Safety wearable device and system based on biosensing and human body state monitoring

Abstract

The invention discloses a safety wearable device and system based on biosensing and human body state monitoring, and relates to the technical field of intelligent wearable devices. In order to solve the problems that traditional safety protection measures often depend on self-perception and judgment of workers, the mode has large limitation, and potential safety risks cannot be accurately monitored and early warned in real time. Safety wearable equipment based on biosensing and human body state monitoring comprises intelligent equipment, the intelligent equipment is composed of a safety bracelet, a safety helmet, a safety waistband, safety shoes and a safety vest, vital signs of workers are monitored in real time, and construction environment data are recorded; when an abnormal condition is detected, the intelligent equipment can give an alarm in time, so that a worker and a monitoring center can take emergency measures, and a powerful guarantee is provided for the health and safety of the worker through real-time, comprehensive and intelligent data acquisition, analysis and early warning as well as efficient and stable data transmission and remote supervision control.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent wearable devices, and in particular to a safe wearable device and system based on biosensing and human body status monitoring. Background Art

[0002] Safety has always been one of the most important issues in the construction process, especially in the field of electromechanical installation. Electromechanical installation construction usually takes place inside building structures and underground spaces, including but not limited to computer rooms, subway tunnels, laboratories, tunnel galleries and other environments. These special working environments have a series of potential risk factors, including low oxygen content and limited communications, which pose a major hidden danger to the safety of construction workers. The working environment in the field of electromechanical installation construction is complex and changeable, and safety issues are particularly important.

[0003] Traditional safety protection measures often rely on workers’ self-perception and judgment, which has great limitations and cannot monitor and warn potential safety risks in real time and accurately. Low oxygen levels are a common problem in underground construction. In a closed space, oxygen levels may be insufficient, causing workers to suffer from hypoxia, dizziness, or even loss of consciousness. This may occur without adequate warning mechanisms, endangering the lives of workers. At the same time, due to the special nature of the building structure, the transmission of communication signals in underground space is often limited, which means that in an emergency, workers may not be able to contact rescuers or monitoring centers in time, increasing the risk of accidents. Summary of the invention

[0004] The purpose of the present invention is to provide a safety wearable device and system based on biosensing and human body status monitoring, which provides strong protection for the health and safety of workers through real-time, comprehensive and intelligent data collection, analysis and early warning, as well as efficient and stable data transmission and remote supervision and control, while improving production safety and production efficiency, so as to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: Safety wearable devices based on biosensing and human status monitoring include smart devices, which are composed of safety bracelets, safety helmets, safety belts, safety shoes and safety vests. The smart devices are worn on the workers' heads, body parts and feet to monitor the workers' vital signs in real time, including key parameters such as heart rate, respiratory rate, oxygen content and body posture, and issue alarms in time when abnormal conditions are detected. At the same time, they record construction environment data and interact with base stations for data.

[0006] The present invention provides another technical solution, a safety system based on biosensing and human body status monitoring, comprising: A data acquisition unit is used to obtain the biosensor data and human body status information data of the workers wearing the safety wearable equipment in real time, and to collect the environmental parameters of the workers' environment in real time; The main station communication unit is used to build a signal interaction channel between each safety wearable device and the base station, and transmit the collected worker biosensor data, human body status information data and environmental parameters to the main station supervision unit; The master station monitoring unit is used to obtain the data transmitted by the data acquisition unit based on the signal interaction channel, monitor and warn of abnormal conditions of the acquired data, and remotely monitor and control the safety wearable device based on the judgment and warning results.

[0007] Furthermore, the data acquisition unit comprises: Human body parameter acquisition module, used to monitor and collect physiological parameters of workers wearing safety wearable devices; The construction environment acquisition module is used to monitor and collect environmental parameters of the environment in which workers wearing safety wearable devices are located in real time; The abnormal situation warning module is used to judge whether there are abnormalities in the workers and their environment based on the collected physiological parameters and environmental parameters, and to issue a warning signal based on the judgment results and relevant instructions obtained from the main station supervision unit.

[0008] Furthermore, the abnormal situation warning module specifically includes: A threshold judgment mechanism is preset, and the acquired environmental parameters are compared with the normal environmental parameter thresholds to determine whether the worker's environment is normal; Determine the special working environment described by the worker by using environmental parameters that exceed or fall below normal parameter thresholds, and adjust the safety physiological parameter thresholds based on the special working environment; Compare the physiological parameters collected in real time with the preset safety physiological parameter thresholds, and issue an early warning when the physiological parameters collected in real time exceed the thresholds; The parameter types of the physiological parameters exceeding the threshold are extracted, and the abnormal state of the worker is determined based on the parameter types combined with the abnormal environmental parameters.

[0009] Furthermore, the abnormal state of the worker is determined based on the parameter type combined with the environmental abnormality parameters, including: Construct a linear regression model, input the acquired physiological parameters of the workers into the linear regression model for calculation, and obtain the predicted physiological parameters of the workers; Compare the actually measured physiological parameters of the worker with the predicted physiological parameters of the worker, and determine whether the burn exceeds a preset difference threshold based on the comparison result, and if so, consider that an abnormal situation exists; Once an abnormal state is detected, the alarm mechanism is triggered immediately and relevant information of the abnormal state is recorded, including time, location and abnormal type.

[0010] Furthermore, the data acquisition unit also includes dynamically adjusting the sampling frequency of the safety wearable device according to actual needs, specifically: Monitor the data changes corresponding to the parameter type of each physiological parameter in real time during each monitoring cycle; At the end of the monitoring period, obtaining the data change amplitude of each parameter type of each physiological parameter in the current monitoring period; A physiological parameter retrieval time interval of a target physiological parameter type is set for the next monitoring period according to the data variation amplitude of the parameter type of each physiological parameter.

[0011] Furthermore, the master station communication unit comprises: Base station construction module, used to build communication base stations, including external base stations, fixed base stations and mobile base stations; An interactive channel building module is used to establish a signal interactive channel between an external base station and a fixed base station, between a fixed base station and a mobile base station, and between a mobile base station and a safety wearable device; The interactive channel supervision module is used to monitor the status data of the communication connection between the signal interactive channels in real time and determine the data transmission efficiency of the signal interactive channels.

[0012] Furthermore, the master station supervision unit includes: A data acquisition module, used for receiving worker physiological parameters, environmental parameters and positioning data from a data acquisition unit based on a signal interaction channel; A data processing module is used to perform standardization processing on the received worker physiological parameters, environmental parameters and positioning data to obtain standard physiological parameter data, standard environmental parameter data and standard positioning data; The abnormality monitoring module is used to retrieve the historical data related to the workers according to the processed standardized data, analyze the trend of the workers' vital signs in combination with the historical data, determine whether the workers have abnormal conditions, and generate corresponding processing instructions based on the abnormality degree of the abnormal conditions; The personnel supervision module is used to supervise the behavior and working status of workers wearing safety wearable equipment; The device monitoring module is used to monitor the operating status of safety wearable devices.

[0013] Furthermore, the personnel supervision module determines whether there are any abnormal conditions among the workers, specifically: By real-time monitoring of the physiological parameters and environmental parameters of workers wearing safety wearable devices, the working status and health status of workers can be evaluated; Obtaining a plurality of behavioral sample data of the worker based on the working status and health status of the worker; The worker's blinking frequency, movement pause frequency, heart rate acceleration change frequency and behavioral habit weight are extracted from each behavioral sample data; Identify the extracted multiple parameters and obtain identification results; The abnormal coefficient of the worker during work is calculated based on the worker's blinking frequency, action pause frequency, heart rate acceleration change frequency and behavioral habit weight in each behavior sample data and the identification result of each parameter; Confirm whether the abnormality coefficient is greater than a preset coefficient. If so, obtain the driver's location data based on the safety wearable device worn by the worker. Otherwise, confirm that the worker is not abnormal. According to the abnormal results, reminders and warning messages are sent to the safety wearable devices worn by the workers to guide the workers to take corresponding measures.

[0014] Furthermore, the device supervision module supervises the safety wearable device, specifically: Monitor the battery power information of safety wearable devices in real time to determine the total capacity of the battery and the current battery power percentage; Determine the energy consumption of each sensor in the safety wearable device at a preset frequency per hour, and calculate the battery life based on the energy consumption of each sensor at the preset frequency per hour; Correcting the battery life of the battery based on the sampling frequency adjustment result of the safety wearable device of the data acquisition unit; When the current battery power percentage is less than 20%, all power saving measures are taken, including reducing the alarm remaining frequency, reducing the detection frequency and switching to energy saving mode; When the current battery power percentage is between 20% and 50%, only measures of reducing the alarm residual frequency and reducing the detection frequency are taken; When the current battery power percentage is 50% or above, no power saving measures are taken.

[0015] Compared with the prior art, the present invention has the following beneficial effects: Smart devices can monitor workers' vital signs in real time and record data on the construction environment. When abnormal conditions are detected, smart devices can promptly issue alarms so that workers and monitoring centers can take emergency measures to reduce life risks. This helps monitor and analyze the construction process and helps project managers better understand the situation on the construction site. Through real-time, comprehensive, and intelligent data collection, analysis, and early warning, as well as efficient and stable data transmission and remote supervision and control, it provides strong protection for workers' health and safety, while improving production safety and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of data interaction of a wearable safety device based on biosensing and human body status monitoring according to the present invention; Figure 2 This is a module diagram of the safety system based on biosensing and human body status monitoring of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] In order to solve the technical problem that traditional safety protection measures often rely on workers' self-perception and judgment, which has great limitations and cannot monitor and warn potential safety risks in real time and accurately, please refer to Figure 1 , this embodiment provides the following technical solutions: Wearable safety equipment based on biosensing and human status monitoring includes smart equipment, which consists of a safety bracelet, a safety helmet, a safety belt, safety shoes and a safety vest. The smart equipment is worn on the worker's head, body and feet to monitor the worker's vital signs in real time, including key parameters such as heart rate, respiratory rate, oxygen content and body posture, and to issue an alarm in time when an abnormal situation is detected. At the same time, it records construction environment data and interacts with base stations, wherein the base stations include external base stations, fixed base stations and mobile base stations.

[0019] In this embodiment, the vital signs of workers can be monitored in real time through smart devices, including key parameters such as heart rate, respiratory rate, oxygen content, body posture, etc. When an abnormal situation is detected, the smart device can issue an alarm in time so that workers and the monitoring center can take emergency measures to reduce life risks. It can record data on the construction environment, including information such as oxygen content, temperature, humidity, etc., which is helpful for monitoring and analyzing the construction progress and helping engineering managers to better understand the situation at the construction site. Based on data interaction with the base station, workers can be remotely monitored in real time, which is helpful for monitoring and analyzing the construction progress and helping engineering managers to better understand the situation at the construction site.

[0020] See also Figure 2 The present invention provides a safety system based on biosensing and human body status monitoring, comprising: The data acquisition unit is used to obtain the biosensor data and human status information data of the workers wearing the safety wearable equipment in real time, and to collect the environmental parameters of the workers' environment in real time, including: The human body parameter acquisition module is used to monitor and collect the physiological parameters of workers wearing safety wearable devices, such as heart rate, blood oxygen saturation, etc.; The construction environment acquisition module is used to monitor and collect environmental parameters of the environment in which workers wearing safety wearable devices are located, such as temperature, humidity, gas concentration, etc.; The abnormal situation warning module is used to judge whether there are abnormalities in the workers and their environment based on the collected physiological parameters and environmental parameters, and issue a warning signal based on the judgment results and relevant instructions obtained from the main station supervision unit; In this embodiment, the data acquisition unit further includes dynamically adjusting the sampling frequency of the safety wearable device according to actual needs, specifically: Monitor the data changes corresponding to the parameter type of each physiological parameter in real time during each monitoring cycle; At the end of the monitoring period, obtaining the data change amplitude of each parameter type of each physiological parameter in the current monitoring period; According to the data variation amplitude of the parameter type of each physiological parameter, a physiological parameter retrieval time interval of a target physiological parameter type is set for the next monitoring period; The master station communication unit is used to build a signal interaction channel between each safety wearable device and the base station, and transmit the collected worker biosensor data, human body status information data and environmental parameters to the master station monitoring unit to ensure the stability and security of data transmission, including: Base station construction module, used to build communication base stations, including external base stations, fixed base stations and mobile base stations, to ensure the coverage and reliability of data transmission; An interactive channel building module is used to establish a signal interactive channel between an external base station and a fixed base station, between a fixed base station and a mobile base station, and between a mobile base station and a safety wearable device; The interactive channel supervision module is used to monitor the status data of the communication connection between the signal interactive channels in real time, determine the data transmission efficiency of the signal interactive channels, and ensure the stability and security of data transmission; The master station monitoring unit is used to obtain the data transmitted by the data acquisition unit based on the signal interaction channel, monitor and warn of abnormal conditions of the acquired data, and remotely monitor and control the safety wearable device based on the judgment and warning results.

[0021] In this embodiment, the data acquisition unit acquires the workers' biosensor data and human state information data, as well as environmental parameters in real time, thereby ensuring real-time monitoring of the workers' health status and environmental conditions, improving the real-time and accuracy of data acquisition, and dynamically adjusting the sampling frequency of the safety wearable device according to actual needs. The data acquisition can be optimized based on the changes in physiological parameters, thereby ensuring the continuity of the data and reducing unnecessary energy consumption and data processing burden. At the same time, physiological parameters and environmental parameters are monitored to provide comprehensive health and safety protection for workers. Intelligent analysis is performed based on the real-time collected data to timely discover and warn of possible abnormal conditions, effectively improving the ability to protect the safety of workers. The master station communication unit ensures the efficiency and stability of data transmission between the data acquisition unit and the master station monitoring unit by establishing various types of base stations and building stable and secure signal interaction channels, remotely monitoring and controlling the safety wearable device, improving the remote management capability of the workers' safety, and enabling rapid adoption of corresponding measures in emergency situations.

[0022] In this embodiment, the abnormal situation warning module specifically includes: A threshold judgment mechanism is preset, and the acquired environmental parameters are compared with the normal environmental parameter thresholds to determine whether the worker's environment is normal; Determine the special working environment described by the worker by using environmental parameters that exceed or fall below normal parameter thresholds, and adjust the safety physiological parameter thresholds based on the special working environment; Compare the physiological parameters collected in real time with the preset safety physiological parameter thresholds, and issue an early warning when the physiological parameters collected in real time exceed the thresholds; Extracting parameter types of physiological parameters that exceed the threshold, and determining the abnormal state of the worker based on the parameter type combined with the environmental abnormality parameter, wherein the abnormal state includes hypoxemia, abnormal heart rate, sudden physiological changes, etc. For example, in the case of working at high altitudes, the blood oxygen threshold may need to be relatively low to allow a larger range of variation; In this embodiment, the setting of the threshold is precisely adjusted based on the data of scientific research and clinical experiments; currently, a person is judged to be in a hypoxic state when the blood oxygen level is <= 94, and a person is judged to be in a dangerous state when the blood oxygen level is <= 94 and the gyroscope deflects 45 degrees and the acceleration is 5 meters / second and the gyroscope value remains unchanged.

[0023] In this embodiment, the abnormal state of the worker is determined based on the parameter type combined with the environmental abnormality parameter, specifically including: Construct a linear regression model, input the acquired physiological parameters of the workers into the linear regression model for calculation, and obtain the predicted physiological parameters of the workers; Compare the actually measured physiological parameters of the worker with the predicted physiological parameters of the worker, and determine whether the burn exceeds a preset difference threshold based on the comparison result, and if so, consider that an abnormal situation exists; Once an abnormal state is detected, the alarm mechanism is triggered immediately and relevant information of the abnormal state is recorded, including time, location and abnormal type.

[0024] In this embodiment, the threshold value of the safety physiological parameter is adjusted according to the special working environment, so that the early warning system is more in line with the characteristics of the actual working environment, the applicability and accuracy of the early warning are improved, and the real health status of the workers can be better reflected. The physiological parameters of the workers are predicted by a linear regression model and compared with the actual measured values, which further improves the accuracy of the early warning. Through real-time and accurate early warning and rapid response, the health and safety hazards of the workers can be discovered and dealt with in time, and the losses to workers and enterprises caused by potential safety accidents can be avoided or reduced, thereby improving the safety and efficiency of work, realizing intelligent prediction and early warning of the health status of workers, improving the intelligence level of the early warning system, reducing the dependence on manual intervention, and improving the efficiency and accuracy of supervision.

[0025] In this embodiment, the master station supervision unit includes: A data acquisition module, used for receiving worker physiological parameters, environmental parameters and positioning data from a data acquisition unit based on a signal interaction channel; A data processing module is used to perform standardization processing on the received worker physiological parameters, environmental parameters and positioning data to obtain standard physiological parameter data, standard environmental parameter data and standard positioning data; The abnormality monitoring module is used to retrieve the historical data related to the workers based on the processed standardized data, analyze the trend of the workers' vital signs in combination with the historical data, determine whether the workers have abnormal conditions, and generate corresponding processing instructions based on the abnormality degree of the abnormal conditions, so as to conduct more in-depth data analysis and work efficiency evaluation; The personnel supervision module is used to supervise the behavior and working status of workers wearing safety wearable devices to ensure work safety; In this embodiment, the personnel supervision module determines whether a worker has an abnormal condition, specifically: By real-time monitoring of the physiological parameters and environmental parameters of workers wearing safety wearable devices, the working status and health status of workers can be evaluated; Obtaining multiple behavioral sample data of workers based on their working status and health status; The worker's blinking frequency, movement pause frequency, heart rate acceleration change frequency and behavioral habit weight are extracted from each behavioral sample data; Identify the extracted multiple parameters and obtain identification results; The abnormal coefficient of the worker during work is calculated based on the worker's blinking frequency, action pause frequency, heart rate acceleration change frequency and behavioral habit weight in each behavior sample data and the identification result of each parameter; Confirm whether the abnormality coefficient is greater than a preset coefficient. If so, obtain the driver's location data based on the safety wearable device worn by the worker. Otherwise, confirm that the worker is not abnormal. Send reminders and warning messages to the safety wearable devices worn by the workers according to the abnormal results, and guide the workers to take corresponding measures; In this embodiment, by retrieving historical data and combining it with real-time data, the trend of workers' vital signs can be analyzed and whether there are abnormal conditions. Processing instructions based on the degree of abnormality can provide decision support for managers, facilitating them to conduct more in-depth data analysis and work efficiency evaluation. By real-time monitoring of workers' physiological parameters and environmental parameters, combined with behavioral sample data, workers' work status and health status can be comprehensively evaluated; The equipment supervision module is used to supervise the operating status of safety wearable equipment to ensure the normal operation of the equipment; In this embodiment, the device supervision module supervises the safety wearable device, specifically: Monitor the battery power information of safety wearable devices in real time to determine the total capacity of the battery and the current battery power percentage; Determine the energy consumption of each sensor in the safety wearable device at a preset frequency per hour, and calculate the battery life based on the energy consumption of each sensor at the preset frequency per hour; The battery life of the battery is corrected based on the sampling frequency adjustment result of the safety wearable device of the data acquisition unit, and the power supply is adjusted according to the working status and actual needs of the device to optimize energy consumption and extend the service life of the device; When the current battery power percentage is less than 20%, all power saving measures are taken, including reducing the alarm remaining frequency, reducing the detection frequency and switching to energy saving mode; When the current battery power percentage is between 20% and 50%, only measures of reducing the alarm residual frequency and reducing the detection frequency are taken; When the current battery power percentage is 50% or above, no power saving measures are taken.

[0026] In this embodiment, by real-time monitoring of battery power information and the energy consumption of each sensor, the battery life can be calculated, and the power supply can be adjusted according to the working status and actual needs of the equipment to achieve energy consumption optimization and extend the service life of the equipment. In addition, according to different percentages of battery power, corresponding power-saving measures are taken to further improve the stability and reliability of the equipment, and realize comprehensive, real-time and intelligent supervision and management of workers and equipment, which helps to improve work efficiency, reduce the probability of safety accidents, and provide strong protection for the safe production of enterprises and the health of personnel.

[0027] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. Safety wearable devices based on biosensing and human body status monitoring, including smart devices, characterized by: The smart device consists of a safety bracelet, a safety helmet, a safety belt, safety shoes and a safety vest. The smart device is worn on the worker's head, body and feet to monitor the worker's vital signs in real time, including key parameters such as heart rate, respiratory rate, oxygen content and body posture. It will promptly issue an alarm when an abnormal situation is detected, record construction environment data, and interact with the base station for data.

2. A safety system based on biosensing and human body status monitoring, applied in the safety wearable device based on biosensing and human body status monitoring as claimed in claim 1, characterized in that: include: A data acquisition unit is used to obtain the biosensor data and human body status information data of the workers wearing the safety wearable equipment in real time, and to collect the environmental parameters of the workers' environment in real time; The main station communication unit is used to build a signal interaction channel between each safety wearable device and the base station, and transmit the collected worker biosensor data, human body status information data and environmental parameters to the main station supervision unit; The master station monitoring unit is used to obtain the data transmitted by the data acquisition unit based on the signal interaction channel, monitor and warn of abnormal conditions of the acquired data, and remotely monitor and control the safety wearable device based on the judgment and warning results.

3. The safety system based on biosensing and human body status monitoring as claimed in claim 2, characterized in that: Data acquisition unit, including: Human body parameter acquisition module, used to monitor and collect physiological parameters of workers wearing safety wearable devices; The construction environment acquisition module is used to monitor and collect environmental parameters of the environment in which workers wearing safety wearable devices are located in real time; The abnormal situation warning module is used to judge whether there are abnormalities in the workers and their environment based on the collected physiological parameters and environmental parameters, and to issue a warning signal based on the judgment results and relevant instructions obtained from the main station supervision unit.

4. The safety system based on biosensing and human body status monitoring as claimed in claim 3, characterized in that: Abnormal situation warning module, specifically including: A threshold judgment mechanism is preset, and the acquired environmental parameters are compared with the normal environmental parameter thresholds to determine whether the worker's environment is normal; Determine the special working environment described by the worker by using environmental parameters that exceed or fall below normal parameter thresholds, and adjust the safety physiological parameter thresholds based on the special working environment; Compare the physiological parameters collected in real time with the preset safety physiological parameter thresholds, and issue an early warning when the physiological parameters collected in real time exceed the thresholds; The parameter types of the physiological parameters exceeding the threshold are extracted, and the abnormal state of the worker is determined based on the parameter types combined with the abnormal environmental parameters.

5. The safety system based on biosensing and human body status monitoring as claimed in claim 4, characterized in that: Determine the abnormal status of workers based on parameter type and environmental abnormal parameters, including: Construct a linear regression model, input the acquired physiological parameters of the workers into the linear regression model for calculation, and obtain the predicted physiological parameters of the workers; Compare the actually measured physiological parameters of the worker with the predicted physiological parameters of the worker, and determine whether the burn exceeds a preset difference threshold based on the comparison result, and if so, consider that an abnormal situation exists; When an abnormal state is detected, the alarm mechanism is triggered immediately and relevant information of the abnormal state is recorded, including time, location and abnormal type.

6. The safety system based on biosensing and human body status monitoring as claimed in claim 5, characterized in that: The data acquisition unit also includes dynamically adjusting the sampling frequency of the safety wearable device according to actual needs, specifically: Monitor the data changes corresponding to the parameter type of each physiological parameter in real time during each monitoring cycle; At the end of the monitoring period, obtaining the data change amplitude of each parameter type of each physiological parameter in the current monitoring period; A physiological parameter retrieval time interval of a target physiological parameter type is set for the next monitoring period according to the data variation amplitude of the parameter type of each physiological parameter.

7. The safety system based on biosensing and human body status monitoring as claimed in claim 6, characterized in that: Master station communication unit, including: Base station construction module, used to build communication base stations, including external base stations, fixed base stations and mobile base stations; An interactive channel building module is used to establish a signal interactive channel between an external base station and a fixed base station, between a fixed base station and a mobile base station, and between a mobile base station and a safety wearable device; The interactive channel supervision module is used to monitor the status data of the communication connection between the signal interactive channels in real time and determine the data transmission efficiency of the signal interactive channels.

8. The safety system based on biosensing and human body status monitoring as claimed in claim 7, characterized in that: Master station supervision unit, including: A data acquisition module, used for receiving worker physiological parameters, environmental parameters and positioning data from a data acquisition unit based on a signal interaction channel; A data processing module is used to perform standardization processing on the received worker physiological parameters, environmental parameters and positioning data to obtain standard physiological parameter data, standard environmental parameter data and standard positioning data; The abnormality monitoring module is used to retrieve the historical data related to the workers according to the processed standardized data, analyze the trend of the workers' vital signs in combination with the historical data, determine whether the workers have abnormal conditions, and generate corresponding processing instructions based on the abnormality degree of the abnormal conditions; The personnel supervision module is used to supervise the behavior and working status of workers wearing safety wearable equipment; The device monitoring module is used to monitor the operating status of safety wearable devices.

9. The safety system based on biosensing and human body status monitoring as claimed in claim 8, characterized in that: The personnel supervision module determines whether there are any abnormal conditions among workers, specifically: By real-time monitoring of the physiological parameters and environmental parameters of workers wearing safety wearable devices, the working status and health status of workers can be evaluated; Obtaining a plurality of behavioral sample data of the worker based on the working status and health status of the worker; The worker's blinking frequency, movement pause frequency, heart rate acceleration change frequency and behavioral habit weight are extracted from each behavioral sample data; Identify the extracted multiple parameters and obtain identification results; The abnormal coefficient of the worker during work is calculated based on the worker's blinking frequency, action pause frequency, heart rate acceleration change frequency and behavioral habit weight in each behavior sample data and the identification result of each parameter; Confirm whether the abnormality coefficient is greater than a preset coefficient. If so, obtain the driver's location data based on the safety wearable device worn by the worker. Otherwise, confirm that the worker is not abnormal. According to the abnormal results, reminders and warning messages are sent to the safety wearable devices worn by the workers to guide the workers to take corresponding measures.

10. The safety system based on biosensing and human body status monitoring as claimed in claim 9, characterized in that: The device supervision module supervises safety wearable devices, specifically: Monitor the battery power information of safety wearable devices in real time to determine the total capacity of the battery and the current battery power percentage; Determine the energy consumption of each sensor in the safety wearable device at a preset frequency per hour, and calculate the battery life based on the energy consumption of each sensor at the preset frequency per hour; Correcting the battery life of the battery based on the sampling frequency adjustment result of the safety wearable device of the data acquisition unit; When the current battery power percentage is less than 20%, all power saving measures are taken, including reducing the alarm remaining frequency, reducing the detection frequency and switching to energy saving mode; When the current battery power percentage is between 20% and 50%, only measures of reducing the alarm residual frequency and reducing the detection frequency are taken; When the current battery power percentage is 50% or above, no power saving measures are taken.

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