Data acquisition management method and system based on electronic fence

Abstract

The invention discloses a data acquisition management method and system based on an electronic fence, particularly relates to the field of construction safety management, is used for solving the problem of real-time monitoring of constructors, and is characterized in that risk areas are divided through a GIS (Geographic Information System), the electronic fence is arranged, the position information of the constructors is collected in real time, and individual and collective behavior characteristics are extracted; and calculating the difference degree between the individual and the collective behavior mode, and evaluating the consistency and coordination degree of collective behaviors. Constructing an interaction event matrix, analyzing the interaction strength between constructors, calculating an interaction risk index, identifying a high-frequency interaction group through a graph theory algorithm, and evaluating the group risk level. And the hidden risk index is combined with the main component projection score and the interaction-synergy isomerism index, so that a manager can accurately identify high-risk personnel and formulate targeted management and prevention measures according to an electronic fence area, and comprehensive data support and decision basis are provided for safety management of a construction site.

Description

Technical Field

[0001] The present invention relates to the field of construction safety management, and more specifically, to a data collection management method and system based on electronic fences. Background Art

[0002] In large-scale construction sites, ensuring the safety of construction workers is always the top priority of management. The construction environment is complex and changeable, and there are many potential risks, such as high-altitude operations, heavy machinery operations, and confined space work. These risks require managers to grasp the location and activities of construction workers in real time so that they can respond and adjust in time. To this end, more and more construction projects have introduced advanced technical means, such as GIS systems and GPS positioning technology, to improve the safety management level of construction sites through accurate location information collection and real-time monitoring. However, simple location information collection and monitoring are not enough to fully guarantee safety. How to effectively analyze and use this data to further improve safety management has become an urgent problem to be solved.

[0003] In the existing technology, although GPS positioning and GIS systems have been widely used in construction safety management, there are still several shortcomings. First, the existing system mainly focuses on the monitoring of individual location information, lacks the analysis of the collective behavior patterns of construction personnel, and cannot fully evaluate the impact of collective behavior on individual safety. Secondly, the existing risk assessment methods are usually relatively single, and fail to comprehensively consider the differences and interactive risks between individual and collective behavior patterns, resulting in poor accuracy and comprehensiveness of risk assessment. In addition, the lack of effective data fusion technology makes it impossible to fully utilize multi-source data, further limiting the system's safety management capabilities. Therefore, there is an urgent need for an innovative technology that can dynamically adjust the frequency of data collection, comprehensively analyze individual and collective behavior patterns, and perform multi-source data fusion to improve the overall safety management level of the construction site.

[0004] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiment of the present invention provides a data collection management method and system based on electronic fences. The risk area is divided by the GIS system and the electronic fence is set. The GPS module is integrated into the safety equipment of the construction personnel, the data transmission protocol is configured and tested, and the data collection system is started to monitor and record the location information and activity trajectory of the construction personnel in real time, which can significantly improve the safety management level of the construction site. By collecting the location information of the construction personnel, extracting individual and collective behavior characteristics, calculating the difference between individual and collective behavior patterns, and combining the electronic fence area division and risk area influencing factors, an accurate assessment of the hidden risks of construction personnel is achieved. The introduction of the collective synergy index helps to evaluate the normative impact of collective behavior on individual behavior and reflect the consistency and coordination of collective behavior. By constructing an interactive event matrix, the interaction intensity between construction personnel is detected and analyzed, the interactive risk index is calculated, the potential risks brought by frequent interactions are revealed, and high-frequency interaction groups are identified through graph theory algorithms to evaluate the overall risk level within the group. The comprehensive calculation of the hidden risk index, combined with the principal component projection score and the interaction-cooperation heterogeneity index, enables managers to accurately identify high-risk personnel and formulate targeted management and prevention measures based on the division of electronic fence areas, providing comprehensive data support and decision-making basis for the safety management of construction sites to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: S1, set up multiple electronic fence areas with different risk levels through the GIS system, and integrate GPS positioning modules into the safety equipment of construction workers to collect and transmit the location information of construction workers in real time; S2, collect the location information of construction workers, combine it with the electronic fence area division, extract individual and collective behavior characteristics, calculate the difference and interaction between individual and collective behavior patterns, obtain the collective synergy index and interaction risk index accordingly, and combine it with the risk area influencing factor to calculate the hidden risk index of each construction worker, identify potential high-risk personnel and manage them, including presenting the hidden risk level; S3, dynamically adjusts the data collection frequency and transmission mode according to the identified hidden risk level.

[0007] In a preferred embodiment, step S1 includes the following contents: Risk areas are divided and electronic fences are set up through the GIS system. GPS modules are integrated into the safety equipment of construction workers. Data transmission protocols are configured and tested. The data collection system is started to monitor and record the location information and activity trajectories of construction workers in real time.

[0008] In a preferred embodiment, the process of obtaining the collective synergy index is as follows: A1, collects the construction workers’ location information in real time through the GPS module, including timestamp, latitude, longitude and altitude; A2, individual feature extraction: extract individual trajectory features, including trajectory length , average speed , number of stopover points , path change frequency ; Collective feature extraction: Extract collective trajectory features, including collective trajectory density , collective path consistency , collective speed consistency , Distribution of collective stopover points ; Among them, the collective is composed of multiple individuals with the same function; A3, individual behavior pattern calculation: calculate the individual behavior pattern based on individual characteristics and define the individual behavior vector ; Collective behavior pattern calculation: Calculate the collective behavior pattern based on collective characteristics and define the collective behavior vector ; Calculate the difference between individual behavior patterns and collective behavior patterns , the formula is as follows: ; A4, based on the GIS system, mark the electronic fence areas of different risk levels in the construction site and define the risk area influencing factors ,in, Indicates the regional risk level, set as: low risk 1, medium risk 2, high risk 3; A5, combining the difference and regional risk influencing factors, calculate the comprehensive risk index of each construction worker , the formula is as follows: ; in, The number of areas for construction personnel activities; For the Risk factors affecting each region; For construction workers Duration of stay in an area; A6, calculate the collective synergy coefficient , reflecting the impact of collective behavior on individual risk, the formula is as follows: ; in, is the number of construction workers in the collective; For the The difference in behavior patterns of individual construction workers.

[0009] In a preferred embodiment, the process of obtaining the interaction risk index is as follows: B1, collect the location information of construction workers, including timestamp, longitude, latitude and altitude; B2, when the distance between two construction workers is less than the distance threshold and lasts longer than ,It is believed that an interaction event has occurred, and the trajectory data of each pair of construction workers are compared to detect the interaction event; B3, constructing the interaction matrix ,in Indicates The construction workers and The interaction intensity between construction workers is calculated based on the number and duration of interaction events; ; in, is the number of time steps; For the Time step The construction workers and The distance between construction workers; is the duration of the interaction; is the indicator function; B4, calculate the interaction risk between each construction worker and all other construction workers. The interaction risk is calculated using the following formula: ; in, is the number of construction workers, is the risk function of interaction intensity, defined as: ; B5, further analyze the interaction pattern, identify high-risk interaction groups, identify high-frequency interaction groups through graph theory algorithms, and assess the overall risk; Building an interaction diagram , where the node Indicates construction workers, represents the interaction relationship, and the edge weight is the interaction strength; Use community detection algorithm to detect interaction groups and calculate the interaction risk index of each group : ,in, is the set of interaction edges within the group; B6, comprehensively consider the interaction risks of individuals and groups, and calculate the interaction risk index of each construction worker : ; in, For construction workers The group of people in which you are located, The number of groups.

[0010] In a preferred embodiment, C1, collects the interaction risk index and collective coordination index of each construction worker; C2, calculate the mean and standard deviation of the interaction risk index and collective coordination index of each construction worker, which are recorded as , and , ; The interaction risk index and collective coordination index of each construction worker were normalized into standard scores; C3, building an interaction-synergy matrix , each element of the matrix Element indicates the The construction workers and The relationship between individual construction workers in terms of interactive risks and collective coordination; ; C4, perform principal component analysis on the interaction-synergy matrix, extract the main components, and reduce the dimension. Let the eigenvector of the first principal component be ; Calculate the projection score of each construction worker on the first principal component: ; in, is the total number of construction workers, is the component of the eigenvector corresponding to the first principal component; C5, calculate the interaction-cooperation heterogeneity index of each construction worker , reflecting the degree of heterogeneity in interaction and collaboration, the formula is as follows: ; in, and is the mean of the standard scores of all construction workers; C6, the first principal component projection score of each construction worker is combined with the interaction-cooperation heterogeneity index to calculate the hidden risk index , the formula is as follows: .

[0011] In a preferred embodiment, the hidden risk index of each construction worker is calculated and compared with a pre-set risk threshold 1 and a pre-set hidden risk threshold 2 to divide the hidden risk levels into different levels. The specific process is as follows: Firstly, the hidden risk index of each construction worker is obtained based on the comprehensive analysis of the interactive risk index and the collective coordination index; comparing the hidden risk index with risk threshold one and hidden risk threshold two; If the hidden risk index is lower than the risk threshold of one, it means that the construction workers’ behavior pattern is highly consistent with the collective and they have less interaction with other people, which is a low risk level; If the hidden risk index is between risk threshold 1 and hidden risk threshold 2, it means that the construction workers have certain differences in their behavior patterns or have moderate interactions with others, which is a medium risk level; If the hidden risk index is higher than the hidden risk threshold of two, it is classified as high risk. The construction workers' behavior patterns are significantly different from the group and they interact frequently with others, which is a high-risk level.

[0012] In a preferred embodiment, step S3 includes the following contents: For construction workers marked as medium risk level, the upper and lower limits of data collection frequency are set as follows: and ; According to the behavior patterns of people at medium risk levels and the division of electronic fence areas, the collection frequency is dynamically adjusted. The formula is as follows: ; in, is the basic acquisition frequency; is the adjusted acquisition frequency; is the hidden risk index; and are the upper and lower limits of the risk threshold; The basic collection frequency is replaced with the adjusted collection frequency to implement the adjusted collection frequency.

[0013] A data collection and management system based on electronic fence, comprising: an area management module, a positioning equipment module, a data collection module, a behavior analysis module, a risk assessment module and a dynamic adjustment module; The regional management module sets multiple electronic fence areas with different risk levels through the GIS system, and sends the divided risk area data to the data collection module and behavior analysis module; The positioning equipment module integrates the GPS positioning module into the safety equipment of the construction personnel, collects and transmits the location information in real time, and transmits the collected location information to the data acquisition module in real time; The data acquisition module collects the location information of construction workers, performs preliminary processing and storage, and transmits the processed data to the behavior analysis module; The behavior analysis module combines the electronic fence area division, extracts individual and collective behavior characteristics, calculates the difference and interaction between individual and collective behavior patterns, and obtains the collective synergy index and interaction risk index accordingly, and sends the collective synergy index and interaction risk index to the risk assessment module; The risk assessment module combines the risk area influencing factors to calculate the hidden risk index of each construction worker, identify potential high-risk personnel and manage them, including presenting the hidden risk level, and sending the assessment results to the dynamic adjustment module; The dynamic adjustment module dynamically adjusts the data collection frequency and transmission mode according to the identified hidden risk level.

[0014] The technical effects and advantages of the data collection management method and system based on electronic fence of the present invention are as follows: 1. The present invention divides risk areas and sets up electronic fences through the GIS system, integrates the GPS module into the safety equipment of construction workers, configures and tests the data transmission protocol, and starts the data acquisition system to monitor and record the location information and activity trajectory of construction workers in real time. It can significantly improve the safety management level of the construction site, effectively monitor the activities of construction workers in different risk areas, timely discover and prevent potential safety hazards, ensure the stability and real-time nature of data transmission, provide accurate and real-time location information support for management personnel, and improve overall construction efficiency and safety.

[0015] 2. The present invention collects the location information of construction workers, extracts individual and collective behavior characteristics, calculates the difference between individual and collective behavior patterns, and combines the electronic fence area division and risk area influencing factors to achieve an accurate assessment of the hidden risks of construction workers. The calculation of the difference between individual behavior patterns and collective behavior patterns provides an in-depth understanding of the degree to which construction workers' behavior deviates from collective standards. The introduction of the collective synergy index helps to evaluate the normative impact of collective behavior on individual behavior, reflecting the consistency and coordination of collective behavior. By constructing an interactive event matrix, detecting and analyzing the interaction intensity between construction workers, and calculating the interactive risk index, the potential risks brought by frequent interactions can be revealed, and high-frequency interaction groups can be identified through graph theory algorithms to evaluate the overall risk level within the group. The comprehensive calculation of the hidden risk index combines the main component projection score with the interactive-synergy heterogeneity index, so that managers can accurately identify high-risk personnel and formulate targeted management and preventive measures based on the division of the electronic fence area. This method not only improves the accuracy of risk assessment, but also provides comprehensive data support and decision-making basis for safety management of construction sites. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of a flow chart of a data collection and management method based on an electronic fence according to the present invention; Figure 2 The present invention is a structural schematic diagram of a data collection and management system based on an electronic fence. DETAILED DESCRIPTION

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

[0018] Figure 1 The present invention provides a data collection and management method based on an electronic fence, comprising: S1, set up multiple electronic fence areas with different risk levels through the GIS system, and integrate GPS positioning modules into the safety equipment of construction workers to collect and transmit the location information of construction workers in real time; S2, collect the location information of construction workers, combine it with the electronic fence area division, extract individual and collective behavior characteristics, calculate the difference and interaction between individual and collective behavior patterns, obtain the collective synergy index and interaction risk index accordingly, and combine it with the risk area influencing factor to calculate the hidden risk index of each construction worker, identify potential high-risk personnel and manage them, including presenting the hidden risk level; S3, dynamically adjusts the data collection frequency and transmission mode according to the identified hidden risk level.

[0019] In large construction sites, ensuring the safety of construction workers is the top priority of management. In order to achieve accurate personnel positioning and risk area monitoring, electronic fence technology based on the GIS system was introduced to the construction site. Through the GIS system, the construction site is divided into multiple areas with different risk levels, such as low-risk areas, medium-risk areas and high-risk areas, each with clear boundaries. In order to monitor the activities of personnel in real time, high-precision GPS positioning modules are integrated into the safety equipment of construction workers (such as helmets, badges, and belts). These modules can collect and transmit the location information of construction workers in real time, including timestamps, longitude and latitude, and altitude, ensuring that managers can instantly grasp the specific location and movement of each construction worker. The application of this technology not only helps to improve the level of safety management on site, but also can quickly locate and rescue trapped people in an emergency, greatly improving the overall safety assurance capabilities of the construction site.

[0020] Step S1 includes the following contents: Risk area division: Divide the areas into different risk levels according to the actual conditions of the construction site and the risk assessment report. Use GIS (Geographic Information System) software to mark and assign different risk levels on the map of the construction site, such as low-risk areas, medium-risk areas, and high-risk areas. Generate an electronic map with risk levels marked, defining the boundaries and attributes of each area.

[0021] Electronic fence setting: Set up electronic fences in the GIS system to ensure that each risk area has clear boundaries. Use polygon tools in the GIS software to draw each electronic fence and define its spatial range and risk level attributes. Complete the risk area map with electronic fences.

[0022] Integrate the GPS module into the construction workers' safety equipment (such as helmets, badges, belts), ensuring that the GPS module can be stably installed and will not affect the construction workers' operations.

[0023] Data transmission protocol configuration: Configure the data transmission protocol to ensure that the data from the GPS module can be stably and timely transmitted to the data acquisition system. According to the technical specifications of the GPS module and the receiving system, set the data transmission protocol (such as LoRa, NB-IoT, Wi-Fi, Bluetooth, etc.) to ensure the stability and reliability of data transmission. The configured transmission protocol ensures smooth data transmission.

[0024] Real-time data transmission test: Test the real-time transmission effect of GPS data to ensure the normal operation of the system. Perform multiple tests in a simulated environment to check the real-time, accuracy and completeness of data transmission, and find and solve potential problems. Test reports confirm that the system can operate stably and meet the requirements of real-time data transmission.

[0025] System launch and real-time monitoring: Start the data collection system for real-time monitoring. The data collection system is officially launched to monitor the location information of construction personnel in real time and record their activities in different risk areas. Real-time monitoring data records the location information and activity trajectories of construction personnel.

[0026] The present invention divides risk areas and sets up electronic fences through the GIS system, integrates GPS modules into the safety equipment of construction workers, configures and tests data transmission protocols, and starts the data acquisition system to monitor and record the location information and activity trajectories of construction workers in real time. It can significantly improve the safety management level of the construction site, effectively monitor the activities of construction workers in different risk areas, promptly discover and prevent potential safety hazards, ensure the stability and real-time nature of data transmission, provide accurate and real-time location information support for management personnel, and improve overall construction efficiency and safety.

[0027] S2 includes the following: Safety management is one of the most important tasks at the construction site, especially in large projects, where the behavior patterns of construction workers and their activities in different areas directly affect the overall safety level. For this reason, the calculation of the collective coordination index becomes particularly important, aiming to evaluate the impact of the collective behavior of construction workers on individual risks at the construction site. By collecting the location information of construction workers in real time, extracting individual and collective behavior characteristics, and analyzing the differences between individual and collective behavior patterns, potential safety hazards can be identified more accurately. The collective coordination index comprehensively considers the difference between individual and collective behavior patterns, spatial behavior consistency, temporal behavior consistency, and individual behavior discreteness. Through detailed analysis of these data, it can reflect the consistency and coordination of collective behavior, thereby providing managers with a reliable basis for risk assessment and guiding the formulation of effective safety management strategies.

[0028] The process of obtaining the collective synergy index is as follows: A1, collects the location information of construction workers in real time through the GPS module, including timestamp, latitude, longitude and altitude.

[0029] Remove noise and outliers, handle missing data, and ensure data accuracy and consistency.

[0030] Convert the cleaned data into a structured data format for easy subsequent processing.

[0031] A2, individual feature extraction: extract individual trajectory features, including trajectory length , average speed , number of stopover points , path change frequency .

[0032] Collective feature extraction: Extract collective trajectory features, including collective trajectory density , collective path consistency , collective speed consistency , Distribution of collective stopover points .

[0033] It should be noted that a collective is composed of multiple individuals with the same functions.

[0034] A3, individual behavior pattern calculation: calculate the individual behavior pattern based on individual characteristics and define the individual behavior vector ; Collective behavior pattern calculation: Calculate the collective behavior pattern based on collective characteristics and define the collective behavior vector ; Calculate the difference between individual behavior patterns and collective behavior patterns , the formula is as follows: ; A4, based on the GIS system, marking the electronic fence areas of different risk levels in the construction site (low risk, medium risk, high risk); Defining risk area impact factors (in represents the regional risk level), set to: low risk (1), medium risk (2), high risk (3).

[0035] A5, combining the difference and regional risk influencing factors, calculate the comprehensive risk index of each construction worker , the formula is as follows: ; in, The number of areas for construction personnel activities; For the Risk factors affecting each region; For construction workers Duration of stay in an area.

[0036] A6, calculate the collective synergy coefficient , reflecting the impact of collective behavior on individual risk, the formula is as follows: ,in, is the number of construction workers in the collective; For the The difference in behavior patterns of individual construction workers.

[0037] The collective coordination index is used to measure the impact of the collective behavior of construction workers on individual risks at the construction site, reflecting the consistency and coordination of collective behavior. Specifically, the collective coordination index comprehensively considers the difference between individual behavior patterns and collective behavior patterns, spatial behavior consistency, temporal behavior consistency, and individual behavior dispersion. When the collective coordination index is large, it means that the coordination between collective behavior patterns is high, the difference between individual behavior and collective behavior is small, the behavior of construction workers in the group is more consistent, and the risk is lower; conversely, when the collective coordination index is small, it means that there are large differences in the behavior patterns of construction workers in the group, the consistency of collective behavior is poor, and the dispersion of individual behavior is high, which means higher potential risks. Through this index, the overall safety status of the construction site can be more accurately evaluated, providing managers with effective risk warning and management basis.

[0038] In complex construction sites, the interactions between construction workers not only affect work efficiency, but also pose a potential threat to overall safety. The calculation of the interaction risk index becomes the key to assessing the impact of these interactions on overall safety risks. By collecting the location information of each construction worker in real time, detecting and analyzing the interaction events between them, we can understand the frequency and intensity of interactions, and how these interactions affect individual and collective safety. The interaction risk index takes into account the nonlinear risk growth of interactive behaviors, reflecting the higher probability of accidents and risk propagation that may be caused by frequent interactions. This index helps to identify high-risk interaction groups and assess the overall risk within the group, thereby providing managers with accurate risk warnings, formulating more targeted safety management measures, and ensuring safe operation of construction sites.

[0039] The process of obtaining the interactive risk index is as follows: B1, collect the location information of construction workers, including timestamp, longitude, latitude and altitude.

[0040] Remove noise and outliers, handle missing data, and ensure data accuracy and consistency.

[0041] Convert the cleaned data into a structured data format for easy subsequent processing.

[0042] B2, when the distance between two construction workers is less than the distance threshold and lasts longer than , it is considered that an interaction event has occurred. The trajectory data of each pair of construction workers are compared to detect interaction events.

[0043] B3, constructing the interaction matrix ,in Indicates The construction workers and The interaction intensity between construction workers is calculated based on the number and duration of interaction events.

[0044] ; in, is the number of time steps; For the Time step The construction workers and The distance between construction workers; is the duration of the interaction; is the indicator function.

[0045] B4, calculate the interaction risk between each construction worker and all other construction workers. The interaction risk is calculated using the following formula: ; in, is the number of construction workers, is the risk function of interaction intensity, defined as: ; The risk function of interaction intensity takes into account the nonlinear growth of interaction intensity, reflecting the higher risks that may be caused by frequent interactions.

[0046] B5, further analyze the interaction patterns and identify high-risk interaction groups. Use graph theory algorithms (such as community detection algorithms) to identify high-frequency interaction groups and assess the overall risk.

[0047] Building an interaction diagram , where the node Indicates construction workers, represents the interaction relationship, and the edge weight is the interaction strength.

[0048] Use community detection algorithms (such as Louvain algorithm) to detect interaction groups and calculate the interaction risk index of each group. : ,in, is the set of interaction edges within the group.

[0049] B6, comprehensively consider the interaction risks of individuals and groups, and calculate the interaction risk index of each construction worker : ; in, For construction workers The group of people in which you are located, The number of groups.

[0050] The interactive risk index (IRI) is used to evaluate the impact of interactive behaviors between construction workers on the overall safety risk, reflecting the importance of the interaction pattern between individuals and groups for safety management. The calculation method first collects the location information of construction workers, removes noise and outliers, and formats the data for processing. Then, the interactive event is defined as when the distance between two construction workers is less than a certain threshold and the duration exceeds a specified time. These interactive events are detected and an interaction matrix is ​​constructed, in which each element represents the interaction intensity between each construction worker and other construction workers, which is calculated by the number and duration of the corresponding event. The risk function of the interaction intensity adopts a nonlinear form, reflecting the higher risk brought by frequent interactions. Subsequently, the interaction risk of each construction worker with all other construction workers is calculated, and the high-frequency interaction groups are identified through graph theory algorithms (such as community detection algorithms), and the interaction graph is constructed and the interaction risk index of the group is calculated. Finally, the interaction risk of each construction worker is calculated as the group set to which the construction worker belongs, combining the interaction risk of individuals and groups. A larger interaction risk index value indicates a higher interaction frequency and the possibility of risk transmission, while a smaller interaction risk index value indicates fewer interactions and lower risks. This index can be used to comprehensively assess the safety status of the construction site and improve the management level.

[0051] The interaction risk index is used to indicate the impact of interaction between construction workers on the overall safety risk, reflecting the importance of interaction patterns between individuals and groups to safety management. A larger interaction risk index value indicates that the interaction between construction workers and other personnel is frequent and intense, implying a higher safety risk, because frequent interactions may lead to a higher probability of accidents and risk transmission; a smaller interaction risk index value indicates that there is less interaction between construction workers and other personnel, which generally means a lower safety risk, because individual behavior is more independent and less affected by the behavior of others.

[0052] At the construction site, safety management involves complex behavior analysis and interaction evaluation. In order to accurately identify potential high-risk personnel, the complex relationship between individual behavior and collective behavior must be considered comprehensively. The interactive risk index (IRI) aims to evaluate the impact of interactive behaviors between construction workers on the overall safety risk. By analyzing the frequency and intensity of interaction, it reveals the potential accident risks that may be caused by frequent interactions. On the other hand, the collective coordination index (CCI) is used to measure the consistency and coordination of construction workers in the collective behavior pattern, reflecting the difference between individual behavior patterns and collective behavior patterns and their impact on individual risks. Combining these two indicators to calculate the hidden risk index (CRI) can not only capture the degree of abnormality of individual behavior, but also deeply analyze the interactive effect between individual and collective behavior. Through this comprehensive evaluation method, high-risk personnel with abnormal behavior patterns and inconsistent with collective behavior can be accurately identified. These personnel may increase potential safety hazards due to their deviation from collective standards or frequent and complex interactions with others. The calculation of the hidden risk index requires combining the projection score of individual behavior on the main components with its interactive-cooperative heterogeneity index to form a multi-dimensional and multi-level risk assessment system. The establishment and application of this system will not only help to discover and prevent potential safety hazards in advance, but also provide managers with comprehensive risk assessment data, so as to formulate more targeted safety management strategies and ultimately improve the overall safety management level of the construction site.

[0053] C1, collect the interaction risk index and collective coordination index of each construction worker; C2, calculate the mean and standard deviation of the interaction risk index and collective coordination index of each construction worker, which are recorded as , and , .

[0054] The interaction risk index and collective synergy index of each construction worker were standardized into a standard score (Z score).

[0055] The standard score reflects the degree of abnormality of an individual relative to the group, with larger positive values ​​indicating above the mean and larger negative values ​​indicating below the mean.

[0056] C3, building an interaction-synergy matrix , each element of the matrix Element indicates the The construction workers and The relationship between individual construction workers in terms of interactive risks and collective collaboration. ; C4, perform principal component analysis on the interaction-synergy matrix, extract the main components, and reduce the dimension. Suppose the eigenvector of the first principal component is .

[0057] Calculate the projection score of each construction worker on the first principal component: ; in, is the total number of construction workers, is the component of the eigenvector corresponding to the first principal component.

[0058] C5, calculate the interaction-cooperation heterogeneity index of each construction worker , reflecting the degree of heterogeneity in interaction and collaboration, the formula is as follows: ; in, and is the mean standard score of all construction workers.

[0059] C6, the first principal component projection score of each construction worker is combined with the interaction-cooperation heterogeneity index to calculate the hidden risk index, the formula is as follows: ; The hidden risk index is used to represent and evaluate the potential safety risks of each construction worker on the construction site, which specifically reflects the hidden impact of the interaction between individual behavior patterns and collective behavior patterns on overall safety. The index combines the first principal component projection score of each construction worker with its interaction-cooperation heterogeneity index to comprehensively reflect the degree of abnormality of the individual in the group and the complexity of its interaction with other personnel. A larger hidden risk index value indicates that the construction worker's behavior is significantly different from the collective behavior, and the interaction with other personnel is frequent and complex, which implies a higher potential safety risk, because such behavior may lead to unforeseen safety hazards and accidents; a smaller hidden risk index value indicates that the construction worker's behavior is highly consistent with the collective behavior, and the interaction with other personnel is less or simpler, which usually means a lower safety risk, because the behavior pattern is more standardized and less subject to external interference. By evaluating the hidden risk index, managers can more accurately identify potential high-risk personnel and take preventive measures in advance, thereby effectively improving the overall safety level of the construction site.

[0060] By calculating the hidden risk index (CRI) of each construction worker and comparing it with the pre-set risk threshold 1 and hidden risk threshold 2, different hidden risk levels are divided. The specific process is as follows: first, the hidden risk index of each construction worker is obtained based on the comprehensive analysis of the interactive risk index and the collective synergy index; Compare the hidden risk index with risk threshold one (e.g., 1.0) and hidden risk threshold two (e.g., 2.5); If the hidden risk index is lower than the risk threshold of one, it means that the construction worker's behavior pattern is highly consistent with the group and has less interaction with other personnel, which is a low risk level. In this case, regular monitoring is maintained and no additional measures are required, but regular inspections are performed to ensure that their behavior pattern remains stable; If the hidden risk index is between risk threshold 1 and hidden risk threshold 2, it means that there are certain differences in the behavior patterns of construction workers, or they have moderate interactions with others, which is a medium risk level. Strengthen inspections and supervision, regularly review their behavior patterns and interactions, pay attention to the frequency of their activities in different areas, and ensure that their behavior is within a controllable range; If the hidden risk index is higher than the hidden risk threshold of two, it is classified as high risk. The construction workers' behavior patterns are significantly different from the group and they interact frequently with others, which belongs to the high-risk level. Key monitoring measures are taken, such as restricting their entry into high-risk areas, increasing the frequency of real-time monitoring, arranging special personnel to be responsible for safety supervision, providing training and guidance when necessary to improve their behavior patterns, and regularly evaluating their risk index to ensure timely adjustment of management strategies.

[0061] Generate a risk report for each construction worker and take corresponding management measures, maintain regular monitoring of low-risk personnel, strengthen inspections and supervision of medium-risk personnel, and take key monitoring measures for high-risk personnel, such as restricting entry into high-risk areas and increasing the frequency of real-time monitoring. Through this method, potential high-risk personnel can be effectively identified and managed to ensure safe operation of the construction site.

[0062] The present invention collects the location information of construction workers, extracts individual and collective behavior characteristics, calculates the difference between individual and collective behavior patterns, and combines the electronic fence area division and risk area influencing factors to achieve an accurate assessment of the hidden risks of construction workers. The calculation of the difference between individual behavior patterns and collective behavior patterns provides an in-depth understanding of the degree to which the construction workers' behavior deviates from the collective standard. The introduction of the collective synergy index helps to evaluate the normative impact of collective behavior on individual behavior, reflecting the consistency and coordination of collective behavior. By constructing an interactive event matrix, detecting and analyzing the interaction intensity between construction workers, and calculating the interactive risk index, the potential risks brought by frequent interactions can be revealed, and high-frequency interaction groups can be identified through graph theory algorithms to evaluate the overall risk level within the group. The comprehensive calculation of the hidden risk index combines the main component projection score with the interactive-synergy heterogeneity index, so that managers can accurately identify high-risk personnel and formulate targeted management and preventive measures based on the division of the electronic fence area. This method not only improves the accuracy of risk assessment, but also provides comprehensive data support and decision-making basis for safety management of construction sites.

[0063] In complex and dynamic construction sites, timely and accurate monitoring of construction workers' behavior is the key to ensuring safety, especially for construction workers with medium risk levels, whose behavior changes and location movements may bring potential safety hazards. To achieve this goal, it is necessary to dynamically adjust the data collection frequency and transmission mode, and use flexible monitoring strategies to adapt to the real-time changing risk level. Traditional fixed-frequency data collection and single transmission mode cannot meet this demand. By dynamically adjusting the data collection frequency and transmission mode according to the hidden risk index, it is possible to more effectively capture the behavioral changes of medium-risk personnel and ensure timely and accurate data at critical moments. Combining a real-time monitoring system with an automated transmission mode switching mechanism not only improves the efficiency of data collection and transmission, but also continuously optimizes and adjusts strategies through a data feedback mechanism, making safety monitoring on construction sites more accurate and efficient. This innovative approach will provide stronger technical support for construction safety management, ensuring that preventive measures are taken in a timely manner before potential risks occur.

[0064] Step S3 includes the following contents: For construction workers marked as medium risk level, the upper and lower limits of data collection frequency are set as follows: and (For example, low frequency is once every 10 minutes, high frequency is once every 1 minute).

[0065] The collection frequency is adjusted dynamically based on the behavior patterns of people at medium risk levels and the division of electronic fence areas. The formula is as follows: ; in, is the basic acquisition frequency; is the adjusted acquisition frequency; is the hidden risk index; and The upper and lower limits of the risk threshold.

[0066] Replace the basic collection frequency with the adjusted collection frequency, implement the adjusted collection frequency, and monitor the data quality and effectiveness of the collection frequency in real time to ensure the accuracy and timeliness of the data.

[0067] Figure 2 The present invention provides a data collection and management system based on electronic fence, including: an area management module, a positioning equipment module, a data collection module, a behavior analysis module, a risk assessment module and a dynamic adjustment module; The regional management module sets multiple electronic fence areas with different risk levels through the GIS system, and sends the divided risk area data to the data collection module and behavior analysis module; The positioning equipment module integrates the GPS positioning module into the safety equipment of the construction personnel, collects and transmits the location information in real time, and transmits the collected location information to the data acquisition module in real time; The data acquisition module collects the location information of construction workers, performs preliminary processing and storage, and transmits the processed data to the behavior analysis module; The behavior analysis module combines the electronic fence area division, extracts individual and collective behavior characteristics, calculates the difference and interaction between individual and collective behavior patterns, and obtains the collective synergy index and interaction risk index accordingly, and sends the collective synergy index and interaction risk index to the risk assessment module; The risk assessment module combines the risk area influencing factors to calculate the hidden risk index of each construction worker, identify potential high-risk personnel and manage them, including presenting the hidden risk level, and sending the assessment results to the dynamic adjustment module; The dynamic adjustment module dynamically adjusts the data collection frequency and transmission mode according to the identified hidden risk level.

[0068] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0069] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0070] It should be noted that, in this article, if there are relational terms such as first and second, etc., they are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including a..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0071] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A data collection and management method based on electronic fence, characterized in that: S1, set up multiple electronic fence areas with different risk levels through the GIS system, and integrate GPS positioning modules into the safety equipment of construction workers to collect and transmit the location information of construction workers in real time; S2, collect the location information of construction workers, combine it with the electronic fence area division, extract individual and collective behavior characteristics, calculate the difference and interaction between individual and collective behavior patterns, obtain the collective synergy index and interaction risk index accordingly, and combine it with the risk area influencing factor to calculate the hidden risk index of each construction worker, identify potential high-risk personnel and manage them, including presenting the hidden risk level; S3, dynamically adjusts the data collection frequency and transmission mode according to the identified hidden risk level.

2. The data collection and management method based on electronic fence according to claim 1 is characterized by: Step S1 includes the following contents: Risk areas are divided and electronic fences are set up through the GIS system. GPS modules are integrated into the safety equipment of construction workers. Data transmission protocols are configured and tested. The data collection system is started to monitor and record the location information and activity trajectories of construction workers in real time.

3. The data collection and management method based on electronic fence according to claim 2 is characterized by: The process of obtaining the collective synergy index is as follows: A1, collects the location information of construction workers in real time through the GPS module, including timestamp, latitude, longitude and altitude; A2, individual feature extraction: extract individual trajectory features, including trajectory length , average speed , number of stopover points , path change frequency ; Collective feature extraction: Extract collective trajectory features, including collective trajectory density , collective path consistency , collective speed consistency , Distribution of collective stopover points ; Among them, the collective is composed of multiple individuals with the same function; A3, individual behavior pattern calculation: calculate the individual behavior pattern based on individual characteristics and define the individual behavior vector ; Collective behavior pattern calculation: Calculate the collective behavior pattern based on collective characteristics and define the collective behavior vector ; Calculate the difference between individual behavior patterns and collective behavior patterns , the formula is as follows: ; A4, based on the GIS system, mark the electronic fence areas of different risk levels in the construction site and define the risk area influencing factors ,in, Indicates the regional risk level, set as: low risk 1, medium risk 2, high risk 3; A5, combining the difference and regional risk influencing factors, calculate the comprehensive risk index of each construction worker , the formula is as follows: ; in, The number of areas for construction personnel activities; For the Risk factors affecting the region; For construction workers Duration of stay in an area; A6, calculate the collective synergy coefficient , reflecting the impact of collective behavior on individual risk, the formula is as follows: ; in, is the number of construction workers in the collective; For the The difference in behavior patterns of individual construction workers.

4. The data collection and management method based on electronic fence according to claim 3 is characterized by: The process of obtaining the interactive risk index is as follows: B1, collect the location information of construction workers, including timestamp, longitude, latitude and altitude; B2, when the distance between two construction workers is less than the distance threshold and lasts longer than ,It is believed that an interaction event has occurred, and the trajectory data of each pair of construction workers are compared to detect the interaction event; B3, constructing the interaction matrix ,in Indicates The construction workers and The interaction intensity between construction workers is calculated based on the number and duration of interaction events; ； in, is the number of time steps; For the Time step The construction workers and The distance between construction workers; is the duration of the interaction; is the indicator function; B4, calculate the interaction risk between each construction worker and all other construction workers. The interaction risk is calculated using the following formula: ; in, is the number of construction workers, is the risk function of interaction intensity, defined as: ; B5, further analyze the interaction pattern, identify high-risk interaction groups, identify high-frequency interaction groups through graph theory algorithms, and assess the overall risk; Building an interaction diagram , where the node Indicates construction workers, represents the interaction relationship, and the edge weight is the interaction strength; Use community detection algorithm to detect interaction groups and calculate the interaction risk index of each group : ,in, is the set of interaction edges within the group; B6, comprehensively consider the interaction risks of individuals and groups, and calculate the interaction risk index of each construction worker : ; in, For construction workers The group of people in which you are located, The number of groups.

5. The data collection and management method based on electronic fence according to claim 4 is characterized in that: C1, collect the interaction risk index and collective coordination index of each construction worker; C2, calculate the mean and standard deviation of the interaction risk index and collective coordination index of each construction worker, which are recorded as , and , ; The interaction risk index and collective coordination index of each construction worker were normalized into standard scores; C3, building an interaction-synergy matrix , each element of the matrix Element indicates the The construction workers and The relationship between individual construction workers in terms of interactive risks and collective coordination; ; C4, perform principal component analysis on the interaction-synergy matrix, extract the main components, and reduce the dimension. Let the eigenvector of the first principal component be ; Calculate the projection score of each construction worker on the first principal component: ; in, is the total number of construction workers, is the component of the eigenvector corresponding to the first principal component; C5, calculate the interaction-cooperation heterogeneity index of each construction worker , reflecting the degree of heterogeneity in interaction and collaboration, the formula is as follows: ; in, and is the mean of the standard scores of all construction workers; C6, the first principal component projection score of each construction worker is combined with the interaction-cooperation heterogeneity index to calculate the hidden risk index , the formula is as follows: .

6. The data collection and management method based on electronic fence according to claim 5 is characterized by: By calculating the hidden risk index of each construction worker and comparing it with the pre-set risk threshold 1 and hidden risk threshold 2, different hidden risk levels are divided. The specific process is as follows: Firstly, the hidden risk index of each construction worker is obtained based on the comprehensive analysis of the interactive risk index and the collective coordination index; comparing the hidden risk index with risk threshold one and hidden risk threshold two; If the hidden risk index is lower than the risk threshold of one, it means that the construction workers’ behavior pattern is highly consistent with the collective and they have less interaction with other people, which is a low risk level; If the hidden risk index is between risk threshold 1 and hidden risk threshold 2, it means that the construction workers have certain differences in their behavior patterns or have moderate interactions with others, which is a medium risk level; If the hidden risk index is higher than the hidden risk threshold of two, it is classified as high risk. The construction workers' behavior patterns are significantly different from the group and they interact frequently with others, which is a high-risk level.

7. The data collection and management method based on electronic fence according to claim 6 is characterized by: Step S3 includes the following contents: For construction workers marked as medium risk level, the upper and lower limits of data collection frequency are set as follows: and ; According to the behavior patterns of people at medium risk levels and the division of electronic fence areas, the collection frequency is dynamically adjusted. The formula is as follows: ; in, is the basic acquisition frequency; is the adjusted acquisition frequency; is the hidden risk index; and are the upper and lower limits of the risk threshold; The basic collection frequency is replaced with the adjusted collection frequency to implement the adjusted collection frequency.

8. A data collection and management system based on an electronic fence, used to implement a data collection and management method based on an electronic fence as described in any one of claims 1 to 7, characterized in that: include: Area management module, positioning equipment module, data acquisition module, behavior analysis module, risk assessment module and dynamic adjustment module; The regional management module sets multiple electronic fence areas with different risk levels through the GIS system, and sends the divided risk area data to the data collection module and behavior analysis module; The positioning equipment module integrates the GPS positioning module into the safety equipment of the construction personnel, collects and transmits the location information in real time, and transmits the collected location information to the data acquisition module in real time; The data acquisition module collects the location information of construction workers, performs preliminary processing and storage, and transmits the processed data to the behavior analysis module; The behavior analysis module combines the electronic fence area division, extracts individual and collective behavior characteristics, calculates the difference and interaction between individual and collective behavior patterns, and obtains the collective synergy index and interaction risk index accordingly, and sends the collective synergy index and interaction risk index to the risk assessment module; The risk assessment module combines the risk area influencing factors to calculate the hidden risk index of each construction worker, identify potential high-risk personnel and manage them, including presenting the hidden risk level, and sending the assessment results to the dynamic adjustment module; The dynamic adjustment module dynamically adjusts the data collection frequency and transmission mode according to the identified hidden risk level.

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