A multi-parameter safety monitoring intelligent bracelet for high-risk working environment

Abstract

The application provides a multi-parameter safety monitoring intelligent bracelet for high-risk operation environment, comprising: a main body with a protection structure and integrated with a display unit; a sensor module integrated with multiple sensors for collecting physiological, environmental and motion data, and the sensors are all provided with a protection structure and a compensation circuit; an identity management module containing a security element for performing identity verification based on an encryption algorithm; a micro-processing control module for fused analysis of sensor data and output of control instructions; a reminding module connected with the micro-processing control module for generating vibration feedback of different frequencies according to the control instructions; a storage module for encrypted storage of data; and a communication positioning module for data transmission and indoor positioning, so as to improve the overall level of safety management and health monitoring of personnel in industrial sites.

Description

Technical Field

[0001] This invention belongs to the field of wearable device technology, and in particular relates to a multi-parameter safety monitoring smart bracelet for high-risk working environments. Background Technology

[0002] In the field of industrial safety and personnel management, wearable devices, especially smart bracelets, are increasingly being used for employee health monitoring and environmental risk perception. Existing technologies typically involve adapting consumer-grade smart bracelets, integrating basic sensors such as heart rate and motion sensors, and using wireless communication technologies like Bluetooth or Wi-Fi for data transmission to remotely monitor some of the employee's physiological indicators. This traditional approach improves the convenience of on-site management to some extent. However, as industrial sites increasingly demand more refined and intelligent safety management, existing solutions have revealed several limitations. First, the devices themselves lack specialized protective designs against harsh industrial environments such as complex electromagnetic interference, dust, oil contamination, and drastic temperature and humidity changes, resulting in insufficient durability and operational stability, making it difficult to meet long-term, reliable operational needs. Second, the monitoring dimensions are relatively limited, mainly focusing on basic physiological indicators such as heart rate and step count, making it difficult to simultaneously collect and analyze multi-dimensional safety information such as harmful gas concentrations and the precise indoor location of employees, thus limiting the comprehensiveness and accuracy of risk warnings. Furthermore, identity authentication largely relies on ordinary NFC or QR code technology, which poses security risks of information copying or tampering, failing to meet the requirements of high-security identity management. In addition, warning methods are typically limited to simple vibration or buzzer alerts, unable to provide differentiated and hierarchical warnings based on risk levels. Finally, the encryption strength of data during local storage and wireless transmission is insufficient, posing a privacy risk. Therefore, there is an urgent need for a wearable device solution that can operate stably in harsh industrial environments, achieve multi-dimensional security monitoring, possess high-security identity management, and provide differentiated warnings and strong data protection to overcome the shortcomings of existing technologies and improve the overall security management level of industrial sites. Summary of the Invention

[0003] This invention aims to solve a series of core technical challenges faced by existing wearable devices when applied in complex and harsh industrial environments, and to provide a technical solution that can systematically address the above problems, thereby improving the overall level of safety management and health monitoring for personnel in industrial settings.

[0004] A multi-parameter safety monitoring smart bracelet for high-risk work environments includes: The main body has a protective structure and integrates a display unit; The sensor module integrates multiple sensors for collecting physiological, environmental, and motion data, and all of these sensors are equipped with protective structures and compensation circuits. The identity management module contains a security element for performing authentication based on cryptographic algorithms; The microprocessor control module is used to fuse and analyze sensor data and output control commands; The reminder module, connected to the microprocessor control module, is used to generate vibration feedback of different frequencies according to control commands; Storage module, used for encrypted data storage; The communication and positioning module is used for data transmission and indoor positioning.

[0005] Furthermore, the main structural module includes a built-in electromagnetic shielding structure and a waterproof and dustproof outer shell.

[0006] Furthermore, the sensor module includes one or more of physiological sensors, environmental sensors, and motion sensors in combination; Among them, environmental sensors include electrochemical sensors used to monitor the concentration of harmful gases; Physiological sensors include heart rate sensors and body temperature sensors.

[0007] Furthermore, the microprocessor control module determines abnormal physiological states based on heart rate and body temperature data.

[0008] Furthermore, the identity management module generates dynamic encryption factors during the verification process and supports dual authorization binding of identity information and remote data erasure.

[0009] Furthermore, the alert module includes multiple vibration units, which achieve graded early warning through combinations of different vibration frequencies, durations, and vibration modes.

[0010] Furthermore, the communication positioning module integrates an ultra-wideband (UWB) positioning unit for indoor location tracking.

[0011] Furthermore, the communication positioning module supports multiple wireless communication protocols, and the data transmission process employs an encrypted transmission protocol.

[0012] Furthermore, the storage module has a circular storage mechanism that automatically overwrites data.

[0013] Furthermore, the bracelet has a privacy mode in which the physiological monitoring function is turned off while the location function is retained.

[0014] This invention achieves the following beneficial effects: First, by employing a high-protection-level shell, electromagnetic shielding layer, and anti-glare display unit, it significantly improves the physical durability, anti-interference capability, and display visibility of the equipment in harsh industrial environments such as dust, humidity, oil, and complex electromagnetic interference, ensuring long-term stable operation of the equipment. Second, by integrating multiple sensors with protection and compensation circuits and combining them with data fusion algorithms, it achieves real-time, accurate monitoring and intelligent analysis of multi-dimensional information such as employee physiological status, ambient harmful gas concentration, and high-precision indoor location, improving the comprehensiveness and accuracy of safety monitoring. Third, by integrating a security chip that supports national cryptographic algorithms and generates dynamic encryption factors, it achieves hardware-level encryption and dynamic verification of identity information, effectively preventing identity information from being copied or tampered with in scenarios such as access control and attendance, ensuring high security of identity management. Fourth, by adopting a dual-motor graded alert module, it can trigger differentiated vibrations based on different risk levels, achieving timely, effective, and non-disruptive graded warnings. Finally, by employing a high-level encrypted local storage module, a wireless communication module that supports the latest encryption protocols, and combining it with a privacy mode switching function, the security and privacy of employees' physiological data and location information are fully guaranteed throughout the entire process of local storage, wireless transmission, and non-working hours.

[0015] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0016] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram showing the connection relationship of various modules of a multi-parameter safety monitoring smart bracelet for high-risk working environments, as described in an embodiment of the present invention.

[0018] Figure 2 This is a flowchart illustrating the workflow of a multi-parameter safety monitoring smart bracelet for high-risk work environments, as described in an embodiment of the present invention. Detailed Implementation

[0019] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0020] This invention provides a multi-parameter safety monitoring smart bracelet for high-risk work environments, such as... Figure 1 As shown, it includes: The main body has a protective structure and integrates a display unit; The sensor module integrates multiple sensors for collecting physiological, environmental, and motion data, and all of these sensors are equipped with protective structures and compensation circuits. The identity management module contains a security element for performing authentication based on cryptographic algorithms; The microprocessor control module is used to fuse and analyze sensor data and output control commands; The reminder module, connected to the microprocessor control module, is used to generate vibration feedback of different frequencies according to control commands; Storage module, used for encrypted data storage; The communication and positioning module is used for data transmission and indoor positioning.

[0021] The main structural module forms the physical basis of the bracelet. The bracelet body features an ergonomic design, with a strap made of oil- and wear-resistant food-grade silicone that is adjustable in length. The bracelet's outer shell has IP68 waterproof and dustproof ratings and incorporates an electromagnetic shielding layer with an effectiveness of at least 80 dB. The main body integrates a 0.96-inch anti-glare organic light-emitting diode (OLED) display unit with a brightness of at least 500 candela per square meter (cd / m²), and includes standard physical operation buttons such as a data query button and a mode switching button.

[0022] The sensor module is integrated within the wristband and includes basic physiological sensors, environmental sensors, and motion sensors. The basic physiological sensors include a heart rate sensor, a blood oxygen sensor, and a body temperature sensor. The environmental sensor is an electrochemical hazardous gas sensor targeting carbon monoxide and hydrogen sulfide. The motion sensor is a triaxial accelerometer with a sampling rate of 100 Hz and a measurement range of ±16 times g. All sensors are equipped with nanoscale dust covers with an aperture no larger than 0.1 micrometers (μm) and temperature compensation circuitry, enabling stable operation in ambient temperatures ranging from -20°C to 60°C and dust concentrations no greater than 10 milligrams per cubic meter (mg / m³). The sensor module continuously collects the wearer's heart rate, blood oxygen, body temperature, ambient carbon monoxide and hydrogen sulfide concentrations, and triaxial acceleration data, transmitting this raw data to the microprocessor control module.

[0023] The identity management module is electrically connected to the microprocessor control module. Its core is a secure element (SE) chip that integrates the national standard SM4 encryption algorithm (128-bit key length) and is compatible with the ISO / IEC 14443 protocol, with a communication distance of 0 to 5 centimeters. This module is used for employee identity management. Upon employee onboarding, a dual-authorization confirmation process between the back-end management system and the wristband binds and encrypts the employee's unique identity information, storing it in the secure element of this module. During identity verification (such as access control unlocking and attendance tracking), this module communicates with an external card reader and generates dynamic encryption factors to prevent identity information from being copied or tampered with. Upon employee departure, the back-end management system can send a command to the wristband via the communication positioning module, which in turn controls the microprocessor control module to completely erase the employee's identity data and disable related functions.

[0024] The alert module is electrically connected to the microprocessor control module and employs a dual-motor design. One motor is a warning motor with a vibration frequency of 100Hz, used to perform vibration for 1 second; the other is an emergency motor with a vibration frequency of 200Hz, used to perform vibration for 3 seconds in a cyclical manner. The module receives instructions from the microprocessor control module and generates vibrations of corresponding frequencies and patterns according to different warning levels.

[0025] The microprocessor control module, as the core control unit of the wristband, uses an industrial-grade STM32H743 microcontroller unit (MCU) with an operating temperature range of -40℃ to 85℃ and a main frequency of 400 MHz. This module is connected to the sensor module, identity management module, display unit, reminder module, storage module, and communication and positioning module via circuitry. Internally, it runs sensor data fusion algorithms, such as combining heart rate and body temperature data to comprehensively determine physiological abnormalities. This module compares the fused analysis results with preset safety thresholds and, based on the comparison results, issues corresponding control commands to the reminder module, communication and positioning module, etc.

[0026] The storage module is connected to the microprocessor control module and uses an 8-gigabyte (GB) Advanced Encryption Standard-256 (AES-256) encrypted flash memory chip. This module is used for local encrypted storage of employee information, physiological data, environmental data, exercise data, and equipment configuration parameters. Local data retention is up to 30 days, after which expired data is automatically overwritten. Simultaneously, this module supports encrypted synchronization with a cloud server via a communication positioning module, enabling secure data backup.

[0027] The communication and positioning module supports Bluetooth 5.0 (transmission distance of at least 100 meters, transmission rate of 2 Mbps) and Wi-Fi 6 (transmission rate of at least 1.2 Gbps). Data transmission is encrypted using Transport Layer Security (TLS) version 1.3. The module also integrates a DW1000 ultra-wideband (UWB) positioning module with a positioning accuracy of ±30 cm and a refresh rate of 1 Hz. This module is responsible for enabling encrypted data communication between the wristband and the backend management system, and for uploading UWB positioning data in real time to achieve real-time indoor location tracking of the wearing employee.

[0028] The supporting modules for functional implementation refer to a series of supporting functions implemented by the microprocessor control module through corresponding algorithms and logic. In terms of health and environmental risk monitoring, the microprocessor control module determines abnormal states using the aforementioned data fusion algorithm. For example, when the heart rate consistently exceeds a preset threshold and body temperature is abnormal, it is determined to be a physiological abnormality; when the concentration of harmful gases exceeds the safety limit, it is determined to be an environmental abnormality. Based on the type and severity of the abnormality, the microprocessor control module classifies warnings into different levels and sends instructions to the alert module to trigger the corresponding level of vibration warning (such as warning motor vibration or emergency motor vibration). Simultaneously, the warning information is encrypted and pushed to the management backend via the communication and positioning module. If the abnormal state persists for more than a preset duration, an enhanced warning mechanism is triggered, such as increasing the vibration frequency or sending an emergency alarm to the backend. Regarding auxiliary functions, the wristband can receive messages from the management backend via the communication and positioning module and remind employees to confirm via the display unit or alert module. By analyzing data from the triaxial accelerometer and UWB positioning trajectory, the microprocessor control module can calculate indicators such as employee activity level and movement distance, and generate a work intensity analysis report which is uploaded to the backend. In addition, employees can manually switch the wristband to non-working time mode using the mode switch button. In this mode, the microprocessor control module will turn off the physiological monitoring function to protect personal privacy, but the basic communication and positioning functions will still continue to operate.

[0029] The working principle and beneficial effects of the above technical solution are as follows: By adopting a high-protection-level shell, electromagnetic shielding layer, and anti-glare display unit, the physical durability, anti-interference ability, and display visibility of the equipment in harsh industrial environments such as dust, humidity, oil, and complex electromagnetic interference are significantly improved, ensuring long-term stable operation of the equipment. Secondly, by integrating multiple sensors with protection and compensation circuits and combining them with data fusion algorithms, real-time, accurate monitoring and intelligent analysis of multi-dimensional information such as employee physiological status, ambient harmful gas concentration, and high-precision indoor location are achieved, improving the comprehensiveness and accuracy of safety monitoring. Thirdly, by integrating a security chip that supports national cryptographic algorithms and generates dynamic encryption factors, hardware-level identity information encryption and dynamic verification are achieved, effectively preventing identity information from being copied or tampered with in scenarios such as access control and attendance, ensuring high security of identity management. Fourthly, by adopting a dual-motor graded alert module, differentiated vibrations can be triggered according to different risk levels, achieving timely, effective, and non-disruptive graded warnings. Finally, by employing a high-level encrypted local storage module, a wireless communication module that supports the latest encryption protocols, and combining it with a privacy mode switching function, the security and privacy of employees' physiological data and location information are fully guaranteed throughout the entire process of local storage, wireless transmission, and non-working hours.

[0030] In one embodiment, the main structural module includes a built-in electromagnetic shielding structure and a waterproof and dustproof outer shell.

[0031] The working principle and beneficial effects of the above technical solution are as follows: the bracelet shell adopts an IP68 waterproof and dustproof design, and has a built-in electromagnetic shielding layer with a shielding effectiveness of not less than 80 decibels (dB), combined with a brightness of not less than 500 cd / m². 2 The anti-glare OLED display unit significantly improves the equipment's physical durability and anti-interference capabilities in harsh industrial environments such as dust, humidity, oil, and strong electromagnetic interference, ensuring that the displayed content is clearly visible under strong light and guaranteeing the long-term stable operation of the equipment in extreme production environments.

[0032] In one embodiment, the sensor module includes one or more of physiological sensors, environmental sensors, and motion sensors; the environmental sensors include electrochemical sensors for monitoring the concentration of harmful gases.

[0033] The working principle and beneficial effects of the above technical solution are as follows: This module integrates physiological, motion, and electrochemical harmful gas sensors. All sensors are equipped with nanoscale dust covers with pore sizes no larger than 0.1μm and temperature compensation circuits to collect human characteristics, motion status, and the concentrations of carbon monoxide and hydrogen sulfide in the environment. This solves the problem of traditional sensors easily failing in high-temperature and high-dust environments, enabling real-time monitoring of multi-dimensional safety information related to "humans and the environment," and providing a more comprehensive data foundation for industrial safety.

[0034] In one embodiment, the physiological sensor includes a heart rate sensor and a body temperature sensor; the microprocessor control module determines abnormal physiological states by fusing heart rate and body temperature data.

[0035] The working principle and beneficial effects of the above technical solution are as follows: The microprocessor control module runs a sensor data fusion algorithm to perform comprehensive logical judgment on the raw data collected by the heart rate sensor and body temperature sensor, rather than relying on the threshold of a single indicator. Through multi-indicator correlation analysis (such as a sustained increase in heart rate accompanied by abnormal body temperature), the accuracy of physiological abnormality judgment is improved, false alarms or missed alarms caused by single threshold alarms are avoided, and multi-dimensional safety information fusion perception and differentiated reminders are realized.

[0036] In one embodiment, the microprocessor control module executes a sensor data fusion algorithm, which includes a normalization processing mechanism for multi-source heterogeneous data and a dynamic weighted evaluation model based on signal confidence. Traditional fixed-weight models not only fail to address the issue of inconsistent dimensions in data from different sensors, but are also highly susceptible to motion artifacts from photoelectric sensors, leading to false alarms, especially under complex conditions such as vigorous movement by the wearer. This embodiment achieves true multi-dimensional deep fusion by introducing normalized mapping, motion variance, and environmental change rate.

[0037] The microprocessor control module performs the following fusion analysis operations: Acquire effective observations from physiological and environmental sensors, and normalize the effective observations of different physical dimensions into a uniform deviation. Motion variance is calculated based on data from a triaxial accelerometer to quantify the intensity of current motion disturbance, and the rate of change of harmful gas concentration is calculated based on data from environmental sensors. Perform dynamic weighted evaluation based on signal confidence: when the motion variance is greater than the preset motion interference threshold, dynamically reduce the weight coefficient of physiological characteristics and adaptively compensate the released weight share to the environmental weight coefficient and motion weight coefficient; when the rate of change of harmful gas concentration is greater than the preset gas surge threshold, forcibly assign the highest confidence to the environmental weight coefficient and compress other weight coefficients. Based on the normalized uniform deviation and the dynamically updated weight coefficients, the real-time comprehensive risk index is calculated. The real-time comprehensive risk index is compared with the preset danger classification threshold, and the corresponding classification warning control command is output to the alert module based on the comparison result. The comprehensive risk index calculation model defined by the microprocessor control module is as follows: R=α·P_norm+β·E_norm+γ·M_factor Among them, R is the comprehensive risk index at the current moment; P_norm is the normalized physiological characteristic risk index; E_norm is the normalized environmental gas risk index; M_factor is the motion state correction coefficient; α, β, and γ respectively represent the dynamic confidence weight coefficients assigned by the microprocessing control module to physiological data, environmental data, and motion posture in real time, and satisfy α + β + γ = 1 at any moment.

[0038] The specific execution steps of this fusion algorithm are as follows: Step 1: Denoising and normalization of multi-source heterogeneous data: The microprocessing control module does not directly respond to single-point extreme values, but instead establishes a sliding data window with a time length of T (for example, 3 seconds). For the physiological data sequence and environmental data sequence within the window, median filtering or the method of averaging after removing the upper and lower extreme values is used to obtain the effective observed values P_obs (such as the smoothed heart rate) and E_obs (such as the smoothed harmful gas concentration) of the current window, so as to eliminate the extreme value error caused by the transient burr noise of the sensor.

[0039] The physiological safety baseline P_base (such as the resting heart rate) and physiological danger threshold P_th of the wearer are preset in the microprocessing control module. The dynamic calculation formula of P_norm is: When P_obs ≤ P_base, P_norm = 0; When P_base < P_obs < P_th, P_norm = (P_obs - P_base) / (P_th - P_base); When P_obs ≥ P_th, P_norm = 1.

[0040] Through this linear mapping, the physiological differences of different individuals are transformed into a unified deviation degree in the interval [0, 1].

[0041] For the harmful gas concentration, the system presets the lower limit of the safe concentration E_safe and the fatal danger concentration E_fatal. The calculation formula of E_norm is: When E_obs ≤ E_safe, E_norm = 0; When E_safe < E_obs < E_fatal, E_norm = (E_obs - E_safe) / (E_fatal - E_safe); When E_obs ≥ E_fatal, E_norm = 1.

[0042] Step 2: Dynamic confidence evaluation and weight adaptive adjustment: During system initialization, the preset baseline weights are read from the storage module, for example, α_0=0.4, β_0=0.4, γ_0=0.2.

[0043] The microprocessor control module receives data from the triaxial accelerometer at a preset frequency and calculates the variance V_motion of the acceleration signal within a preset sliding window to quantify the current intensity of motion disturbance. Simultaneously, it extracts continuous time points from the electrochemical sensor data and calculates the rate of change of harmful gas concentration ΔE / Δt.

[0044] A motion interference threshold Th_motion and a physiological weight lower limit α_min are set. When V_motion > Th_motion is detected, it is determined that the wearer is in a high-intensity work state (such as drilling or arm swinging), at which time the risk of photoelectric physiological signal distortion is extremely high. The system immediately activates the attenuation strategy, dynamically lowering the physiological feature weight α: α=max(α_min,α_0-k1·(V_motion-Th_motion)) Where k1 is the preset motion compensation attenuation coefficient.

[0045] To ensure weight normalization, the system will proportionally and adaptively compensate the released weight share (α_0-α) into the environment weight and motion weight: β = β_0 + 0.5·(α_0 - α) γ = γ_0 + 0.5·(α_0 - α) When the detected rate of change in gas concentration ΔE / Δt > Th_gas (gas surge threshold) indicates a sudden hazardous gas leak. At this point, the microprocessor control module intervenes, assigning the highest confidence level to β (e.g., temporarily locking β=0.7), and correspondingly compressing the weights of α and γ to ensure priority response to catastrophic environmental risks.

[0046] Step 3: Risk Calculation and Tiered Early Warning The microprocessor control module substitutes the obtained P_norm, E_norm, and dynamically updated weights into the risk index calculation model to obtain the real-time comprehensive risk index R. If R > R_warning, the 100Hz warning motor of the alert module is triggered; if R > R_danger, the 200Hz emergency motor is triggered, and the anomaly identifier is uploaded through the communication positioning module.

[0047] The working principle and beneficial effects of the above technical solution are as follows: Through denoising and normalization mechanisms, heterogeneous data with different physical dimensions are unified; combined with a dynamic weighting mechanism, the pain point of single sensors being easily interfered with in high-risk industrial scenarios is effectively solved. When strenuous labor by workers causes motion artifacts in physiological sensors, the system can automatically identify motion variance and remove (reduce weight) unreliable physiological data, relying instead more on environmental and posture determination. This fundamentally overcomes the technical deficiency of conventional wearable devices in high-frequency false alarms under harsh working conditions from the underlying algorithm logic.

[0048] In one embodiment, the identity management module generates a dynamic encryption factor during the verification process and supports dual authorization binding of identity information and remote data erasure.

[0049] The working principle and beneficial effects of the above technical solution are as follows: This module integrates a security element that supports the national cryptographic algorithm SM4, generates a dynamic encryption factor during verification, performs dual authorization binding upon onboarding, and allows the backend to issue an instruction to erase local identity data upon departure. It achieves hardware-level identity encryption and dynamic verification, effectively preventing identity information from being illegally copied or tampered with, and ensuring the security and flexibility of personnel management in scenarios such as attendance and access control.

[0050] In one embodiment, the alert module includes multiple vibration units, which achieve graded early warning through combinations of different vibration frequencies, durations, and vibration modes.

[0051] The working principle and beneficial effects of the above technical solution are as follows: The module adopts a dual-motor design, including a 100Hz warning motor and a 200Hz emergency motor. Based on the control module's instructions, it provides feedback to the wearer through combinations of different vibration modes. It can trigger vibration feedback of different frequencies according to the severity of the assessed risk, achieving timely and layered warning reminders, avoiding the insufficient awareness of emergency situations caused by a single reminder method.

[0052] In one embodiment, the communication positioning module integrates an ultra-wideband (UWB) positioning unit for indoor location tracking.

[0053] The working principle and beneficial effects of the above technical solution are as follows: The module integrates a DW1000 ultra-wideband (UWB) positioning unit, providing real-time indoor location data with an accuracy of ±30cm at a refresh rate of 1Hz. This enables high-precision tracking of the indoor location of workers, facilitating rapid location of trapped personnel in the event of an emergency, and greatly improving the efficiency of emergency rescue in industrial sites.

[0054] In one embodiment, the communication positioning module supports multiple wireless communication protocols, and the data transmission process employs an encrypted transmission protocol.

[0055] The working principle and beneficial effects of the above technical solution are as follows: The module supports Bluetooth 5.0 and Wi-Fi 6 protocols, and uses Transport Layer Security (TLS) version 1.3 for end-to-end encryption during data transmission. This ensures the confidentiality and integrity of physiological data, location information, and early warning information during wireless transmission, preventing critical business data from being maliciously intercepted or eavesdropped on.

[0056] In one embodiment, the storage module has a circular storage mechanism that automatically overwrites data.

[0057] The working principle and beneficial effects of the above technical solution are as follows: Data is stored using AES-256 encrypted flash memory chips, with a data retention period of no more than 30 days. Expired data is automatically overwritten upon expiration. Combining hardware-level encryption and an automatic overwrite mechanism, this solution meets the needs for short-term data backtracking while minimizing the risk of sensitive information leakage and optimizing the use of local storage space.

[0058] In one embodiment, the wristband has a privacy mode in which physiological monitoring is disabled while location tracking is retained.

[0059] The working principle and beneficial effects of the above technical solution are as follows: Users can manually switch to the non-working period mode via physical buttons. At this time, the microprocessor control module will turn off the physiological monitoring function, but maintain basic communication and positioning operations. While ensuring production safety management (such as positioning and basic communication), it fully respects and protects the personal privacy of employees during non-working periods, reflecting a human-centered design management philosophy.

[0060] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A multi-parameter safety monitoring smart bracelet for high-risk work environments, characterized in that, include: The main body has a protective structure and integrates a display unit; The sensor module integrates multiple sensors for collecting physiological, environmental, and motion data, and all of these sensors are equipped with protective structures and compensation circuits. The identity management module contains a security element for performing authentication based on cryptographic algorithms; The microprocessor control module is used to fuse and analyze sensor data and output control commands; The reminder module, connected to the microprocessor control module, is used to generate vibration feedback of different frequencies according to control commands; Storage module, used for encrypted data storage; The communication and positioning module is used for data transmission and indoor positioning.

2. The smart bracelet according to claim 1, characterized in that, The main body includes a built-in electromagnetic shielding structure and a waterproof and dustproof outer shell.

3. The smart bracelet according to claim 1, characterized in that, The sensor module includes physiological sensors, environmental sensors, and motion sensors; Among them, environmental sensors include electrochemical sensors used to monitor the concentration of harmful gases; Physiological sensors include heart rate sensors and body temperature sensors.

4. The smart bracelet according to claim 3, characterized in that, The microprocessor control module determines abnormal physiological states by using heart rate and body temperature data.

5. The smart bracelet according to claim 1, characterized in that, The identity management module generates dynamic encryption factors during the verification process and supports dual authorization binding of identity information and remote data erasure.

6. The smart bracelet according to claim 1, characterized in that, The alert module includes multiple vibration units, which achieve graded early warning through combinations of different vibration frequencies, durations, and vibration modes.

7. The smart bracelet according to claim 1, characterized in that, The communication positioning module integrates an ultra-wideband positioning unit.

8. The smart bracelet according to claim 1, characterized in that, The communication positioning module supports multiple wireless communication protocols, and the data transmission process uses an encrypted transmission protocol.

9. The smart bracelet according to claim 1, characterized in that, The storage module has a circular storage mechanism that automatically overwrites data.

10. The smart bracelet according to claim 1, characterized in that, The wristband has a privacy mode that can turn off the physiological monitoring function while retaining the location function.

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