An information security cap communication and safety monitoring system and method

Abstract

The application discloses an information safety helmet communication and safety monitoring system and method, and relates to the technical field of intelligent protective equipment; the scheme process of the application starts from collecting environment, equipment and behavior information of the information safety helmet, dynamically generates an activation instruction based on equipment power prediction: warns to charge when the power is insufficient, adjusts the monitoring period according to the exposure risk level when the power is sufficient; at the same time, the work scene is divided into blocks, the danger value of each point in each block is calculated through dangerous scene modeling, and the block environment risk value is analyzed in combination with the environment information (step 400), finally, the exposure risk index is calculated by cumulatively calculating the stay time, the environment risk value and the stay time and the danger value (step 500), the exposure warning is sent according to the exposure interval, and the exposure risk index is fed back to step 200 to form a self-adaptive safety monitoring cycle. The whole scheme integrates multi-source data, dynamic strategies and physical models, realizes the safety guarantee of the operating personnel and the optimization of the equipment efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent protective equipment, in particular to an information safety helmet communication and safety monitoring system and method. BACKGROUND

[0002] The information safety helmet is an intelligent safety helmet that integrates sensors, communication and alarm processing capabilities into the safety helmet, which can sense the state of the wearer and the surrounding environment in real time and report data and alarms to the management end to achieve active safety monitoring. The information safety helmet is mainly applied in dangerous working environments, such as construction, mining, chemical industry, power maintenance, tunnel construction, large-scale activities and other occasions requiring personnel safety and positioning, which can effectively protect the safety of the user. Therefore, the information safety helmet is a very important intelligent safety equipment.

[0003] As a front-end sensor, the information safety helmet collects personnel position, behavior, environment and other data for uploading, and then performs safety monitoring according to the uploaded data. The information safety helmet integrates numerous electronic components, and its power consumption is greatly increased compared to traditional safety helmets, which means that frequent charging is required. However, during this process, workers need to work in harsh environments for a long time, and the information safety helmet also needs to work in standby mode for a long time. As a result, there are few charging windows, and the information safety helmet may fail at critical moments due to lack of power, causing serious safety hazards. SUMMARY

[0004] Therefore, it is necessary to provide an information safety helmet communication and safety monitoring system and method to solve the problems mentioned in the background.

[0005] The purpose of the present application can be achieved by the following technical solutions:

[0006] On the one hand, the present application provides an information safety helmet communication and safety monitoring system, comprising an information collection module, a power monitoring module, a work site modeling module, an environment analysis module and a safety monitoring module.

[0007] The information collection module is connected to the information safety helmet through communication, and issues an activation instruction to the information safety helmet to activate the information safety helmet to collect device information, environmental information and behavior information.

[0008] The power monitoring module predicts the power based on the device information and compares it with the predicted work duration to execute corresponding strategies, including power warning and monitoring period adjustment. Based on the adjusted monitoring period, an activation instruction is generated and updated to the information collection module.

[0009] The work site modeling module calculates the static danger value by block based on the pre-stored 3D layout of the work scene and the marked dangerous area, and constructs a spatial danger field by superimposing different distance attenuation coefficients.

[0010] The environmental analysis module performs environmental analysis based on environmental information to output the environmental risk value of the location of the information safety helmet;

[0011] The safety monitoring module performs overlay analysis based on behavioral information and hazardous fields, and then combines environmental risk values ​​to accumulate exposure and output an exposure risk index. If the exposure risk index is greater than the upper limit of the exposure range, a level 1 exposure is generated and an exposure warning is issued; if the exposure risk index is within the exposure range, a level 2 exposure is generated; if the exposure risk index is less than the lower limit of the exposure range, a level 3 exposure is generated.

[0012] In some embodiments, the process of predicting power consumption based on device information and comparing it with the expected operating duration is as follows:

[0013] Obtain the nearest off-get off work time to the current time and calculate the estimated task duration by comparing the time difference between the estimated and current times. There is a preset minimum usage time. If the estimated task duration is greater than or equal to the minimum usage time, the minimum usage time will be used as the base duration. If the estimated task duration is less than the minimum usage time, the estimated task duration will be used as the base duration.

[0014] If the expected battery life is less than the baseline battery life, a charging warning will be generated.

[0015] If the expected battery life is greater than or equal to the baseline duration, the monitoring cycle will be dynamically adjusted to generate an activation command.

[0016] In some embodiments, the monitoring cycle is dynamically adjusted:

[0017] Obtain the exposure risk value and exposure level generated from the most recent monitoring. If the exposure level is level 2, generate a monitoring strategy dominated by safety constraints. If the exposure level is level 3, generate a monitoring strategy dominated by power constraints.

[0018] In some embodiments, a security-constrained monitoring strategy is employed:

[0019] The latest monitoring cycle is obtained by formulaically calculating and analyzing the exposure risk index A. The calculation formula is:

[0020] Q max and Q min These represent the longest and shortest allowed monitoring periods, respectively. λ is the risk sensitivity coefficient, where λ > 0. The risk sensitivity coefficient controls the severity of the impact of risk on the period. The most recent monitoring time is obtained, and the time difference between it and the current time is calculated to obtain the time interval. If the time interval is greater than or equal to the latest monitoring period, an activation command is generated.

[0021] In some embodiments, a monitoring strategy primarily based on power constraints is employed.

[0022] The latest monitoring cycle is obtained by formulaic calculation and analysis of the remaining power D. The calculation formula is:

[0023] Obtain the most recent monitoring time from the current time, calculate the time interval by comparing the time difference with the current time, and generate an activation command if the time interval is greater than or equal to the latest monitoring cycle.

[0024] In some embodiments, a space hazard field is constructed:

[0025] The system stores a pre-defined 3D layout map of the entire work scenario, with hazardous areas marked on the map. The scenario is divided into several sections, and m hazardous areas (where m is a positive integer) are extracted from each section. Each pre-marked hazardous area is assigned a fixed static hazard value and a distance attenuation coefficient, denoted as H. i and K i Where i = 1, 2, 3...m, i represents the index of any dangerous region within the plate; any other location within the plate besides the dangerous regions is denoted as point P. The total impact of all dangerous regions within the plate on this point is obtained by linearly superimposing the attenuated dangerous components of all m dangerous regions within the plate at that point, thus yielding the dangerous value H. total (P), the calculation formula is:

[0026] Based on the danger value H corresponding to any point P within the plate. total (P) Construct a hazard field within the plate, where P is any point within the plate excluding the hazard zone; where d i (P) refers to the geometric distance from point P to the center of the danger zone i, calculated using the Euclidean spatial distance formula: Where the three-dimensional coordinates of point P are (x(P), y(P), z(P)), and the three-dimensional coordinates of danger zone i are (x(P), y(P), z(P)) i y i , z i ); Let be the danger component of the i-th danger zone relative to the location of point P.

[0027] In some embodiments, the process of performing environmental analysis based on environmental information is as follows:

[0028] Extract environmental information of the information safety helmet within the module. Specific environmental information includes temperature, humidity, concentration of inhalable particulate matter, oxygen concentration, concentration of combustible gas, and concentration of toxic gas. Analyze the environmental risks based on the environmental information to output the environmental risk value of the location of the information safety helmet.

[0029] Step 401: Extract the environmental information of the information safety helmet within the module. The specific environmental information includes temperature, humidity, concentration of inhalable particulate matter, oxygen concentration, concentration of combustible gas, and concentration of toxic gas. Set up safe zones with reference to safety regulations. The safe zones include safe temperature zone, safe humidity zone, safe particulate matter zone, safe oxygen zone, safe combustible gas zone, and safe toxic gas zone.

[0030] Step 402: Relative to the safe range, calculate the independent risk state of each parameter to obtain the risk component corresponding to each environmental parameter, specifically the temperature risk component R. T Humidity risk component R S Particulate matter risk component R PM Oxygen risk components Combustible gas risk component R com and the risk component R of toxic gases tox ;

[0031] Step 403, assign the temperature risk component R T Humidity risk component R S Particulate matter risk component R PM Oxygen risk components Combustible gas risk component R com and the risk component R of toxic gases tox The environmental risk value is obtained by performing linear weighted fusion, and the environmental risk value of each information security helmet in each segment can be obtained from this. The average value of these values ​​is then used to calculate the environmental risk index of each segment, which is then marked in the corresponding segment of the 3D layout diagram.

[0032] In some embodiments, the process of outputting the exposure risk index is as follows:

[0033] 8-1. Extract the online time of the information safety helmet from the time it went online to the current time, and count the dwell time of the information safety helmet in each section. Then, take the section with a dwell time > 0 as the dwell section of the information safety helmet. Multiply the dwell time corresponding to the dwell section of the information safety helmet by its corresponding environmental risk value to obtain the dwell risk component of the dwell section, which is denoted as Z.

[0034] 8-2, Based on behavioral information and hazard field overlay analysis, output the risk component of the information safety helmet's stay in each section;

[0035] 8-3. The exposure risk component is obtained by linearly weighting and fusing the retention risk component and the dwell risk component of the information safety helmet in each module. Then, the exposure risk components of the information safety helmet in each module are summed to obtain the cumulative exposure risk index of the information safety helmet, and then updated to the power monitoring module.

[0036] In some embodiments, an overlay analysis is performed based on behavioral information and the hazard field:

[0037] The behavioral information of the information safety helmet in each section is extracted. Specifically, this includes the helmet's walking trajectory within each section and the duration of its stay at each location, denoted as Fj. The walking trajectory is then compared with the hazard field within each section to obtain the H value of the walking trajectory at each location. total (j), where j is a positive integer, j=1,2,3..., and j represents the index of any position on the walking trajectory; according to the formula The component of the dwell risk experienced by the information safety helmet when walking within the plate was calculated.

[0038] On the other hand, the present invention provides an information safety helmet communication and safety monitoring method, comprising the following steps:

[0039] Step 100: Establish a communication connection with the information safety helmet and activate the information safety helmet to collect device information, environmental information, and behavioral information by issuing an activation command to the information safety helmet;

[0040] Step 200: Based on the equipment information, perform power prediction and compare it with the expected operation time to execute the corresponding strategy, including power warning and monitoring cycle adjustment. Generate an activation command based on the adjusted monitoring cycle and update it to step 100.

[0041] Step 300: Based on the pre-stored 3D layout map of the work scene and the marked dangerous areas, the static hazard value is calculated by section and a spatial hazard field is constructed by superimposing different distance attenuation coefficients.

[0042] Step 400: Perform environmental analysis based on environmental information to output the environmental risk value of the location of the information safety helmet;

[0043] Step 500: Based on the behavioral information and the hazardous field, perform overlay analysis, and then combine the environmental risk value to accumulate exposure to output an exposure risk index. If the exposure risk index is greater than the upper limit of the exposure range, a level 1 exposure is generated and an exposure warning is executed; if the exposure risk index is within the exposure range, a level 2 exposure is generated; if the exposure risk index is less than the lower limit of the exposure range, a level 3 exposure is generated.

[0044] Compared with the prior art, the beneficial effects of the present invention are:

[0045] 1. The information safety helmet integrates a variety of electronic components to collect device information, environmental information and behavioral information as a data sensing layer. It is activated and collected according to activation instructions, which creates conditions for subsequent intelligent power consumption management, avoids energy waste caused by continuous sensor operation, and lays the foundation for the long battery life of the device from the source. It is the primary link to realize the intelligent and sustainable operation of the entire system.

[0046] 2. By extracting the remaining power and the average power consumption rate over the past two hours to predict the battery life, and comparing the expected operating time with the minimum usage time, it can proactively identify the risk of insufficient power and issue charging warnings, reducing the probability of equipment failure at critical moments from an organizational and operational perspective; Based on the battery life and exposure risk, it dynamically generates the collection frequency and activation command to achieve adaptive monitoring of energy consumption perception, significantly extending the terminal's usability while ensuring safety sensitivity, and coupling power management with risk management. It ensures high-frequency sampling and alarms in critical scenarios, while retaining the minimum alarm capability through reasonable downsampling in low-risk or insufficient power situations, thus balancing safety and continuity.

[0047] 3. By dividing the work site into sections according to a three-dimensional layout and assigning a static hazard value and a distance attenuation coefficient based on physical or regulatory back-calculation to each hazardous area, abstract hazard sources can be transformed into spatialized and visualized hazardous fields. This allows real-time positioning data to be directly mapped to specific risk areas, enhancing the interpretability and credibility of risk assessment for workers. At the same time, it also facilitates safety personnel in developing targeted access permissions, improving the pertinence and effectiveness of risk control.

[0048] 4. By standardizing the multi-parameter environmental information collected from the cap according to industry safety ranges and calculating the risk components of each parameter, and then weighting and integrating them according to the severity and immediacy of the consequences to form an environmental risk index, multi-factor collaborative judgment is achieved instead of relying on a single threshold, reducing the probability of false alarms and false alarms and focusing attention on the factors that pose the greatest threat to personnel. The environmental risk index can be used for sector-level risk visualization and as the core input for exposure accumulation, effectively eliminating the redundancy of multi-parameter information, highlighting the main contradictions, and providing a standardized and comparable risk intensity input for calculating the exposure risk index of personnel in different sectors in step 500.

[0049] 5. By statistically analyzing the duration of workers' stay in each section and multiplying it by the section's environmental risk index, a stay risk component is obtained. This is combined with the hazard value and stay duration of each location along the walking trajectory to obtain a dwelling risk component. Finally, these components are linearly weighted and merged into a section exposure component, which is then summed to obtain the cumulative exposure risk index for workers. This accurately quantifies individual exposure load and identifies individuals with long-term high exposure or repeated exposure. Based on the exposure interval, a three-level response is implemented, such as mandatory local evacuation or adjustment of monitoring frequency. This achieves a leap from area monitoring of sections to individual proactive protection, directly and effectively alerting high-risk workers to evacuate in a timely manner, truly forming a closed loop of safety management encompassing risk perception, assessment, early warning, and intervention. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application or the conventional technology, the drawings used in the description of the embodiments or the conventional technology will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 This is a schematic diagram of the system module connections of the present invention;

[0052] Figure 2 This is a schematic diagram of the process flow of the method of the present invention. Detailed Implementation

[0053] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0054] As a front-end sensor, the information safety helmet collects data such as personnel location, behavior, and environment, and uploads it to the cloud management platform. The cloud management platform performs safety monitoring based on the uploaded data. It integrates many electronic components, and its power consumption is much higher than that of traditional safety helmets, which means that it needs to be charged frequently. However, in this process, since workers need to work in harsh environments for a long time, the information safety helmet also needs to work in standby mode for a long time, which can easily lead to the helmet becoming ineffective due to power failure at critical moments.

[0055] This embodiment is applicable to high-risk operational scenarios requiring continuous, graded, and safe management of personnel exposure and the on-site environment, such as construction sites, tunnels and underground engineering, mines, petrochemical and chemical plants, power generation and distribution sites, and large temporary event venues. It aims to achieve real-time perception, adaptive energy consumption sampling, spatial risk modeling, and cumulative early warning of personnel exposure through the collaboration of wearable devices with cloud and edge platforms. The required hardware facilities include: a smart safety helmet as the front end for perception and alarm (with built-in temperature and humidity sensors, inhalable particulate matter sensors, oxygen sensors, combustible gas sensors, toxic gas sensors, inertial measurement units and position modules, microcontrollers and local storage, low-power wireless communication modules, indicator lights, buzzers, etc.).

[0056] like Figure 1 As shown, this embodiment provides an information safety helmet communication and safety monitoring system, including: an information acquisition module, a power monitoring module, a work site modeling module, an environmental analysis module, and a safety monitoring module;

[0057] The information acquisition module communicates with the information safety helmet and activates it to collect device information, environmental information, and behavioral information by issuing activation commands to the helmet. The information safety helmet consists of an information module and a helmet body, with the information module integrated into the helmet body. It sends device information to the power monitoring module, environmental information to the environmental analysis module, and behavioral information to the safety monitoring module.

[0058] The power monitoring module predicts power consumption based on equipment information and compares it with the expected operating time to execute corresponding strategies, including power warning and monitoring cycle adjustment. The monitoring cycle adjustment is based on the exposure risk index and remaining power. Based on the adjusted monitoring cycle, an activation command is generated and updated to the information acquisition module to control the information acquisition and upload frequency of the information safety helmet, thereby achieving long battery life for the information safety helmet.

[0059] The work site modeling module calculates static hazard values ​​by section based on the pre-stored 3D layout map of the work scene and marked hazardous areas, and constructs a spatial hazard field by superimposing different distance attenuation coefficients. It then sends the field to the safety monitoring module so as to accurately quantify the degree of exposure of workers to hazardous areas during walking.

[0060] The environmental analysis module analyzes the environmental information to output the environmental risk value of the location of the safety helmet and sends it to the safety monitoring module so as to accurately quantify the degree of exposure of the workers to the environmental conditions of the plate during the walking process.

[0061] The safety monitoring module performs overlay analysis based on behavioral information and hazardous fields, and then combines environmental risk values ​​to accumulate exposure and output an exposure risk index. If the exposure risk index is greater than the upper limit of the exposure range, a level 1 exposure is generated and an exposure warning is issued; if the exposure risk index is within the exposure range, a level 2 exposure is generated and the exposure risk index is sent to the power monitoring module; if the exposure risk index is less than the lower limit of the exposure range, a level 3 exposure is generated and the exposure risk index is sent to the power monitoring module.

[0062] Compared to existing safety helmets, which experience a surge in power consumption after integrating multiple sensors, severely conflicting with the demands of long shifts and high-intensity continuous operations in the industrial sector, frequent charging or power outages lead to decreased equipment reliability and loss of protective function at critical moments, creating safety hazards, this embodiment accurately measures the exposure risk of workers by combining on-demand sensing, energy consumption sensing adaptive sampling monitoring, three-dimensional spatial hazard field and dose-time exposure accumulation. This effectively resolves the contradiction between safety monitoring sensitivity and terminal battery life, thereby improving on-site personnel protection capabilities while reducing operation and maintenance costs and enhancing the system's engineering availability and traceability.

[0063] Furthermore, to better illustrate the technical solution of the aforementioned information safety helmet communication and security monitoring system, such as... Figure 2 As shown, this embodiment of the invention combines an information safety helmet communication and security monitoring method, which is described in detail and includes the following steps:

[0064] Step 100: The information safety helmet integrates various electronic components. Upon receiving an activation command, these components are activated to collect and upload environmental, device, and behavioral information in real time. It should be noted that the activation command is generated in step 200 based on a comprehensive analysis of the helmet's battery level and its surrounding environment. This is to ensure safety monitoring while conserving power. Communication with the helmet is established only upon receiving the activation command to collect device, environmental, and behavioral information. Environmental information includes temperature, humidity, inhalable particulate matter concentration, oxygen concentration, combustible gas concentration, and toxic gas concentration. Device information includes remaining battery power and the battery consumption rate within the last n hours. Behavioral information includes the helmet's walking trajectory... The information safety helmet records the worker's walking trajectory and dwell time at each location throughout the operation. It should be noted that the helmet only activates to collect equipment and environmental information upon receiving an activation command, and then uploads this information, along with the behavioral data. In other words, behavioral information is continuously recorded, while environmental and equipment information is activated on demand. The information safety helmet integrates various electronic components, acting as a data sensing layer to collect equipment and environmental information. Activation is based on the activation command, creating conditions for intelligent power management in step 200. This avoids energy waste caused by continuous sensor operation, laying the foundation for long-lasting equipment operation from the source. It is the primary link in achieving intelligent and sustainable operation of the entire system.

[0065] Step 200: Extract the device information of the information security helmet, predict the device power consumption based on the device information to generate a corresponding sampling frequency, generate an activation command based on the sampling frequency, and send it to step 100; specifically:

[0066] The device information is extracted, including the remaining battery power and the battery consumption rate within the nearest n hours. The remaining battery power is divided by the battery consumption rate to obtain the estimated battery life. Here, n is a constant greater than zero, which is set to 2 hours by those skilled in the art. The value of n is chosen to balance prediction accuracy and response timeliness: a two-hour window can cover the energy consumption fluctuations of the information safety helmet under common work intensity without being excessively interfered with by extremely short-term impulse noise, thus obtaining a relatively stable and representative average consumption rate for short-term battery life estimation and early warning; at the same time, two hours is sufficient to reserve operable time for operation and maintenance scheduling (such as shift battery swapping, temporary power replenishment), facilitating the timely issuance of operation and maintenance instructions; the battery consumption rate is % / h; for example, if the battery power of a safety helmet drops from 100% to 80% in 2 hours, then its average battery consumption rate in these 2 hours is (100%-80%) / 2 hours = 10% / hour.

[0067] The system obtains the nearest end-of-shift time and calculates the estimated operation duration by comparing it with the current time. A minimum usage duration is preset, which is set to 2.5 hours by those skilled in the art. This minimum usage duration is designed based on a comprehensive trade-off between on-site operation rhythm, battery life prediction accuracy, and safety redundancy. On the one hand, selecting a benchmark slightly longer than the two-hour window used to estimate power consumption (i.e., 2.5 hours) allows for a safety margin in predicting short-term average power consumption, addressing the uncertainties caused by sudden high power consumption and battery performance affected by temperature and aging. On the other hand, 2.5 hours facilitates coordination with shift changes, temporary battery swaps, or charging arrangements, while avoiding setting the threshold too high to prevent frequent false alarms or increased maintenance costs. The design principles also include two boundary logics: if the estimated operation duration before the end of the shift is greater than or equal to this minimum duration, then this minimum duration is used as the minimum guarantee (ensuring the equipment can cover at least a reasonable maintenance response window); if the estimated operation duration is less than the minimum duration, then the estimated operation duration is used as the benchmark to avoid unnecessary charging reminders for short-term operations nearing the end of the shift.

[0068] If the estimated operation time is greater than or equal to the minimum usage time, the minimum usage time will be used as the base time; if the estimated operation time is less than the minimum usage time, the estimated operation time will be used as the base time.

[0069] If the expected battery life is less than the baseline time, it means that the information helmet's current battery level is insufficient to maintain the minimum required usage. A charging warning will then be generated to remind the user to charge the information helmet in a timely manner.

[0070] If the expected battery life is greater than or equal to the baseline duration, it means that the information safety helmet currently has sufficient power to maintain necessary usage. The monitoring cycle will then be dynamically adjusted based on the exposure risk index and remaining battery power to generate an activation command; specifically:

[0071] Each information safety helmet is pre-set to have an exposure risk index for each monitoring session. The exposure risk index is a value that comprehensively measures the exposure risk by combining the user's location and the duration of time spent at each location. The exposure risk value and exposure level generated from the most recent monitoring session are obtained. If the exposure level is level 2, a monitoring strategy based on safety constraints is generated. If the exposure level is level 3, a monitoring strategy based on power constraints is generated.

[0072] A safety-constrained monitoring strategy: The latest monitoring cycle is obtained by formulaically calculating and analyzing the exposure risk index A. The specific calculation formula is as follows:

[0073] Among them, Q max and Q minThese are the maximum and minimum monitoring periods allowed, respectively. The minimum monitoring period setting is to prevent the device from being activated frequently due to an excessively short monitoring period, which would increase power consumption. If the monitoring period exceeds the maximum monitoring period, the monitoring becomes meaningless. λ is the risk sensitivity coefficient, where λ > 0. The risk sensitivity coefficient controls the severity of the impact of risk on the period.

[0074] A monitoring strategy primarily driven by power constraints: The latest monitoring cycle is obtained through formulaic calculation and analysis of the remaining power D. The calculation formula is:

[0075] It should be noted that the latest monitoring period varies between the two strategy modes. and It naturally falls within the interval [Q_min, Q_max] and requires no additional constraints; obtain the most recent monitoring time from the current time, calculate the time interval by the time difference between it and the current time, and generate an activation command if the time interval is greater than or equal to the latest monitoring cycle;

[0076] By extracting remaining power and the average power consumption rate over the past two hours to predict battery life, and comparing the expected operating time with the minimum usage time, the system can proactively identify low power risks and issue charging warnings, reducing the probability of equipment failure at critical moments from an organizational and operational perspective. Based on battery life and exposure risks, the system dynamically generates collection frequencies and activation commands to achieve adaptive monitoring of energy consumption. While ensuring safety sensitivity, it significantly extends the terminal's usability time, coupling power management with risk management. This ensures high-frequency sampling and alarms in critical scenarios, while retaining minimum alarm capabilities through reasonable downsampling in low-risk or low-power situations, balancing safety and continuity.

[0077] Step 300: A 3D layout map of the entire work scenario is pre-stored. Hazardous areas are marked on the 3D layout map, such as high-temperature equipment and high-voltage electrical cabinets. These are specific physical areas or spatial ranges that may cause harm to workers, as defined by the work safety officer according to the work rules. Their ranges are usually fixed and determined primarily by the fixed facilities and physical structure on site. The entire work scenario is divided into several sections, each with workers operating within it; that is, each section has a safety helmet. It should be noted that the work assignments within each section are arranged by management personnel, which is a standard arrangement for this work scenario. It should also be noted that the section division of the entire work scenario is not based on a single standard, but rather comprehensively considers the physical structure, work functions, hazard distribution, management methods, and technical conditions to ensure that the divided sections can effectively address hazards. The system should accurately reflect the characteristics of operations and risks while facilitating monitoring and management. Specifically, it should use physical boundaries such as factory areas, tunnels, workshops, floors, rooms, and corridors as natural divisions to ensure that each section corresponds to a clear three-dimensional spatial range. It should be divided according to different production or operational stages to align with personnel tasks and job distribution. Priority should be given to the spatial concentration or distribution of hazardous sources, dividing areas with concentrated high-risk equipment and facilities into independent sections for targeted risk calculation and monitoring. Combined with on-site management practices and personnel scheduling methods, the division results should correspond to management responsibility areas, work group divisions, or task assignments, facilitating data management and accountability tracking. Finally, the signal coverage, positioning accuracy, and communication capabilities of information safety helmets or other sensors should be considered to ensure the division results are compatible with the technical conditions of sensing and transmission.

[0078] Extract m hazardous areas distributed within the plate, where m is a positive integer; pre-determine that each pre-labeled hazardous area corresponds to a fixed static hazard value and a distance attenuation coefficient, and denote them as H respectively. i and K iWhere i = 1, 2, 3...m, i represents the index of any hazardous area within the block; the static hazard value is determined by safety experts in this work scenario based on a comprehensive balance of hazard type, severity of potential consequences, and trigger probability. For example, the static hazard value of an open distribution box is set at 90 (out of 100), while the static hazard value of a platform edge with guardrails is set at 70. It should be noted that for any hazardous area within each block, the degree of hazard impact decreases with increasing distance. Furthermore, the degree of decrease varies for each type of hazardous area due to the drastically different modes of propagation and action of energy or harmful substances from different hazard sources. The distance attenuation coefficient directly determines the range of influence and the attenuation characteristics in space. Therefore, in order to accurately quantify the attenuation effect of different dangerous areas, different distance attenuation coefficients are set. The distance attenuation coefficient is a key parameter in the mathematical model. It controls the rate attenuation of the danger value with distance. Those skilled in the art can solve the corresponding distance attenuation coefficient by reverse engineering the safety distance or influence boundary defined in the relevant regulations or standards of the dangerous sources in each dangerous area. By using the method based on standards and physical models, a unique distance attenuation coefficient can be set for each type of dangerous area in a scientific and reasonable manner, so that the calculation of the entire dynamic risk map is both in line with the theory and meets the needs of actual safety management.

[0079] Let point P be any location within the plate other than the danger zone. The total impact of all danger zones on it is obtained by linearly superimposing the attenuated danger components of all m danger zones within the plate at that point, thus yielding the danger value H. total (P), the calculation formula is:

[0080] Based on the danger value H corresponding to any point P within the plate. total (P) Construct a hazard field within the plate, where P is any point within the plate excluding the hazard zone; where d i (P) refers to the geometric distance from point P to the center of the danger zone i, calculated using the Euclidean spatial distance formula:

[0081] Where the three-dimensional coordinates of point P are (x(P), y(P), z(P)), and the three-dimensional coordinates of danger zone i are (x(P), y(P), z(P)) i y i , z i ); The term is an exponential decay term, responsible for reducing the static hazard value H of the i-th hazard region. i According to distance d i (P) is attenuated; Let be the danger component of the i-th danger zone relative to the location of point P. This formula simulates the concept of field theory in physics. Each danger zone forms a danger field in the space around it. Its intensity (i.e., static danger value) decreases with increasing distance. The total field strength at a certain point in space (i.e., the sum of danger components) is equal to the algebraic sum of the field strengths generated by all independent field sources at that point. This conforms to the superposition principle of classical physical fields (such as electric field, magnetic field, and gravitational field), is intuitive and logical, and accurately reflects the real complex risk situation.

[0082] By dividing the work site into sections according to a three-dimensional layout and assigning a static hazard value and a distance attenuation coefficient based on physical or regulatory back-calculation to each hazardous area, abstract hazard sources can be transformed into spatialized and visualized hazardous fields. This allows real-time positioning data to be directly mapped to specific risk areas, enhancing the interpretability and credibility of risk assessment for workers. At the same time, it also facilitates safety personnel in developing targeted access permissions, improving the pertinence and effectiveness of risk management.

[0083] Step 400: Extract environmental information of the information safety helmet (i.e., the worker) within the module. Specific environmental information includes temperature, humidity, concentration of inhalable particulate matter, oxygen concentration, concentration of combustible gases, and concentration of toxic gases. Based on this environmental information, analyze the environmental risk to output the environmental risk value for the location of the information safety helmet; specifically:

[0084] Step 401: Record the temperature, humidity, inhalable particulate matter concentration, oxygen concentration, combustible gas concentration, and toxic gas concentration as T, S, and C, respectively. PM C O2 C com C toxIt should be noted that combustible gases refer to gases that pose a risk of explosion or fire, including but not limited to methane and hydrogen; toxic gases refer to gases that pose a risk of poisoning or acute health damage, including but not limited to carbon monoxide, hydrogen sulfide, and sulfur dioxide; a preset safety range is defined, including a safe temperature range, a safe humidity range, a safe particulate matter range, a safe oxygen range, a safe combustible range, and a safe toxic range. Those skilled in the art, referring to GB / T4200-2008 Classification of High-Temperature Operations, set the suitable working temperature to 18-28℃, and referring to GB / T18883-2002 Indoor Air Quality Standard and general industrial hygiene recommendations, set the safe working humidity to 40%-60%; and referring to GBZ2.1-2019 Occupational Exposure Limits for Hazardous Factors in the Workplace Part 1: Chemical Hazards The safety particulate matter concentration is set at [0, 4 mg / m³] according to the "Factors". Referring to "GB8958-2006 Safety Regulations for Oxygen-Deficient Hazardous Operations" and the safety design specifications for various gas detection instruments, the safety oxygen range is set at [19.5% VOL, 23.5% VOL]. Referring to "GB50493-2019 Design Standard for Combustible and Toxic Gas Detection Alarms in Petrochemical Industry", the safety combustible concentration is set at [0, 10% LEL]. Referring to "GBZ2.1-2019 Occupational Exposure Limits for Hazardous Factors in the Workplace Part 1: Chemical Hazardous Factors", the safety toxic concentration is set at [0, 10 mg / m³]. Here, LEL is a fixed, known percentage value of volume concentration. The integrated combustible gas sensor on the safety helmet has this conversion process built in, directly outputting a reading in %LEL units.

[0085] Step 402: Relative to the safe range, calculate the independent risk state of each parameter to obtain the risk component corresponding to each environmental parameter, specifically the temperature risk component R. T Humidity risk component R S Particulate matter risk component R PM Oxygen risk component R O2 Combustible gas risk component R com and the risk component R of toxic gases tox ;

[0086] (1) Temperature T, the calculation formula is: ;

[0087] (2) Humidity S, the calculation formula is: ;

[0088] (3) Concentration of inhalable particulate matter C PM The calculation formula is: ;

[0089] (4) Oxygen concentration C O2 The calculation formula is: ;

[0090] (5) Combustible gas concentration C com The calculation formula is: ;

[0091] (6) Concentration of toxic gas C tox The calculation formula is: ;

[0092] Step 403, assign the temperature risk component R T Humidity risk component R S Particulate matter risk component R PM Oxygen risk component R O2 Combustible gas risk component R com and the risk component R of toxic gases tox The environmental risk value Risk is obtained by performing linear weighted fusion. The specific linear weighted fusion formula is as follows:

[0093] Among them W T W S W PM W O2 W com and W tox These are the temperature risk components R. T Humidity risk component R S Particulate matter risk component R PM Oxygen risk component R O2 Combustible gas risk component R com and the risk component R of toxic gases toxThe weighting coefficients are 0.05, 0.05, 0.1, 0.2, 0.3, and 0.3, respectively. These weighting coefficients are designed by those skilled in the art based on the severity of consequences, time urgency, risk development speed, and scenario adaptability of each parameter. The primary criterion is the severity of consequences, assigning higher weights to factors that can rapidly lead to death or large-scale disasters (such as flammable and toxic gases). Immediacy and irreversibility are considered (risks that are sudden and difficult to reverse in a short time have higher weights), while also taking into account detection reliability and feasible on-site response methods (factors with stable detection and rapid handling can be appropriately weighted). Oxygen, as an amplifying factor, has a medium weight because it can significantly amplify or inhibit the hazards of other gases. Particulate matter, temperature, and humidity have smaller weights because they are mostly long-term or indirect effects. The principle of calculating environmental risk values ​​using the above linear weighted fusion formula is to first combine different environmental parameters... (Temperature, humidity, particulate matter, oxygen, combustible gas, toxic gas) are standardized based on their respective safety ranges to obtain independent risk components for each parameter. Then, differentiated weights are assigned to each parameter according to the severity, immediacy, risk development speed, and scenario adaptability of its consequences to personnel safety in the working environment. Finally, a unified environmental risk value is obtained through linear weighted fusion. This avoids the limitations of traditional solutions that rely on a single threshold for risk assessment, enabling environmental risk assessment to comprehensively reflect the combined effects of multiple factors and highlight the factors that pose the most direct and urgent harm to personnel (such as toxic gases and combustible gases). It solves the problems of one-sided risk assessment, high false alarm and false alarm rates, and difficulty in eliminating information redundancy between parameters. From this, the environmental risk value of each information safety helmet in each section can be obtained, and the average value can be calculated to obtain the environmental risk index of each section, which is then marked in the corresponding section of the 3D layout diagram.

[0094] By standardizing the multi-parameter environmental information collected from the cap according to industry safety ranges and calculating the risk components of each parameter, and then weighting and integrating them according to the severity and immediacy of the consequences to form an environmental risk index, multi-factor collaborative judgment is achieved instead of relying on a single threshold. This reduces the probability of false alarms and false alarms and focuses attention on the factors that pose the greatest threat to personnel. The environmental risk index can be used for sector-level risk visualization and also serves as the core input for exposure accumulation. It effectively eliminates the redundancy of multi-parameter information, highlights the main contradictions, and provides a standardized and comparable risk intensity input for calculating the exposure risk index accumulated by personnel in different sectors in step 500.

[0095] Step 500: Extract the online time of the information safety helmet from its launch to the current time (e.g., the information safety helmet was launched at 9:00 AM today, workers started working, and it is now 11:00 AM, so the online time is 2 hours). Calculate the dwell time of the information safety helmet in each section, and designate sections with a dwell time > 0 as the dwell sections of the information safety helmet. Note that the online time is obtained by summing the dwell times of the information safety helmet in each dwell section. Multiply the dwell time corresponding to the dwell section of the information safety helmet by its corresponding environmental risk value to obtain the dwell risk component of the dwell section, denoted as Z.

[0096] The behavioral information of the information safety helmet in each section is extracted. Specifically, this includes the helmet's walking trajectory within each section and the duration of its stay at each location, denoted as Fj. The walking trajectory is then compared with the hazard field within each section to obtain the H value of the walking trajectory at each location. total (j), where j is a positive integer, j=1,2,3..., and j represents the index of any position on the walking trajectory; according to the formula The dwell risk component L received by the information safety helmet when walking within the plate was calculated;

[0097] The exposure risk component is calculated by linearly weighting and fusing the residual risk component Z and the dwell risk component L of the information safety helmet in each section using the formula A=0.6×Z+0.4×L. In this linear weighting and fusing formula, the residual risk weight is taken as 0.6 and the walking dwell risk weight is taken as 0.4. This is because in most work scenarios, the parameters in the environmental information contribute more directly and significantly to the cumulative dose and chronic hazards, and should be given higher priority. On the other hand, although the exposure caused by the hazardous field is important, its overall contribution is relatively secondary, so a smaller weight is taken. The principle is to achieve a comprehensive balance of the cumulative dose and chronic hazards of each parameter by quantitatively distinguishing the timeliness and severity of the effects of different risk factors. This allows the exposure risk index to reflect both the overall cumulative risk level of the workers and the impact of instantaneous high-risk points in the walking path, thereby improving the scientificity and comprehensiveness of the index.

[0098] Then, the exposure risk components of the information safety helmet in each section are summed to obtain the cumulative exposure risk index of the information safety helmet;

[0099] An exposure range is preset, with values ​​in the range [30, 60]. This exposure range is designed by those skilled in the art based on occupational exposure limits, dose-response relationships, and action levels. First, acceptable and unacceptable risks are mapped to critical values ​​on an exponential scale with reference to occupational exposure limits. Second, the cumulative effect of exposure intensity and time is quantified based on dose-response relationships, with higher indices corresponding to greater and faster probabilities of health damage. Third, action level practices are used as an early warning starting point so that monitoring and control measures can be taken before the hazard reaches a critical level. If the exposure risk index is greater than the upper limit of the exposure range... If the information safety helmet user has accumulated a relatively high risk of environmental exposure, a Level 1 exposure is generated, and the information safety helmet is controlled to issue an exposure warning. The exposure warning is specifically: the LED indicator on the information safety helmet flashes red light at a high frequency and emits a rapid, high-pitched buzzer to notify the workers using the information safety helmet to evacuate the site in time; if the exposure risk index is within the exposure range, a Level 2 exposure is generated; if the exposure risk index is less than the lower limit of the exposure range, a Level 3 exposure is generated; the Level 2 exposure and its corresponding exposure value or the Level 3 exposure and its corresponding exposure value are sent to step 200.

[0100] By statistically analyzing the dwell time of workers (information safety helmets) in each section and multiplying it by the section's environmental risk index, a dwell risk component is obtained. This is combined with the hazard value and dwell time of each location along the walking trajectory to obtain a stay risk component. Finally, these components are linearly weighted and merged into a section exposure component, which is then summed to obtain the cumulative exposure risk index for the workers. This accurately quantifies individual exposure load and identifies individuals with long-term high exposure or repeated exposure. Based on exposure intervals, a three-level response is implemented, such as mandatory local evacuation or monitoring frequency adjustment. This achieves a leap from area monitoring of sections to proactive individual protection, directly and effectively alerting high-risk workers to evacuate in a timely manner, truly forming a closed loop of safety management encompassing risk perception, assessment, early warning, and intervention.

[0101] The process of this invention begins with the information safety helmet collecting environmental, equipment, and behavioral information (step 100). Based on equipment battery prediction (step 200), activation instructions are dynamically generated: a charging warning is issued when the battery is low, and the monitoring cycle is adjusted according to the exposure risk level (from step 500) when the battery is sufficient. Simultaneously, the work scenario is divided into sections, and the hazard value of each point in each section is calculated through hazard field modeling (step 300). This is combined with environmental information (step 400) to analyze the environmental risk value of each section. Finally, the exposure risk index is calculated by accumulating the dwell time with the environmental risk value, dwell time, and hazard value (step 500). An exposure warning is issued based on the exposure interval, and the exposure risk index is fed back to step 200, forming an adaptive safety monitoring cycle. The entire solution integrates multi-source data, dynamic strategies, and physical models to achieve both worker safety and equipment efficiency optimization.

[0102] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0103] The formula described above is an example of an empirical formula defined by an expert in the field. Any formula that conforms to the relationship between the parameters of this application is acceptable. The specific size of the weighting factors in the formula shall be reasonably set by a person skilled in the art based on actual use.

[0104] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. An information safety hat communication and safety monitoring system, characterized by, Comprise: Information acquisition module, power monitoring module, work field modeling module, environment analysis module and safety monitoring module; The information acquisition module is connected with the information safety cap through communication, and generates an activation instruction to activate the information safety cap to collect equipment information, environmental information and behavior information; The power monitoring module predicts the power based on the equipment information and compares it with the expected work duration to execute corresponding strategies, including power warning and monitoring period adjustment, generates an activation instruction based on the adjusted monitoring period and updates it to the information acquisition module; The work field modeling module is based on the pre-stored 3D layout of the work scene and the labeled dangerous area, calculates the static danger value by block and constructs the spatial danger field by superposition with different distance attenuation coefficients; The environment analysis module analyzes the environment based on the environmental information to output the environmental risk value of the location where the information safety cap is located; The safety monitoring module performs superposition analysis based on the behavior information and the danger field, and combines the environmental risk value to output the exposure risk index. If the exposure risk index is greater than the upper limit of the exposure interval, a first exposure is generated and an exposure warning is executed; If the exposure risk index is in the exposure interval, a second exposure is generated; if the exposure risk index is less than the lower limit of the exposure interval, a third exposure is generated.

2. The information security hat communication and safety monitoring system of claim 1, wherein, The process of predicting the power based on the equipment information and comparing it with the expected work duration is as follows: Get the nearest off-work time from the current time, and calculate the time difference between the current time and the nearest off-work time to get the expected work duration. There is a minimum use time. If the expected work duration is greater than or equal to the minimum use time, the minimum time is used as the reference time. If the expected work duration is less than the minimum use time, the expected work duration is used as the reference time; If the expected endurance time is less than the reference time, a charging warning is generated; If the expected endurance time is greater than or equal to the reference time, the monitoring period is dynamically adjusted to generate an activation instruction.

3. The information security hat communication and safety monitoring system of claim 2, wherein, Dynamic adjustment of monitoring period: Get the exposure risk value and exposure level generated by the nearest monitoring from the current time. If the exposure level is two, generate a monitoring strategy dominated by safety constraints. If the exposure level is three, generate a monitoring strategy dominated by power constraints.

4. The information security hat communication and safety monitoring system of claim 3, wherein, Monitoring strategy dominated by safety constraints: The exposure risk index A is calculated and analyzed to obtain the latest monitoring period , and the calculation formula is: wherein and respectively are the longest monitoring period and the shortest monitoring period, is a risk sensitivity coefficient, the risk sensitivity coefficient controls the degree of severity of the impact of the risk on the period; the most recent monitoring time from the current time is obtained, and a time interval is calculated by time difference between the current time and the most recent monitoring time, and if the time interval is greater than or equal to the latest monitoring period, an activation instruction is generated.

5. The information security hat communication and safety monitoring system of claim 4, wherein, Monitoring strategy dominated by power constraints: The latest monitoring period is obtained by formulating and analyzing the residual power D The calculation formula is: The time interval is calculated by taking the time difference between the time of the most recent monitoring time and the current time. If the time interval is greater than or equal to the latest monitoring period, an activation instruction is generated.

6. The information security hat communication and safety monitoring system of claim 1, wherein, Construction of spatial danger field: The preset stores a 3D layout diagram of the entire work scene, and a dangerous area is marked in the 3D layout diagram, the entire work scene is divided into a plurality of blocks, m dangerous areas distributed in the blocks are extracted, and m is a positive integer; it is predetermined that each pre-labeled dangerous area corresponds to a fixed static dangerous value and a distance attenuation coefficient, and they are respectively denoted as and wherein i = 1, 2, 3 …… m, i represents the index of any one dangerous area in the block; Any one position in the plate except the dangerous area is recorded as P point, and the total value of the influence of all dangerous areas in the plate on P point is obtained by linear superposition of the dangerous components generated by all m dangerous areas in the plate after attenuation at the point, to obtain the dangerous value H total (P), and the calculation formula is: According to the dangerous value H corresponding to any point P in the plate total (P) constructs a dangerous field in the plate, P is any point in the plate except the dangerous area; wherein It refers to the geometric distance between point P and the center of dangerous area i, which is calculated by using the Euclidean space distance formula: , wherein the three-dimensional coordinates of point P are (x(P), y(P), z(P)), and the three-dimensional coordinates of dangerous area i are (x i , y i , z i ); The dangerous component of the i-th dangerous area to the position of point P.

7. The information security hat communication and safety monitoring system of claim 1, wherein, The process of analyzing the environment based on the environmental information is as follows: Extract the environmental information of the information safety cap in the block. The specific environmental information includes temperature, humidity, respirable particulate matter concentration, oxygen concentration, combustible gas concentration and toxic gas concentration. Analyze the environmental risk based on the environmental information to output the environmental risk value of the location where the information safety cap is located; Step 401, extract the environmental information of the information safety cap in the block. The specific environmental information includes temperature, humidity, respirable particulate matter concentration, oxygen concentration, combustible gas concentration and toxic gas concentration. Set the safety interval according to the safety regulations, which includes the safety temperature interval, the safety humidity interval, the safety particulate matter interval, the safety oxygen interval, the safety combustible interval and the safety toxic interval; Step 402, calculate the independent risk state of each parameter relative to the safety interval, obtain the risk component corresponding to each environmental parameter, specifically, temperature risk component R T , humidity risk component R S , particulate matter risk component R PM , oxygen risk component , combustible gas risk component R com and toxic gas risk component R tox ; Step 403, the temperature risk component R T , the humidity risk component R S , the particulate matter risk component R PM , the oxygen risk component , the combustible gas risk component R com and the toxic gas risk component R tox are linearly weighted and fused to obtain an environmental risk value, so that the environmental risk values of each information security cap in each block can be obtained, and the environmental risk indexes of each block are obtained by averaging calculation, and are marked in the corresponding blocks in the 3D layout diagram.

8. The information security hat communication and safety monitoring system of claim 1, wherein, The output process of the exposure risk index is as follows: 8-1, extract the online time of the information security hat from the online time to the current time, respectively, and count the residence time of the information security hat in each board, and take the board with residence time > 0 as the residence board of the information security hat, and multiply the residence time of the information security hat in the residence board by the corresponding environmental risk value to obtain the residence risk component of the residence board, denoted as Z; 8-2, based on the behavior information and the dangerous field, the residence risk component of the information security hat in each board is calculated by superposition analysis; 8-3, the residence risk component and the residence risk component of the information security hat in each board are linearly weighted and fused to obtain the exposure risk component, and the exposure risk index of the information security hat is calculated by summing the exposure risk component of the information security hat in each board, and updating it to the power monitoring module.

9. The information security hat communication and safety monitoring system of claim 8, wherein, Based on the behavior information and the dangerous field, the residence risk component of the information security hat in each board is calculated by superposition analysis: Extract the behavior information of the information security hat in each plate, and the specific behavior information includes the walking track of the information security hat in each plate and the staying time at each position, denoted as Fj, and the walking track is compared with the dangerous field in the plate to obtain the H total (j), where j is a positive integer, j=1, 2, 3……, j represents the index of any one position on the walking track; according to the formula The staying risk component received by the information security hat when walking in the plate is calculated.

10. An information safety hat communication and safety monitoring method, characterized by The application is applied to the information security hat communication and safety monitoring system in any one of claims 1-9, comprising the following steps: Step 100, by communicating with the information security hat, and by issuing an activation instruction to the information security hat to activate the information security hat to collect device information, environmental information and behavior information; Step 200, based on the device information, the power is predicted and compared with the expected working time to execute the corresponding strategy, including power warning and monitoring period adjustment, based on the adjusted monitoring period to generate the activation instruction, and update it to step 100; Step 300, based on the pre-stored 3D layout map of the work scene and the labeled dangerous area, the static danger value is calculated according to the board, and the spatial danger field is constructed by superposition with different distance attenuation coefficients; Step 400, based on the environmental information, the environmental analysis is carried out to output the environmental risk value of the position where the information security hat is located; Step 500, based on the behavior information and the dangerous field, the exposure risk index is output by superposition analysis and exposure accumulation combined with the environmental risk value, if the exposure risk index is greater than the upper limit of the exposure interval, then generate a first exposure, and execute exposure warning; if the exposure risk index is in the exposure interval, then generate a second exposure; if the exposure risk index is less than the lower limit of the exposure interval, then generate a third exposure.

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