to be abnormal. Further analysis of the cause of the abnormality is then conducted to investigate which one or more factors in the cabin environment data caused the abnormal change in personnel vital signs data. The specific manifestations of the abnormality are recorded, including the type and degree of abnormality of personnel vital signs data. An abnormality analysis result is generated and transmitted to the control information output module.

[0040] The control information output module is used to display the acquired normal monitoring information and anomaly analysis results to the relevant management personnel.

[0041] Second Embodiment

[0042] As a second embodiment of the present invention, it is implemented based on the first embodiment, and the difference from the first embodiment is as follows:

[0043] The abnormal situation monitoring and analysis module is used to process the acquired abnormal monitoring signals, obtain the corresponding abnormal cabin rescue area, and obtain the corresponding abnormal personnel situation within the abnormal cabin rescue area. It also determines the number of abnormal personnel and generates a single-person abnormality identifier or a multi-person abnormality identifier, and then analyzes the abnormal situation of different personnel respectively.

[0044] For cases involving a single individual with an abnormal identification, the system first retrieves the individual's historical vital sign data and compares it with the current abnormal vital sign data. It analyzes whether the abnormal vital sign is the first occurrence or similar to a previous abnormality in the historical data. If it is the first occurrence, it is immediately marked as an emergency abnormality, triggering an emergency response mechanism and generating a single abnormality handling signal. If the abnormal vital sign is similar to a previous abnormality in the historical data, the system further analyzes the handling results and subsequent recovery of that previous abnormality. If the previous abnormality was effectively alleviated by adjusting environmental parameters, a similar environmental control strategy is attempted, and the environmental control strategy is monitored and analyzed. Specifically, the vital sign data of other normal individuals are monitored. If no abnormal fluctuations are found in the vital sign data of other normal individuals during the application of a similar environmental control strategy, the current environmental control strategy is maintained, and environmental parameter control information is generated. If abnormal changes are found in the vital sign data of other normal individuals, or if the vital sign data of the abnormal individual is not improved or even worsens, the current environmental control strategy is immediately stopped, a single abnormality handling signal is generated, and it is transmitted to the comprehensive control and analysis module.

[0045] In the case of multiple abnormal identifications, the historical vital signs data of all abnormal individuals are first retrieved in batches and compared with the current abnormal vital signs data. Through data analysis, it is determined whether the abnormalities of multiple individuals belong to the same type of abnormality, that is, whether the abnormal vital signs have similar characteristics. If it is determined to be the same type of abnormality, the group abnormality early warning mechanism is immediately activated, a group abnormality handling signal is generated, and the signal is transmitted to the comprehensive control and analysis module.

[0046] If analysis reveals that multiple abnormalities among individuals are not of the same type, then for each individual with an abnormality, the handling procedure for a single abnormality will be followed. This involves retrieving their respective historical vital sign data, analyzing the occurrence of the abnormality, and determining whether to mark it as an emergency abnormality and trigger the emergency response mechanism based on whether it is the first occurrence or similar to historical data. This process generates a corresponding single abnormality handling signal, which is then transmitted to the integrated control and analysis module.

[0047] The comprehensive control and analysis module analyzes both single and group abnormal control signals. For a single abnormal control signal, it analyzes the abnormal factors. If the abnormality is caused by environmental factors, it adjusts the signal based on environmental-vital sign correlation parameters. If the abnormality is not caused by environmental factors, it acquires the abnormal vital sign parameters corresponding to the single abnormal control signal and matches them with the corresponding abnormality level range. Specifically, the emergency level is defined as: blood oxygen <90%, heart rate >130 beats / min; the secondary emergency level is defined as: blood oxygen 90%-93%, heart rate 100-130 beats / min. The corresponding abnormality level is determined, and the abnormality level includes both emergency and secondary emergency levels. For emergency situations, the emergency control mode is directly activated; for secondary emergency situations, the regular control mode is activated, and the changes in abnormal vital sign parameters are monitored in real time. If the abnormal vital sign parameters improve and stabilize during the control process, the current control mode is maintained until the vital signs fully recover. If the abnormal vital sign parameters do not improve or continue to deteriorate, the control mode is immediately upgraded, and a higher-level emergency response mechanism is triggered, generating single abnormal control information.

[0048] For abnormal group signals, assess the severity and scope of the abnormality. If the abnormality is caused by a common environmental factor, quickly adjust relevant environmental parameters to a safe range and continuously monitor changes in group vital signs. If the cause of the abnormality involves multiple factors, immediately initiate a multi-dimensional analysis process, and the specific analysis methods are as follows:

[0049] A comprehensive review of the cabin environment data during the period of the group anomaly was conducted to identify any sudden changes or persistent anomalies in environmental parameters. At the same time, the activity trajectories of all personnel with anomalies during that period were retrieved to analyze whether there was any common exposure to a specific environmental area or operating procedure. If a significant correlation was found between the sudden change in environmental parameters and the personnel anomaly in time or space, emergency control of the environmental parameter was prioritized, and environmental parameter stability monitoring was initiated simultaneously to ensure that the environmental parameter remained within the safe threshold after control.

[0050] If the correlation between environmental parameters and personnel anomalies is weak, or if there are multiple potential influencing factors intertwined, then by further combining the dynamic changing trends of personnel vital signs data, machine learning algorithms are used to construct an anomaly prediction model to predict the development trend of group anomalies. Based on the prediction results, the priority of control strategies is dynamically adjusted, and group anomaly handling information is generated. The anomaly type, occurrence time, scope of impact, control measures taken, and effect evaluation are recorded in detail. This information is transmitted to the control information output module in real time to provide comprehensive decision support for managers.

[0051] The management information output module is used to display the generated single anomaly handling information and group anomaly handling information to the corresponding management personnel.

[0052] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0053] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. An intelligent control platform for emergency rescue cabins integrating environmental control and life support, characterized in that: include: The normal condition monitoring and analysis module is used to analyze the monitoring of normal signals, retrieve the historical vital sign data of the personnel currently under monitoring, generate normal monitoring information if there is no change, lock the period of change and the corresponding cabin environment data if there is a change, mark the candidate related data and verify it, generate an environment-vital sign association report, and if the environmental data does not change, retrieve the data of the non-change period to check for anomalies and generate anomaly analysis results. The abnormal situation monitoring and analysis module processes the monitored abnormal signals, identifies the number of abnormal personnel in the rescue area of ​​the abnormal cabin, and generates a single person abnormality identifier or a multiple person abnormality identifier. In the case of a single abnormality, if it is the first time it has occurred, a single abnormality handling signal is generated. If it is not the first time, a similar environmental control strategy is adopted. If there are no normal personnel abnormalities after monitoring, environmental parameter control information is generated. Otherwise, a single abnormality handling signal is generated. In the case of multiple personnel abnormalities, historical data is compared. If the same type of abnormality is generated, a group abnormality handling signal is generated. Otherwise, a single abnormality signal is generated. The comprehensive control and analysis module is used to process single and group anomaly signals. For single anomaly signals, if they are caused by environmental factors, control is applied based on environmental-vital sign correlation parameters. If they are not caused by environmental factors, the anomaly level is determined based on abnormal vital sign parameters, and control is applied accordingly, generating single anomaly information. For group anomaly signals, if they are caused by common environmental factors, relevant environmental parameters are adjusted to a safe range and group vital signs are monitored. If multiple factors are involved, a multi-dimensional analysis process is initiated to predict the development trend of group anomalies and dynamically adjust the priority of control strategies based on the prediction results, generating group anomaly information.

2. The intelligent control platform for emergency rescue cabins integrating environmental regulation and life support as described in claim 1, characterized in that, It also includes a cabin information analysis module, which is used to analyze the collected cabin data, divide the emergency rescue cabin into cabin rescue areas according to the area, match the vital signs data of the personnel in the cabin rescue area with the pre-stored normal data, and output the monitoring normal signal or monitoring abnormal signal. The control information output module is used to display normal monitoring information, anomaly analysis results, single anomaly handling information, and group anomaly handling information to the corresponding management personnel.

3. The intelligent control platform for emergency rescue cabins integrating environmental regulation and life support as described in claim 2, characterized in that, The methods for outputting normal or abnormal monitoring signals are as follows: Acquire cabin data, including cabin environment data and personnel vital signs data, and clean it. Divide the emergency rescue cabin into areas to obtain cabin rescue areas. At the same time, acquire the personnel vital signs data corresponding to the cabin rescue areas and match them with the pre-stored normal monitoring data range. If all personnel vital signs data are within their corresponding normal monitoring data range, the vital signs are judged to be normal, and a normal monitoring signal is generated. Conversely, if any personnel vital signs data is outside its corresponding normal monitoring data range, the vital signs are judged to be abnormal, and an abnormal monitoring signal is generated.

4. The intelligent control platform for emergency rescue cabins integrating environmental regulation and life support as described in claim 1, characterized in that, The normal condition monitoring and analysis module analyzes normal monitoring signals in the following way: Retrieve historical data of currently monitored normal personnel, and further define significant change criteria based on the normal monitoring data range set by medical staff. If the threshold is not reached, it is judged as no significant change, and normal monitoring information is generated and directly transmitted to the control information output module. If a single indicator does not reach the threshold for significant change, but there is a continuous unidirectional trend, it is also determined that there is a change. At the same time, the change period is automatically locked, the cabin environment data within the change period is retrieved, the type of environmental parameter change, the magnitude of change and the start time are recorded, and the start time of environmental change is compared with the start time of vital sign change.

5. The intelligent control platform for emergency rescue cabins integrating environmental regulation and life support according to claim 4, characterized in that, The method for comparing the onset time of environmental changes with the onset time of changes in vital signs is as follows: If the time difference between the two is ≤ t minutes and the trend of change is consistent, the changed cabin environment data and the changed personnel vital signs data are marked as candidate related data; if the environmental data does not change, the time difference is > t1 minutes, or the trend of change is not logically related, the abnormality verification and investigation stage is directly entered, and the specific values ​​of t and t1 are set by the operator. Retrieve cabin environmental data and personnel vital signs data during non-change periods, where the non-change period is the period after the change period and the period when the environmental data has stabilized. If the personnel vital signs data recover to the normal level before the change during the non-change period, the candidate related data is deemed to be correctly verified, and an environment-vital signs association report is generated. If the personnel vital signs data do not recover during the non-change period, investigate the cause of the anomaly and record the specific manifestation of the anomaly.

6. The intelligent control platform for emergency rescue cabins integrating environmental regulation and life support according to claim 1, characterized in that, The abnormal situation monitoring module handles single abnormal signals as follows: Retrieve the historical vital signs data of the abnormal person and compare it with the current abnormal vital signs data. If the abnormal vital signs are the first time they have appeared, mark it as an emergency abnormality, trigger the emergency response mechanism, and generate a single abnormality handling signal. If the abnormal vital signs are similar to an abnormality in historical data, analyze the handling results and recovery status of that abnormality. If the previous abnormality was alleviated by adjusting environmental parameters, try to adopt a similar environmental control strategy and monitor the vital signs data of other normal personnel. If the vital signs of other normal personnel do not fluctuate abnormally, maintain the current control strategy and generate environmental parameter control information. If the vital signs of other normal personnel show abnormal changes or the vital signs of abnormal personnel do not improve, stop the current control strategy and generate a single abnormality handling signal.

7. The intelligent control platform for emergency rescue cabins integrating environmental regulation and life support as described in claim 1, characterized in that, The abnormal situation monitoring module processes group abnormal signals in the following way: Batch retrieve historical vital sign data of all abnormal personnel, compare it with the current abnormal vital sign data, and determine whether they are of the same type of abnormality. If they are of the same type of abnormality, activate the group abnormality early warning mechanism and generate a group abnormality handling signal; if they are not of the same type of abnormality, operate according to the single person abnormality handling procedure for each abnormal person and generate the corresponding single abnormality handling signal.

8. The intelligent control platform for emergency rescue cabins integrating environmental regulation and life support according to claim 1, characterized in that, The integrated control and analysis module processes single anomaly signals as follows: Analyze the abnormal factors; if they are caused by environmental factors, adjust them in conjunction with environmental-vital correlation parameters. If the abnormality is not caused by environmental factors, match the abnormal vital signs parameters with the abnormality level range to determine the abnormality level. Emergency response mode is activated for emergency-level situations, and normal control mode is activated for sub-emergency-level situations. Monitor abnormal vital signs parameters in real time. If the vital signs improve and stabilize, maintain the current mode until the vital signs recover. If the vital signs do not improve, upgrade the control mode, trigger a higher-level emergency response mechanism, and generate a single abnormality handling information.

9. The intelligent control platform for emergency rescue cabins integrating environmental regulation and life support according to claim 1, characterized in that, The integrated control and analysis module processes group anomaly signals in the following way: Assess the severity and scope of the group anomaly. If it is caused by a common environmental factor, adjust relevant environmental parameters to a safe range and monitor the group's vital signs. If multiple factors are involved, initiate a multi-dimensional analysis process to investigate cabin environmental data during the period of the anomaly, identify sudden changes in environmental parameters, retrieve the activity trajectories of the abnormal personnel, and analyze whether there are common exposure areas or operating procedures. If the sudden change in environmental parameters is significantly correlated with the personnel anomaly in time and space, prioritize the control of that environmental parameter and monitor its stability. If the correlation is weak or the factors are intertwined, combine the dynamic changes in the personnel's vital signs to predict the development trend of the group anomaly and dynamically adjust the priority of the control strategy to generate group anomaly handling information.

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