A method and system for locating persons trapped in fire

Abstract

The present invention belongs to the technical field of fire rescue, and discloses a method and system for locating persons trapped in a fire, wherein the method for locating persons trapped in a fire comprises the following steps: integrating a heart rate sensor, a body temperature sensor, and a respiratory rate sensor into a portable device, collecting vital sign data, and sending the data to a central processing unit through a wireless transmission mechanism, performing monitoring and analysis, and acquiring vital sign monitoring data; the present invention realizes more accurate vital sign status recognition and abnormal warning by integrating sensor data and performing real-time analysis, and further improves the positioning accuracy of trapped persons by combining real-time collection of acoustic fluctuations and processing of acoustic wave characteristics, optimizes the allocation of rescue resources by calculating the sound source positioning coordinates, and can formulate efficient and targeted rescue strategies and priority allocations, thereby significantly improving rescue efficiency, reducing search time and waste of resources, and increasing the survival probability of trapped persons.

Description

Technical Field

[0001] The invention belongs to the technical field of fire rescue, and in particular relates to a method and a system for locating persons trapped in a fire. Background Art

[0002] The field of fire rescue technology involves a series of systematic methods and tools aimed at improving the efficiency and safety of responding to fire accidents, including fire prevention, detection, alarm systems and emergency response measures. When a fire occurs, a quick and effective response is crucial to ensuring the safety of personnel. Fire rescue technology not only involves physical equipment such as fire trucks, water guns, etc., but also includes advanced monitoring and communication technologies for real-time transmission of fire scene information to rescue teams, which can more accurately formulate rescue strategies, including fire simulation, escape route optimization, and training and drills for rescue personnel.

[0003] Among them, the method for locating trapped persons in fire is a technology specifically used to quickly and accurately determine the position of trapped persons in fire situations. The key purpose of this method is to optimize the allocation of rescue resources, shorten the rescue time, thereby increasing the survival rate and reducing injuries. This technology relies on a variety of sensors to detect the vital signs, sounds or biological reactions of trapped persons, as well as combining building information and fire scene dynamics to determine the position of trapped persons. By implementing this method, the rescue team can perform search and rescue operations more specifically, reduce blind searches, and improve rescue efficiency.

[0004] The existing technology relies on the single processing of multiple sensor data in fire rescue, and fails to fully combine different data sources for comprehensive analysis, resulting in a lack of dynamic tracking and abnormal warning of the life status of trapped persons when dealing with complex fire environments. The sound source positioning in the existing technology relies on basic acoustic feature analysis, and fails to achieve accurate sound source positioning and rescue signal recognition, resulting in positioning errors and waste of rescue resources in actual operations; due to the lack of effective combination of vital signs and sound source information, the existing technology shows certain limitations in resource allocation and priority determination, resulting in insufficient optimization of rescue strategies, affecting the overall rescue efficiency and effectiveness, and further leading to extended rescue time, excessive consumption of resources and reduced survival chances of trapped persons. In high-risk fire scenarios, the best rescue effect cannot be achieved. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a method and system for locating people trapped in a fire. By integrating sensor data and performing real-time analysis, more accurate recognition of vital signs and abnormal warnings can be achieved. The real-time collection of acoustic fluctuations and sound wave feature processing can be combined to further improve the positioning accuracy of trapped people. By calculating the sound source positioning coordinates, the allocation of rescue resources can be optimized, and efficient and targeted rescue strategies and priority allocations can be formulated, which can significantly improve rescue efficiency, reduce search time and resource waste, increase the survival probability of trapped people, and improve the overall rescue effect.

[0006] In order to solve the above-mentioned technical problems, the present invention provides the following technical solutions:

[0007] A method for locating persons trapped in a fire comprises the following steps:

[0008] Integrate heart rate sensors, body temperature sensors, and respiratory rate sensors into portable devices to collect vital sign data, which are then sent to a central processing unit via a wireless transmission mechanism for monitoring and analysis to obtain vital sign monitoring data;

[0009] According to the vital signs monitoring data, analyze the heart rate variability and body temperature fluctuation trends, and combine the respiratory rate fluctuation range to obtain vital signs status identification information;

[0010] Based on the vital sign status recognition information, real-time collection of acoustic fluctuations in the environment is performed, sound wave feature analysis is performed, target frequency fluctuations in background noise are identified, and an environmental acoustic data set is obtained;

[0011] Process the environmental acoustic data set, combine the identified sound wave features, perform frequency and waveform matching operations, identify the sound waves with rescue signal characteristics, and obtain the target rescue signal location information;

[0012] By analyzing the location information of the target rescue signal and combining the time difference and intensity difference of the sound wave propagation, the sound source positioning calculation is performed to determine the direction and distance of the sound source, and the sound source positioning coordinates of the trapped person are obtained;

[0013] Based on the vital signs status identification information and the sound source positioning coordinates of the trapped persons, rescue resources are prioritized, rescue action strategies are formulated, the allocation order and urgency of rescue resources are optimized, and rescue priority and action strategy guidelines are established.

[0014] The following is a further optimization of the above technical solution by the present invention:

[0015] The vital signs monitoring data includes heart rate, body temperature, and respiratory rate; the vital signs status identification information includes heart rate variability, body temperature fluctuations, and respiratory rate changes; the environmental acoustic data set includes sound wave amplitude, sound wave frequency, and noise characteristics; the target rescue signal location information includes sound source location, frequency characteristics, and matching results; the trapped person sound source positioning coordinates include sound source direction, sound source distance, and propagation time difference; the rescue priority and action strategy guidelines include priority division, resource allocation order, and urgency.

[0016] Further optimization: Integrate heart rate sensors, body temperature sensors, and respiratory rate sensors into portable devices to collect vital sign data, and send them to the central processing unit through a wireless transmission mechanism for monitoring and analysis. The specific steps for obtaining vital sign monitoring data are as follows:

[0017] Integrate heart rate sensors, body temperature sensors, and respiratory rate sensors into portable devices, adjust the directions of multiple sensors to match the user's activity posture, configure the spacing to avoid signal interference, and obtain sensor configuration status information;

[0018] According to the sensor configuration status information, multiple sensors are started and calibrated for environmental matching, the sampling frequency is dynamically adjusted to match the environmental noise, key vital signs data including heart rate, body temperature and respiratory rate are collected, and vital signs data collection information is obtained;

[0019] According to the vital signs data collection information, the size and encryption level of the data packet are adjusted through the built-in wireless configuration, the matching transmission frequency is set, the data is sent to the central processing unit for parsing, and data monitoring and analysis are performed to obtain vital signs monitoring data.

[0020] Further optimization: Based on the vital signs monitoring data, analyze the heart rate variability and body temperature fluctuation trends, and combine the respiratory rate fluctuation range to obtain the vital signs status identification information. The specific steps are as follows:

[0021] Based on the vital signs monitoring data, the heart rate data is continuously collected, the time interval of data collection is kept consistent, and a heart rate data sequence is generated;

[0022] Based on the heart rate data sequence, synchronously collect body temperature and respiratory rate, adjust the collection equipment and match the collection frequency of heart rate data to obtain synchronous vital sign data;

[0023] Based on synchronized vital signs data, trend analysis is performed on heart rate variability, body temperature fluctuations, and respiratory rate fluctuations. Sliding window technology is used to optimize the processing speed and accuracy of data streams. Through real-time data stream analysis, abnormal fluctuation events are identified and recorded to obtain vital signs status identification information.

[0024] Further optimization: Based on the vital sign status recognition information, real-time collection of acoustic fluctuations in the environment is performed, sound wave feature analysis is performed, and target frequency fluctuations in background noise are identified. The specific steps for obtaining the environmental acoustic data set are as follows:

[0025] Based on the vital sign status recognition information, configure the environmental sound collection equipment, adjust the sensitivity and response range of the equipment, automatically adjust and optimize the sensitivity of the environmental sound, collect the sound data in the environment, and obtain the original acoustic data set;

[0026] Based on the original acoustic data set, adjust the acquisition parameters and optimize the capture of acoustic wave data, extract and record the amplitude and frequency of the sound waves, adjust the signal processing components, extract and organize the key acoustic features, and obtain characteristic acoustic data;

[0027] Using characteristic acoustic data, background noise and target frequencies are dynamically separated, sound wave analysis is adjusted and frequency fluctuations are identified and recorded. By adjusting processing parameters, data analysis of sound waves is optimized to generate an environmental acoustic data set.

[0028] Further optimization: Process the environmental acoustic data set, combine the identified sound wave features, perform frequency and waveform matching operations, identify the sound waves of the rescue signal characteristics, and obtain the target rescue signal location information in the following steps:

[0029] According to the environmental acoustic data set, adjust the direction and sensitivity of the microphone, filter the acoustic data and isolate the environmental noise, and obtain the preliminary screening results of the acoustic data;

[0030] Using the preliminary screening results of acoustic data, frequency analysis is performed on the target data segment. By adjusting the threshold and response time of the frequency filter, the rescue signal characteristics are matched and identified, and the sound wave characteristics are matched to obtain the sound wave recognition results.

[0031] According to the sound wave recognition results, the direction and intensity data of sound wave propagation are analyzed, the coordinates of the sound source are calculated, the sound source is located through the analysis of sound intensity and direction, the position of the rescue signal is determined, and the target rescue signal position information is generated.

[0032] Further optimization: By analyzing the location information of the target rescue signal, combined with the time difference and intensity difference of sound wave propagation, the sound source positioning calculation is performed to determine the direction and distance of the sound source. The specific steps for obtaining the sound source positioning coordinates of the trapped person are as follows:

[0033] According to the location information of the target rescue signal, the positioning equipment is configured, the receiving frequency and signal sensitivity are adjusted, the received rescue signal is monitored in real time, the propagation time difference and intensity difference of the sound wave are synchronously recorded, and the sound wave propagation data set is obtained;

[0034] Based on the sound wave propagation data set, analyze the time difference and intensity difference and identify the direction of the sound source, adjust and correct the data collection points, adjust the calculation of the sound source direction through data comparison and analysis, provide a preliminary estimate of the sound source distance, and obtain the basic positioning data of the sound source;

[0035] Using the basic sound source positioning data, the Doppler effect algorithm is adopted, combined with the real-time sound wave propagation model to adjust and optimize parameters. By modifying the variables in the model and matching the sound wave characteristics of the environment, the distance and direction calculation of the sound source are refined to generate the sound source positioning coordinates of the trapped person.

[0036] Further optimization: The formula of the Doppler effect algorithm is: ;

[0037] in, is the received frequency, is the transmitting frequency, is the speed of sound, is the speed at which the receiver moves toward the sound source, is the speed at which the sound source moves toward the receiver, is the ambient temperature, For the corresponding humidity, is the environmental adjustment factor.

[0038] Further optimization: Based on the vital signs status identification information and the sound source location coordinates of the trapped persons, prioritize rescue resources, formulate rescue action strategies, optimize the allocation order and urgency of rescue resources, and establish the rescue priority and action strategy guidelines. The specific steps are as follows:

[0039] According to the trapped person's sound source location coordinates, collect and organize vital sign status identification information and sound source location coordinates, perform preliminary logical grouping on the data, prioritize them based on the urgency of vital signs and the spatial distance of the sound source, and obtain preliminary rescue resource priority;

[0040] According to the initial rescue resource priority, formulate resource allocation and timeline for each rescue mission, adjust resource allocation and match the mission requirements with differentiated priorities, and form a rescue action strategy;

[0041] According to the rescue action strategy, implement resource scheduling and optimization measures, manage the dynamic scheduling and equipment use of rescue teams, optimize emergency response efficiency and resource utilization, and establish rescue priorities and action strategy guidelines.

[0042] A fire trapped person positioning system, used to implement the fire trapped person positioning method, the system comprises:

[0043] The vital sign analysis module integrates the heart rate sensor, body temperature sensor, and respiratory rate sensor into the portable device to capture the vital sign data. By comparing the value range, it performs matching analysis on the vital sign data to obtain the vital sign status information.

[0044] The wireless data transmission module integrates multiple vital sign values ​​based on vital sign status information, identifies differentiated source data through value consistency comparison, and obtains integrated vital sign information;

[0045] The acoustic wave feature capture module integrates vital signs information, extracts the acoustic wave frequency and amplitude, performs feature screening of acoustic wave signals, and obtains acoustic wave feature information by combining the vital signs information comparison results;

[0046] The sound source positioning and identification module compares the sound wave propagation time difference and intensity difference based on the sound wave characteristic information, combines the sound wave direction and distance data, compares the differentiated sound wave propagation paths, and constructs the sound source positioning coordinates of the trapped person;

[0047] The rescue strategy formulation module sorts the priorities of differentiated rescue resources based on the sound source positioning coordinates and integrated vital signs information of the trapped persons, and prioritizes multiple types of resources based on vital signs and positioning information to establish rescue priorities and action strategy guidelines.

[0048] The present invention adopts the above technical solution and has the following beneficial effects:

[0049] 1. The present invention integrates multiple sensor data such as heart rate, body temperature, respiratory rate, etc., and performs real-time analysis operations to effectively identify the status of vital signs, thereby providing a method for dynamically tracking the life status of people trapped in a fire. The method combines multiple vital sign data to achieve more accurate status identification and abnormal situation warnings, and combines real-time collection and analysis of acoustic fluctuations to further enhance the accuracy of locating trapped people by identifying and processing the sound wave characteristics in specific rescue signals.

[0050] 2. The present invention obtains and calculates the location coordinates of the sound source through processing the amplitude and frequency parameters of the sound waves, optimizes the allocation of rescue resources, and formulates rescue strategies and priority allocations by combining the vital signs status identification information with the sound source location coordinates, making the rescue operation more efficient and targeted. This precise analysis and resource optimization strategy effectively improves the rescue efficiency, reduces the search time and resource waste, increases the survival probability of the trapped persons, and significantly improves the rescue effect.

[0051] The present invention is further described below in conjunction with the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A schematic diagram of the working process of an embodiment of the present invention;

[0053] Figure 2 is a detailed flow chart of step S1 in an embodiment of the present invention;

[0054] Figure 3 is a detailed flow chart of step S2 in an embodiment of the present invention;

[0055] Figure 4 is a detailed flow chart of step S3 in an embodiment of the present invention;

[0056] Figure 5 is a detailed flow chart of step S4 in an embodiment of the present invention;

[0057] Figure 6 is a detailed flow chart of step S5 in an embodiment of the present invention;

[0058] Figure 7 is a detailed flow chart of step S6 in an embodiment of the present invention;

[0059] Figure 8 The figure is a flow chart of a system for locating persons trapped in a fire according to an embodiment of the present invention. DETAILED DESCRIPTION

[0060] See also Figure 1 , a method for locating persons trapped in a fire, comprising the following steps:

[0061] S1: Integrate heart rate sensor, body temperature sensor, and respiratory rate sensor into portable devices to collect vital sign data, and send them to the central processing unit through a wireless transmission mechanism for monitoring and analysis to obtain vital sign monitoring data;

[0062] S2: Based on the vital signs monitoring data, analyze the heart rate variability and body temperature fluctuation trends, and combine the respiratory rate fluctuation range to obtain vital signs status identification information;

[0063] S3: Based on the vital sign status recognition information, real-time acquisition of acoustic fluctuations in the environment is performed, sound wave feature analysis is performed, target frequency fluctuations in background noise are identified, and an environmental acoustic data set is obtained;

[0064] S4: Process the environmental acoustic data set, combine the identified sound wave features, perform frequency and waveform matching operations, identify the sound waves of the rescue signal characteristics, and obtain the target rescue signal location information;

[0065] S5: By analyzing the location information of the target rescue signal, combined with the time difference and intensity difference of the sound wave propagation, the sound source positioning calculation is performed to determine the direction and distance of the sound source, and the sound source positioning coordinates of the trapped person are obtained;

[0066] S6: Based on the vital signs status identification information and the sound source positioning coordinates of the trapped persons, prioritize the rescue resources, formulate rescue action strategies, optimize the allocation order and urgency of rescue resources, and establish rescue priority and action strategy guidelines.

[0067] The vital signs monitoring data includes heart rate, body temperature, and respiratory rate; the vital signs status identification information includes heart rate variability, body temperature fluctuations, and respiratory rate changes; the environmental acoustic data set includes sound wave amplitude, sound wave frequency, and noise characteristics; the target rescue signal location information includes sound source location, frequency characteristics, and matching results; the trapped person sound source positioning coordinates include sound source direction, sound source distance, and propagation time difference; the rescue priority and action strategy guidelines include priority division, resource allocation order, and urgency.

[0068] like Figure 2 As shown, a heart rate sensor, a body temperature sensor, and a respiratory rate sensor are integrated into a portable device to collect vital sign data, which are sent to a central processing unit through a wireless transmission mechanism for monitoring and analysis. The specific steps for obtaining vital sign monitoring data are as follows:

[0069] S101: Integrate a heart rate sensor, a body temperature sensor, and a breathing rate sensor into a portable device, adjust the directions of multiple sensors to match the user's activity posture, configure the spacing to avoid signal interference, and obtain sensor configuration status information.

[0070] In this embodiment, the specific execution process of S101 is as follows: integrate the heart rate sensor, body temperature sensor, and respiratory rate sensor into the portable device. In the design stage, first determine the functional characteristics of each sensor and its spatial position in the device. In order to ensure that the sensor can accurately capture data when the user moves, the fixed point of each sensor is designed in detail to ensure that it can change position naturally with the user's activities without causing mutual interference; for example, the heart rate sensor is located on one side of the device, the body temperature sensor is installed on the part of the device that contacts the skin, and the respiratory rate sensor is set at a position close to the respiratory tract. By using non-metallic materials as sensor spacing materials, the electromagnetic interference caused by metal is effectively reduced. The direction of the sensor is finely adjusted so that it can accurately capture data under different user postures. For example, the heart rate sensor is rotated to keep it close to the heart area. After the design work is completed, a series of functional tests are performed to ensure that each sensor can work normally at the set position and direction, and there is no signal interference between each other. The sensor configuration status information is obtained. In order to evaluate the effectiveness of the sensor configuration, the device responsiveness score can be used. The formula calculates the overall responsiveness of the device under given user posture and environmental conditions. The results are obtained by processing the experimental data through regression analysis, ensuring the versatility and adaptability in different usage environments.

[0071] Device Responsiveness Rating The formula is: ;

[0072] in, Represents the signal quality score of the heart rate sensor; Represents the signal quality score of the body temperature sensor; Represents the signal quality score of the respiratory rate sensor, It is the adjusted weight coefficient, reflecting the importance of each sensor in the portable device.

[0073] S102: Based on the sensor configuration status information, multiple sensors are started and calibrated for environmental matching, the sampling frequency is dynamically adjusted to match the environmental noise, key vital signs data including heart rate, body temperature and respiratory rate are collected, and vital signs data collection information is obtained.

[0074] In this embodiment, the specific execution process of S102 is as follows: according to the sensor configuration status information, multiple sensor functions of the device are started. In the initialization stage, the sensor is first calibrated for environmental matching to ensure the compatibility of the sensor with the current environment; for example, if the user is in a high temperature environment, the sensitivity of the body temperature sensor is adjusted to avoid high readings. According to the environmental noise level, the sampling frequency of the sensor is dynamically adjusted, such as lowering the sampling frequency in noisy environments such as gyms to reduce the impact of noise and effectively collect key vital signs data; during the collection process, the device will monitor the heart rate, body temperature and respiratory rate data in real time to ensure the accuracy and reliability of the data and obtain vital signs data collection information.

[0075] S103: According to the vital sign data collection information, the size and encryption level of the data packet are adjusted through the built-in wireless configuration, the matching transmission frequency is set, the data is sent to the central processing unit for parsing, and the data is monitored and analyzed to obtain the vital sign monitoring data.

[0076] In this embodiment, the specific execution process of S103 is as follows: according to the vital signs data collection information, the data packet is optimized and processed. First, the size of the data packet is adjusted to adapt to different transmission requirements and save bandwidth. At the same time, the transmitted data is encrypted to ensure the privacy and security of user data. Through the built-in wireless module, the matching transmission frequency is dynamically set according to the network status to optimize the data transmission efficiency. After the data is sent to the central processing unit, the unit will conduct an in-depth analysis of the data and use advanced monitoring algorithms to analyze the data to ensure that health trends and potential health problems can be accurately extracted from the data, so as to achieve real-time and accurate acquisition of vital signs monitoring data.

[0077] like Figure 3As shown in the figure, according to the vital signs monitoring data, the steps of analyzing the heart rate variability and body temperature fluctuation trend and combining the respiratory rate fluctuation range to obtain the vital signs status identification information are as follows:

[0078] S201: Based on the vital sign monitoring data, continuously collect heart rate data, maintain a consistent time interval for data collection, and generate a heart rate data sequence.

[0079] In this embodiment, the specific execution process of S201 is as follows: based on the vital signs monitoring data, first configure the heart rate sensor for continuous acquisition to ensure the consistency of the data acquisition interval, set the specific time point of each acquisition through the software interface, such as collecting heart rate data once per second, thereby generating a continuous and evenly spaced heart rate data sequence, use time synchronization technology to ensure that the internal clock of the acquisition device is synchronized with the global standard time, avoid data deviations caused by time errors, and use the built-in data buffering mechanism to ensure that no heart rate data points are lost during the data transmission process, maintain data integrity, and generate a heart rate data sequence.

[0080] S202: Based on the heart rate data sequence, synchronously collect body temperature and respiratory rate, adjust the collection device and match the collection frequency of the heart rate data, and obtain synchronous vital sign data.

[0081] In this embodiment, the specific execution process of S202 is as follows: based on the heart rate data sequence, the synchronous acquisition of the body temperature and respiratory rate sensors is started at the same time. In order to match the acquisition frequency of the heart rate data, the hardware parameters of the body temperature and respiratory rate sensor, such as the sampling rate and sensitivity, are first adjusted to ensure synchronization with the output frequency of the heart rate sensor. Through the real-time monitoring software, the response time of each sensor is adjusted so that the acquisition points of the three vital signs data can be aligned at the same timestamp, thereby obtaining time-synchronized vital signs data. This process involves precise time control and data processing algorithms to ensure the consistency of the data in time sequence and the statistical comparability to obtain synchronized vital signs data.

[0082] S203: Based on the synchronized vital signs data, trend analysis is performed on heart rate variability, body temperature fluctuations, and respiratory rate fluctuations. The sliding window technology is applied to optimize the processing speed and accuracy of the data stream. Through real-time data stream analysis, abnormal fluctuation events are identified and recorded to obtain vital signs status identification information.

[0083] In this embodiment, the specific execution process of S203 is as follows: based on the synchronized vital signs data, first define the calculation method of heart rate variability, body temperature fluctuation and respiratory rate fluctuation, use the improved sliding window technology to set the window size and step size to optimize the processing speed and accuracy of the data stream, and calculate the standard deviation of the heart rate, the average deviation of the body temperature and the coefficient of variation of the respiratory rate within the set window, which are used as volatility measurement indicators. As the window slides, the volatility indicators are updated in real time, and abnormal fluctuation events are identified and recorded by setting thresholds. The volatility indicators not only provide real-time health status of vital signs, but also can track long-term trend changes of vital signs through continuous monitoring and obtain vital sign status identification information.

[0084] Considering the need for more detailed analysis of data fluctuations, a weighted vital sign volatility score was introduced formula: ;

[0085] in, Represents the standard deviation of heart rate data, which is used to evaluate the volatility of heart rate. Represents the average deviation of body temperature data and is used to evaluate the stability of body temperature. Represents the coefficient of variation of respiratory rate, which is used to evaluate the consistency of respiratory rate. are weight coefficients, corresponding to the importance assessment parameters of heart rate, body temperature and respiratory rate respectively. The weight coefficients are obtained based on historical data analysis to ensure that the influence of each parameter in the overall score is reasonable.

[0086] like Figure 4 As shown, based on the vital sign status recognition information, the real-time collection of acoustic fluctuations in the environment is performed, the sound wave feature analysis is performed, the target frequency fluctuations in the background noise are identified, and the steps for obtaining the environmental acoustic data set are as follows:

[0087] S301: Based on the vital sign status recognition information, configure the environmental sound collection device, adjust the sensitivity and response range of the device, automatically adjust and optimize the sensitivity of the environmental sound, collect the sound data in the environment, and obtain the original acoustic data set.

[0088] In this embodiment, the specific execution process of S301 is as follows: based on the vital sign status identification information, start to configure the installation and debugging of the environmental sound collection device, select the sound collection device suitable for the current environment, and adjust the microphone sensitivity and frequency response range of the device according to the sound type and intensity range that needs to be monitored; for example, if the monitoring environment is a hospital, a high-sensitivity microphone is required to capture weak sounds. If it is an industrial site, a microphone that can withstand high-decibel sounds is required. The gain control and filter settings of the microphone are adjusted through the software interface to adapt to the noise level in the environment, including turning on the dynamic range control function to automatically adjust the strength of the input signal to avoid overload and distortion. The device can capture environmental sounds more accurately and generate high-quality original acoustic data sets.

[0089] S302: Based on the original acoustic data set, adjust the acquisition parameters and optimize the capture of acoustic wave data, extract and record the amplitude and frequency of the sound waves, adjust the signal processing components, extract and organize key acoustic features, and obtain characteristic acoustic data.

[0090] In this embodiment, the specific execution process of S302 is as follows: based on the original acoustic data set, further optimize the capture efficiency of the sound wave data; adjust the acquisition parameters, such as sampling rate and bit depth, to ensure that the amplitude and frequency of the sound waves can be recorded in detail; the selection of the sampling rate depends on the frequency of the sound to be captured. For example, in order to capture high-frequency sounds, the sampling rate needs to be set higher. In the data capture stage, use signal processing components to filter out non-target sound waves and focus on the extraction of key acoustic features; use advanced digital signal processing algorithms, such as fast Fourier transform (FFT), to extract frequency and amplitude information from the sound wave data. The processing steps ensure that useful acoustic features are extracted from complex sound environments, and characteristic acoustic data is generated after sorting.

[0091] S303: Use characteristic acoustic data to dynamically separate background noise and target frequency, adjust sound wave analysis and identify and record frequency fluctuations, optimize sound wave data analysis by adjusting processing parameters, and generate an environmental acoustic data set.

[0092] In this embodiment, the specific execution process of S303 is as follows: using characteristic acoustic data, adopting dynamic separation technology to distinguish background noise from target frequency, setting parameters of the analysis model, such as the sensitivity and threshold of the separation algorithm, to ensure that the target sound can be effectively identified from the complex background, and by continuously adjusting the parameters of the sound wave analysis, such as the window size and step size, enhancing the model's ability to recognize frequency fluctuations, using time-frequency analysis technology to identify and record sound events that are significantly different from background noise. Sound events are caused by specific environmental factors, optimizing the analysis process of the sound wave data, and ultimately generating a detailed environmental acoustic data set.

[0093] To optimize the processing and analysis of acoustic wave data, a new acoustic wave analysis efficiency evaluation value has been introduced formula: ;

[0094] in, Represents the average amplitude of the target frequency in the sound wave data, Represents the total number of sampling points, used to normalize the amplitude value. Represents the standard deviation of the sound wave frequency and is used to evaluate the frequency fluctuation. and are adjustment coefficients, which are used to control the impact of amplitude and frequency fluctuations on the overall evaluation.

[0095] like Figure 5 As shown in FIG. 1 , the steps of processing the environmental acoustic data set, combining the identified sound wave features, performing frequency and waveform matching operations, identifying the sound waves of the rescue signal features, and obtaining the target rescue signal location information are as follows:

[0096] S401: According to the environmental acoustic data set, adjust the direction and sensitivity of the microphone, filter the acoustic data and isolate the environmental noise, and obtain preliminary filtering results of the acoustic data.

[0097] In this embodiment, the specific execution process of S401 is as follows: according to the environmental acoustic data set, the direction of the microphone is first adjusted to maximize the reception of the target sound and minimize the impact of environmental noise. The physical or electronic direction of the microphone is controlled through the software interface to make it more sensitive to the direction of the key sound source, and the sensitivity of the microphone is adjusted to achieve the best sound capture effect by real-time monitoring of the ambient sound and adjusting the input gain; high-pass and low-pass filters are used to eliminate irrelevant noise outside the frequency range, such as traffic or industrial noise, and only retain frequency bands with potential information value. After the adjustment is completed, a preliminary screening of the sound data is performed to screen out sound clips with large background noise or insignificant sound, and obtain preliminary screening results of the acoustic data.

[0098] S402: Using the preliminary screening results of the acoustic data, perform frequency analysis on the target data segment, match and identify the rescue signal characteristics by adjusting the threshold and response time of the frequency filter, match the sound wave characteristics, and obtain the sound wave recognition result.

[0099] In this embodiment, the specific execution process of S402 is as follows: using the preliminary screening results of acoustic data, further in-depth analysis of the target sound data segment, using advanced frequency analysis tools, detailed frequency analysis of the screened data, and identifying the frequency components of various sounds; according to preset rescue signal characteristics, such as specific frequency patterns and time series, adjust the threshold and response time of the frequency filter to accurately match the rescue signal, and through technical adjustments, it is possible to accurately identify the characteristics of the rescue signal from a complex acoustic background and match the sound wave characteristics; finally, through a series of processing and analysis, the sound wave recognition result is obtained.

[0100] S403: According to the sound wave recognition result, the direction and intensity data of the sound wave propagation are analyzed, the coordinates of the sound source are calculated, the sound source is located by analyzing the sound intensity and direction, the position of the rescue signal is determined, and the target rescue signal position information is generated.

[0101] In this embodiment, the specific execution process of S403 is as follows: according to the sound wave recognition results, the sound wave propagation direction and intensity are analyzed, and the sound wave propagation model and directional algorithm are used to analyze the propagation path and intensity changes of the sound waves in the collected sound data; data is collected through a multi-microphone array, and beamforming technology is used to enhance the sound wave signal from the target direction, and the triangulation method is further used to combine the propagation speed of the sound wave and the sound intensity change to calculate the coordinates of the sound source. The analysis results help to accurately locate the source of the rescue signal, and finally generate the target rescue signal location information.

[0102] In order to optimize the accuracy of sound source localization, a new sound source localization efficiency evaluation result is introduced formula: ;

[0103] in, Represents the maximum sound intensity collected from multiple directions. Represents the average distance from the sound source to the microphone array and is used to normalize the sound intensity value. Represents the angular difference between the sound source and the center line of the microphone array, which is used to determine the accuracy of the sound source direction. and are adjustment coefficients that control the weights of sound intensity and angle difference in the positioning algorithm.

[0104] like Figure 6 As shown in the figure, by analyzing the location information of the target rescue signal, combining the time difference and intensity difference of the sound wave propagation, the sound source positioning calculation is performed to determine the direction and distance of the sound source, and the steps for obtaining the sound source positioning coordinates of the trapped person are as follows:

[0105] S501: According to the location information of the target rescue signal, configure the positioning device, adjust the receiving frequency and signal sensitivity, monitor the received rescue signal in real time, synchronously record the propagation time difference and intensity difference of the sound wave, and obtain the sound wave propagation data set.

[0106] In this embodiment, the specific execution process of S501 is as follows: according to the target rescue signal location information, first configure the positioning device, select a positioning device with high sensitivity and adjustable receiving frequency to meet the rescue signal reception needs in different environments, adjust the receiving frequency to match the expected signal frequency in the current environment through the interface settings, and adjust the gain of the signal amplifier to ensure the reception quality of the rescue signal. Use high-precision time synchronization technology to ensure that the sound wave signals received from different directions can accurately record their propagation time difference. Use signal strength detection technology to record the intensity difference of the sound waves, thereby effectively capturing the dynamic characteristics of sound wave propagation. The data are stored and organized together as a sound wave propagation data set to provide detailed records of real-time monitoring for subsequent analysis.

[0107] S502: Based on the sound wave propagation data set, analyze the time difference and intensity difference and identify the direction of the sound source, adjust and correct the data collection points, adjust the calculation of the sound source direction through data comparison and analysis, provide a preliminary estimate of the sound source distance, and obtain the basic positioning data of the sound source.

[0108] In this embodiment, the specific execution process of S502 is as follows: based on the sound wave propagation data set, firstly, a detailed analysis of the time difference and the intensity difference is performed, and the advanced sound wave analysis software is used to compare the time and intensity of the data collected at different directions and distances, and the approximate direction of the sound source is identified. According to the analysis results, the data collection points are adjusted and corrected, and the layout of the sound wave receiving array is optimized to ensure the accuracy and consistency of the data. Through repeated data comparison and analysis, the calculation method of the sound source direction is further adjusted to improve its accuracy, which provides a preliminary estimate for the determination of the sound source distance, thereby obtaining the basic positioning data of the sound source.

[0109] S503: Using the basic sound source positioning data, the Doppler effect algorithm is adopted, and the real-time sound wave propagation model is combined to adjust and optimize the parameters. By modifying the variables in the model and matching the sound wave characteristics of the environment, the distance and direction calculation of the sound source are refined to generate the sound source positioning coordinates of the trapped person.

[0110] In this embodiment, the specific execution process of S503 is as follows: using the basic positioning data of the sound source, an improved Doppler effect algorithm is used to accurately calculate the distance and direction of the sound source. First, in combination with the real-time sound wave propagation model, the model parameters are adjusted and optimized to ensure that the model can accurately reflect the propagation characteristics of the sound waves in the current environment. By modifying the variables in the model, such as the sound wave velocity and the sound source movement speed, etc., to match the sound wave characteristics of the environment, the adjustment enables the Doppler effect algorithm to more accurately refine the calculation of the distance and direction of the sound source, thereby generating more accurate sound source positioning coordinates for the trapped person.

[0111] The formula of the Doppler effect algorithm is: ;

[0112] in, is the received frequency, is the transmitting frequency, is the speed of sound, is the speed at which the receiver moves toward the sound source, is the speed at which the sound source moves toward the receiver, is the ambient temperature, For the corresponding humidity, is the environmental adjustment factor.

[0113] The specific implementation process is as follows:

[0114] Get temperature based on real-time data from the on-site environment and relative humidity ,calculate value, the The value is determined by regression analysis of historical data, using Value to adjust the speed of sound Relative speed to the source and receiver and To adapt to environmental changes, the speed of sound According to the standard sound speed and environmental factors , , The frequency is recalculated in the Doppler effect algorithm using the adjusted sound speed and velocity values. , and finally generate more accurate sound source localization coordinates.

[0115] like Figure 7 As shown in the figure, according to the vital sign status identification information and the sound source positioning coordinates of the trapped persons, the rescue resources are prioritized, the rescue action strategy is formulated, the allocation order and urgency of the rescue resources are optimized, and the steps for establishing the rescue priority and action strategy guide are as follows:

[0116] S601: According to the sound source location coordinates of the trapped persons, collect and organize the vital signs status identification information and the sound source location coordinates, perform preliminary logical grouping on the data, prioritize them based on the urgency of the vital signs and the spatial distance of the sound source, and obtain preliminary rescue resource priority.

[0117] In this embodiment, the specific execution process of S601 is as follows: according to the sound source positioning coordinates of the trapped person, start collecting and organizing relevant vital sign status identification information and sound source positioning coordinate data, and through the data management system, perform preliminary logical grouping of the collected vital sign information and sound source coordinates, divide them according to geographical location and urgency, and prioritize them based on the urgency of vital signs (such as abnormal heart rate and body temperature changes) and the spatial distance of the sound source (such as the actual distance between the sound source and the nearest rescue team). Use data analysis tools to automatically calculate the urgency index of each trapped person, and combine it with their location information to generate a comprehensive score. Such a scoring mechanism ensures that rescue resources can be allocated first to individuals who need assistance most, and obtain preliminary rescue resource priority.

[0118] S602: Based on the initial rescue resource priority, formulate resource configuration and timeline for each rescue mission, adjust resource allocation and match the mission requirements with differentiated priorities, and form a rescue action strategy.

[0119] In this embodiment, the specific execution process of S602 is as follows: based on the preliminary rescue resource priority, start to formulate the resource allocation and timeline of each rescue mission, conduct a detailed assessment of each rescue team and equipment, and adjust resource allocation according to the demand characteristics of different rescue missions (such as urgency, geographical location and environmental conditions). For example, more serious situations may require more medical support and advanced equipment. Through the rescue management system, match the task requirements of differentiated priorities, optimize the configuration of personnel and equipment, and form a rescue action strategy to ensure that each task has a definite execution timeline and required resources, thereby improving the efficiency and effectiveness of the rescue operation.

[0120] S603: Implement resource scheduling and optimization measures based on rescue action strategies, manage the dynamic scheduling of rescue teams and equipment use, optimize emergency response efficiency and resource utilization, and establish rescue priorities and action strategy guidelines.

[0121] In this embodiment, the specific execution process of S603 is as follows: according to the rescue action strategy, implement resource scheduling and optimization measures, manage the dynamic scheduling of the rescue team, use the real-time data tracking system to monitor the location and status of the rescue team, ensure rapid response to emergencies, carefully plan and manage the use of equipment, adjust equipment allocation and maintenance plans according to actual usage, improve the efficiency of emergency response and resource utilization through optimization measures, establish rescue priorities and action strategy guidelines, and provide standardized operating procedures and decision support for future rescue operations.

[0122] In order to optimize the efficiency of rescue resource allocation, a new resource allocation efficiency evaluation result is introduced formula: ;

[0123] in, Represents the urgency score of the rescue mission, taking into account the urgency of vital sign data and the distance from the sound source. represents the distance from the rescue resource to the sound source, and the square term reflects the importance of the distance factor in resource allocation. Represents rescue response time, and its reciprocal is used to indicate the importance of response speed. and is the weight coefficient used to adjust the impact of urgency score and response time on resource allocation efficiency.

[0124] like Figure 8 As shown, the present invention also provides a fire trapped person positioning system, which is used to execute the fire trapped person positioning method, and the system comprises:

[0125] The vital sign analysis module integrates the heart rate sensor, body temperature sensor, and respiratory rate sensor into the portable device to capture vital sign data. By comparing the numerical ranges of multiple data, it performs matching analysis of heart rate, body temperature, and respiratory rate, and integrates multiple numerical comparison results in the matching analysis results to obtain vital sign status information;

[0126] The wireless data transmission module sends and receives data through a wireless transmission mechanism based on vital sign status information, integrates multiple vital sign values, determines the data comparison differences of differentiated sources by comparing the consistency of the integrated values, and obtains the integrated vital sign information;

[0127] The acoustic wave feature capture module captures acoustic wave signals in the environment based on the integration of vital signs information, extracts the frequency and amplitude parameters of the acoustic wave, performs feature screening on the screened acoustic wave signals, and obtains acoustic wave feature information by combining the comparison results with vital signs information;

[0128] The sound source positioning and identification module is based on the sound wave feature information. By calculating the difference in the propagation path of the sound wave, the sound wave propagation time difference and intensity difference are compared. By combining the direction and distance data of the sound wave, the propagation path of the differentiated sound wave is compared to construct the sound source positioning coordinates of the trapped person.

[0129] The rescue strategy formulation module is based on the sound source positioning coordinates of the trapped persons and the integrated vital signs information. Through the correlation analysis of the positioning coordinates and vital signs data, it ranks the priorities of differentiated rescue resources in sequence, combines the vital signs and positioning information, prioritizes multiple types of resources, and establishes rescue priorities and action strategy guidelines.

[0130] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for locating persons trapped in a fire, characterized in that: The following steps are involved: Integrate heart rate sensors, body temperature sensors, and respiratory rate sensors into portable devices to collect vital sign data, which are then sent to a central processing unit via a wireless transmission mechanism for monitoring and analysis to obtain vital sign monitoring data; According to the vital signs monitoring data, analyze the heart rate variability and body temperature fluctuation trends, and combine the respiratory rate fluctuation range to obtain vital signs status identification information; Based on the vital sign status recognition information, real-time collection of acoustic fluctuations in the environment is performed, sound wave feature analysis is performed, target frequency fluctuations in background noise are identified, and an environmental acoustic data set is obtained; Process the environmental acoustic data set, combine the identified sound wave features, perform frequency and waveform matching operations, identify the sound waves with rescue signal characteristics, and obtain the target rescue signal location information; By analyzing the location information of the target rescue signal and combining the time difference and intensity difference of the sound wave propagation, the sound source positioning calculation is performed to determine the direction and distance of the sound source, and the sound source positioning coordinates of the trapped person are obtained; According to the vital signs status identification information and the sound source location coordinates of the trapped persons, rescue resources are prioritized, rescue action strategies are formulated, the allocation order and urgency of rescue resources are optimized, and rescue priority and action strategy guidelines are established; The vital sign monitoring data includes heart rate, body temperature, and respiratory rate; the vital sign status identification information includes heart rate variability, body temperature fluctuation, and respiratory rate change; the environmental acoustic data set includes sound wave amplitude, sound wave frequency, and noise characteristics; The target rescue signal location information includes the sound source location, frequency characteristics, and matching results; the trapped person sound source location coordinates include the sound source direction, sound source distance, and propagation time difference; the rescue priority and action strategy guide include priority division, resource allocation order, and urgency; Integrate heart rate sensors, body temperature sensors, and respiratory rate sensors into portable devices to collect vital sign data, which are then sent to a central processing unit via a wireless transmission mechanism for monitoring and analysis. The specific steps for obtaining vital sign monitoring data are as follows: Integrate heart rate sensors, body temperature sensors, and respiratory rate sensors into portable devices, adjust the directions of multiple sensors to match the user's activity posture, configure the spacing to avoid signal interference, and obtain sensor configuration status information; According to the sensor configuration status information, multiple sensors are started and calibrated for environmental matching, the sampling frequency is dynamically adjusted to match the environmental noise, key vital signs data including heart rate, body temperature and respiratory rate are collected, and vital signs data collection information is obtained; According to the vital signs data collection information, the size and encryption level of the data packet are adjusted through the built-in wireless configuration, the matching transmission frequency is set, the data is sent to the central processing unit for parsing, and data monitoring and analysis are performed to obtain vital signs monitoring data.

2. The method for locating persons trapped in a fire according to claim 1, characterized in that: According to the vital signs monitoring data, the steps of analyzing the heart rate variability and body temperature fluctuation trend and combining the respiratory rate fluctuation range to obtain the vital signs status identification information are as follows: Based on the vital signs monitoring data, the heart rate data is continuously collected, the time interval of data collection is kept consistent, and a heart rate data sequence is generated; Based on the heart rate data sequence, synchronously collect body temperature and respiratory rate, adjust the collection equipment and match the collection frequency of heart rate data to obtain synchronous vital sign data; Based on synchronized vital signs data, trend analysis is performed on heart rate variability, body temperature fluctuations, and respiratory rate fluctuations. Sliding window technology is used to optimize the processing speed and accuracy of data streams. Through real-time data stream analysis, abnormal fluctuation events are identified and recorded to obtain vital signs status identification information.

3. The method for locating persons trapped in a fire according to claim 2, characterized in that: Based on the vital sign status recognition information, the real-time collection of acoustic fluctuations in the environment is carried out, the acoustic wave characteristics are analyzed, and the target frequency fluctuations in the background noise are identified. The specific steps to obtain the environmental acoustic data set are as follows: Based on the vital sign status recognition information, configure the environmental sound collection equipment, adjust the sensitivity and response range of the equipment, automatically adjust and optimize the sensitivity of the environmental sound, collect the sound data in the environment, and obtain the original acoustic data set; Based on the original acoustic data set, adjust the acquisition parameters and optimize the capture of acoustic wave data, extract and record the amplitude and frequency of the sound waves, adjust the signal processing components, extract and organize the key acoustic features, and obtain characteristic acoustic data; Using characteristic acoustic data, background noise and target frequencies are dynamically separated, sound wave analysis is adjusted and frequency fluctuations are identified and recorded. By adjusting processing parameters, data analysis of sound waves is optimized to generate an environmental acoustic data set.

4. The method for locating persons trapped in a fire according to claim 3, characterized in that: The specific steps of processing the environmental acoustic data set, combining the identified sound wave features, performing frequency and waveform matching operations, identifying the sound waves of the rescue signal features, and obtaining the target rescue signal location information are as follows: According to the environmental acoustic data set, adjust the direction and sensitivity of the microphone, filter the acoustic data and isolate the environmental noise, and obtain the preliminary screening results of the acoustic data; Using the preliminary screening results of acoustic data, frequency analysis is performed on the target data segment. By adjusting the threshold and response time of the frequency filter, the rescue signal characteristics are matched and identified, and the sound wave characteristics are matched to obtain the sound wave recognition results. According to the sound wave recognition results, the direction and intensity data of sound wave propagation are analyzed, the coordinates of the sound source are calculated, the sound source is located through the analysis of sound intensity and direction, the position of the rescue signal is determined, and the target rescue signal position information is generated.

5. The method for locating persons trapped in a fire according to claim 4, characterized in that: By analyzing the location information of the target rescue signal, combined with the time difference and intensity difference of sound wave propagation, the sound source positioning calculation is performed to determine the direction and distance of the sound source. The steps to obtain the sound source positioning coordinates of the trapped person are as follows: According to the location information of the target rescue signal, the positioning equipment is configured, the receiving frequency and signal sensitivity are adjusted, the received rescue signal is monitored in real time, the propagation time difference and intensity difference of the sound wave are synchronously recorded, and the sound wave propagation data set is obtained; Based on the sound wave propagation data set, analyze the time difference and intensity difference and identify the direction of the sound source, adjust and correct the data collection points, adjust the calculation of the sound source direction through data comparison and analysis, provide a preliminary estimate of the sound source distance, and obtain the basic positioning data of the sound source; Using the basic sound source positioning data, the Doppler effect algorithm is adopted, combined with the real-time sound wave propagation model to adjust and optimize parameters. By modifying the variables in the model and matching the sound wave characteristics of the environment, the distance and direction calculation of the sound source are refined to generate the sound source positioning coordinates of the trapped person.

6. The method for locating persons trapped in a fire according to claim 5, characterized in that: The formula of the Doppler effect algorithm is: Among them, f ′ is the received frequency, f is the transmitting frequency, v is the speed of sound, v d is the speed at which the receiver moves toward the sound source, v s is the speed at which the sound source moves toward the receiver, T is the ambient temperature, H is the corresponding humidity, and k is the environmental adjustment coefficient.

7. The method for locating persons trapped in a fire according to claim 6, characterized in that: According to the vital signs status identification information and the sound source location coordinates of the trapped persons, the rescue resources are prioritized, the rescue action strategy is formulated, the allocation order and urgency of the rescue resources are optimized, and the steps to establish the rescue priority and action strategy guide are as follows: According to the trapped persons' sound source location coordinates, collect and organize vital signs status identification information and sound source location coordinates, perform preliminary logical grouping on the data, prioritize them based on the urgency of vital signs and the spatial distance of the sound source, and obtain preliminary rescue resource priorities; According to the initial rescue resource priority, formulate resource allocation and timeline for each rescue mission, adjust resource allocation and match the mission requirements with differentiated priorities, and form a rescue action strategy; Based on the rescue action strategy, implement resource scheduling and optimization measures, manage the dynamic scheduling and equipment use of rescue teams, optimize emergency response efficiency and resource utilization, and establish rescue priorities and action strategy guidelines.

8. A system for locating persons trapped in a fire, used to implement the method for locating persons trapped in a fire according to claim 7, characterized in that: The system includes: The vital sign analysis module integrates the heart rate sensor, body temperature sensor, and respiratory rate sensor into the portable device to capture the vital sign data. By comparing the value range, it performs matching analysis on the vital sign data to obtain the vital sign status information. The wireless data transmission module integrates multiple vital sign values ​​based on vital sign status information, identifies differentiated source data through value consistency comparison, and obtains integrated vital sign information; The acoustic wave feature capture module integrates vital signs information, extracts the acoustic wave frequency and amplitude, performs feature screening of acoustic wave signals, and obtains acoustic wave feature information by combining the vital signs information comparison results; The sound source positioning and identification module compares the sound wave propagation time difference and intensity difference based on the sound wave characteristic information, combines the sound wave direction and distance data, compares the differentiated sound wave propagation paths, and constructs the sound source positioning coordinates of the trapped person; The rescue strategy formulation module sorts the priorities of differentiated rescue resources based on the sound source positioning coordinates of the trapped persons and the integrated vital signs information. It prioritizes multiple types of resources based on the vital signs and positioning information and establishes rescue priorities and action strategy guidelines.

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