A method and system for hierarchical control of construction project safety risks

Abstract

The present invention relates to the technical field of construction engineering safety management, specifically a method and system for hierarchical management and control of construction engineering safety risks, comprising the following steps: based on construction logs, by analyzing the construction logs, identifying multiple violations and evaluating the severity, matching risk scores for multiple violations, and generating a standardized risk indicator table. In the present invention, by identifying multiple violations and matching risk scores, a more accurate risk forecast is provided, combining project data with employee role information, automatically identifying responsible persons and managers and notifying risks, optimizing risk communication processes, ensuring instant information transmission and rapid problem resolution, combining with an evaluation of the effectiveness of safety measures, optimizing response measures and improving the efficiency and effectiveness of safety management, and providing an intuitive understanding of risk diffusion trends by analyzing geographic data of risk events and drawing risk distribution maps, helping managers to prevent risks and allocate resources.

Description

Technical Field

[0001] The present invention relates to the technical field of construction engineering safety management, and in particular to a method and system for hierarchical management and control of construction engineering safety risks. Background Art

[0002] The field of construction project safety management technology focuses on preventing, identifying and controlling risks and hazards in construction projects. It covers safety control measures from the project planning stage to construction and maintenance stages, including risk assessment, safety design, accident prevention strategies, emergency response plans, and safety regulations. It aims to protect the health and safety of workers, avoid property losses, and ensure project quality and environmental protection through effective risk management. It combines site management technology, system engineering and relevant laws and regulations to improve the safety and sustainability of construction projects.

[0003] Among them, the method of graded control of construction project safety risks aims to manage safety risks in construction projects in a graded manner. By classifying the various risks that arise in construction projects, corresponding preventive measures and emergency response strategies are implemented to reduce the accident rate and reduce the damage or losses caused. Combined with the implementation of risk assessment, the formulation of risk response strategies and continuous monitoring, it helps construction companies or project managers to scientifically arrange safety resources and measures, improve the efficiency and effectiveness of safety management, enhance the level of project safety, and ensure the safety of personnel and assets during the construction process.

[0004] The traditional construction project safety risk classification management method focuses on preventing and controlling known risks, but has deficiencies in dynamic risk identification and real-time response. It relies on regular risk assessments and post-accident analysis, lacks the effective use of real-time data and the ability to assess risks immediately, resulting in difficulty in timely adjustment and response when unforeseen new risks arise in a rapidly changing construction environment, increasing the risk of accidents. It is unable to quickly and accurately identify the responsible persons and relevant managers for sudden safety accidents or violations, resulting in processing delays, affecting the timeliness and effectiveness of risk control, and lacks the ability to continuously monitor and provide real-time feedback mechanisms. There is a lack of immediate assessment and adjustment of the effectiveness of the implementation of safety measures, which makes it impossible to optimize safety measures based on actual conditions, affecting the effectiveness of safety management. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system for hierarchical management of construction project safety risks.

[0006] In order to achieve the above object, the present invention adopts the following technical solution, a method for hierarchical management and control of construction project safety risks, comprising the following steps:

[0007] S1: Based on the construction log, by analyzing the construction log, identify multiple violations and assess their severity, match risk scores for multiple violations, and generate a standardized risk indicator table;

[0008] S2: Based on the standardized risk indicator table, the construction site is monitored in real time, and according to the actual risk events, the severity of multiple risk events is evaluated and the risk level is calculated to generate a real-time risk rating result;

[0009] S3: Based on the real-time risk rating results, identify the responsible persons and managers related to the current risk event by analyzing the project data and employee role information, match and send risk notification information according to the responsible person roles, and generate a risk message notification record;

[0010] S4: Using the risk message notification record, the response process of multiple risk events is recorded in real time, including risk level, responsibility allocation, processing status, event time and location, to generate a risk event record;

[0011] S5: Based on the risk event records, real-time evaluation of the actual effects of safety response measures in multiple risk events is performed to generate response effect evaluation information;

[0012] S6: Based on the response effect evaluation information and according to the location information of multiple risk events, a risk distribution map is drawn by marking the risk areas and the locations of risk events, and the diffusion path of risk events is analyzed to generate hotspot location marking information.

[0013] As a further scheme of the present invention, the standardized risk index table includes the risk score of workers not wearing safety equipment, the risk score of mechanical equipment operation violations, and the risk level of construction areas not marked as required; the real-time risk rating results include the risk event level, risk event frequency information, and risk event impact assessment results; the risk message notification record includes the risk event responsible person identification result, notification information content matching result, and notification information response status; the risk event record includes event process record, time and geographic location information, and response measure implementation record; the response effect evaluation information includes risk level comparison information before and after the implementation of safety measures, accident rate change data, and cost-benefit analysis results; the hotspot location marking information includes the coordinates of each risk area, risk type information, and accident data statistics.

[0014] As a further solution of the present invention, based on the construction log, by analyzing the construction log, identifying multiple violations and evaluating the severity, matching risk scores for the multiple violations, and generating a standardized risk indicator table, the specific steps are:

[0015] S101: Based on the construction log, extract the illegal behaviors recorded in the log, including not wearing a safety helmet and illegal equipment operation, and generate a record of illegal events;

[0016] S102: Based on the violation event records, perform severity assessments on multiple violation behaviors according to the risks and impacts of the violation behaviors, match risk scores for multiple violation types, and generate a risk score matching list;

[0017] S103: Based on the risk score matching list, taking into account industry standards and safety regulations, the risk scores of various violations are adjusted and optimized to generate a standardized risk indicator table.

[0018] As a further solution of the present invention, based on the standardized risk index table, the construction site is monitored in real time, and according to the actual risk events, the severity of multiple risk events is evaluated and the risk level is calculated, and the steps of generating real-time risk rating results are specifically as follows:

[0019] S201: Based on the standardized risk indicator table, by real-time monitoring of the construction site, identifying and recording illegal behaviors, including the type, time and location information of the illegal events, and generating real-time illegal event data;

[0020] S202: Based on the real-time violation event data, by matching with risk indicators, assessing the severity of multiple security violation behaviors, calculating risk levels, and generating event risk rating records;

[0021] S203: According to the event risk rating record, the risk level of the target event is calculated according to the risk levels and occurrence frequencies of multiple violations in the target risk event, and a real-time risk rating result is generated.

[0022] As a further solution of the present invention, the specific formula for calculating the risk level of the target event is:

[0023] ;

[0024] in, Representative The weight coefficient of each violation, Representative The risk level of the violation, Represents the target risk event The number of violations that occurred, Represents the calculated overall risk level, An index representing a different violation.

[0025] As a further solution of the present invention, based on the real-time risk rating result, by analyzing the project data and employee role information, identifying the responsible persons and managers related to the current risk event, and matching and sending risk notification information according to the responsible person role, the steps of generating the risk message notification record are specifically as follows:

[0026] S301: Based on the real-time risk rating results, analyze the types, occurrence times, and impact areas of multiple risk events to generate risk event analysis data;

[0027] S302: According to the risk event analysis data, by analyzing the project data and employee role information, identifying the responsible persons and managers related to the current risk event, and generating a responsible person identification result;

[0028] S303: Using the identification result of the responsible person, configure notification information, including location information, time information, and type information of the risk event, and send it to the responsible person and the manager to generate a risk message notification record.

[0029] As a further solution of the present invention, the risk message notification record is used to record the response process of multiple risk events in real time, including risk level, responsibility allocation, processing status, event time and location. The steps of generating the risk event record are specifically as follows:

[0030] S401: Based on the risk message notification record, real-time tracking of the responses of multiple responsible persons to the risk notification, recording the processing status and time of the risk event, and generating a risk processing tracking record;

[0031] S402: Based on the risk processing tracking record, the response process information of the risk event is recorded in real time, including the risk level, responsible person, processing status, time and location information, and location information record data is generated;

[0032] S403: Based on the location information record data, classify the risk event records according to the time information to generate risk event records.

[0033] As a further solution of the present invention, based on the risk event records, the actual effects of the safety response measures in multiple risk events are evaluated in real time, and the steps of generating response effect evaluation information are specifically as follows:

[0034] S501: Based on the risk event record, assess the risk level before and after the response measures are implemented, and generate risk level assessment data;

[0035] S502: Based on the risk level assessment data, by calculating the change range of the risk level before and after the execution of multiple security measures, the processing effect of multiple measures on the risk event is evaluated, and the measure effect analysis result is generated;

[0036] S503: Based on the measure effect analysis result, by evaluating the response effects of various risk events, matching optimal response measures for various risk events and constructing a response measure matching list, response effect evaluation information is generated.

[0037] As a further solution of the present invention, based on the response effect evaluation information, according to the occurrence location information of multiple risk events, by marking the risk area and the location of the risk event, drawing a risk distribution map, and analyzing the diffusion path of the risk event, the steps of generating hotspot location marking information are specifically as follows:

[0038] S601: Based on the response effect evaluation information, and according to the location data of multiple risk events, calculate the geographic coordinate information and generate an event geographic coordinate set;

[0039] S602: Using the event geographic coordinate set, draw a risk distribution map according to the coordinate data of the occurrence locations of multiple risk events;

[0040] S603: Based on the risk distribution map, analyze the spatial relationship between risk events, evaluate the risk hotspot areas and risk diffusion paths, and generate hotspot location marking information.

[0041] A system for hierarchical management and control of construction project safety risks, the system for hierarchical management and control of construction project safety risks is used to execute the above-mentioned method for hierarchical management and control of construction project safety risks, the system comprising:

[0042] The log analysis module analyzes and identifies various violations based on construction logs, including failure to wear a safety helmet and equipment operation violations. It evaluates the severity of various violations and generates a standardized risk indicator table.

[0043] The real-time monitoring module analyzes the activities at the construction site in real time based on the standardized risk indicator table, identifies risk events, classifies them and assesses their risk levels, and generates real-time risk rating results;

[0044] Based on the real-time risk rating results, the risk notification module analyzes project data and employee roles, identifies responsible persons and managers related to target risk events, matches and sends risk notification information according to roles, and generates risk message notification records;

[0045] The processing record module records the response process of multiple risk events based on the risk message notification record, including the risk level, responsible person, processing status and specific location of the event, and generates a risk event record;

[0046] The effect evaluation module is based on the risk event records, compares the risk levels before and after event processing, evaluates the effectiveness of multiple response measures, analyzes the geographical distribution and diffusion path of risk events, and generates hotspot location marking information.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In the present invention, by identifying multiple violations and matching risk scores, more accurate risk prediction is provided. By combining project data with employee role information, responsible persons and managers are automatically identified and risk notifications are made, the risk communication process is optimized to ensure the immediate transmission of information and the rapid resolution of problems. Combined with the evaluation of the effectiveness of safety measures, response measures are optimized and the efficiency and effectiveness of safety management are improved. By analyzing the geographic data of risk events and drawing risk distribution maps, an intuitive understanding of risk diffusion trends is provided to help managers prevent risks and allocate resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0050] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0051] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0052] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0053] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0054] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0055] Figure 7 This is a detailed flow chart of S6 of the present invention;

[0056] Figure 8 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0059] See also Figure 1 The present invention provides a technical solution, a method for hierarchical management and control of construction project safety risks, comprising the following steps:

[0060] S1: Based on the construction log, by analyzing the construction log, identify multiple violations and assess their severity, match risk scores for multiple violations, and generate a standardized risk indicator table;

[0061] S2: Based on the standardized risk indicator table, the construction site is monitored in real time. According to the actual risk events, the severity of multiple risk events is evaluated and the risk level is calculated to generate real-time risk rating results;

[0062] S3: Based on the real-time risk rating results, by analyzing project data and employee role information, identify the responsible persons and managers related to the current risk event, match and send risk notification information according to the responsible person's role, and generate risk message notification records;

[0063] S4: Use risk message notification records to record the response process of multiple risk events in real time, including risk level, responsibility allocation, processing status, event time and location, and generate risk event records;

[0064] S5: Based on risk event records, evaluate the actual effects of safety response measures in multiple risk events in real time and generate response effect evaluation information;

[0065] S6: Based on the response effect evaluation information and the location information of multiple risk events, the risk distribution map is drawn by marking the risk areas and the locations of risk events, and the diffusion path of risk events is analyzed to generate hotspot location marking information.

[0066] The standardized risk indicator table includes the risk score for workers not wearing safety equipment, the risk score for mechanical equipment operation violations, and the risk level of construction areas not marked as required. Real-time risk rating results include risk event levels, risk event frequency information, and risk event impact assessment results. Risk message notification records include risk event responsible person identification results, notification information content matching results, and notification information response status. Risk event records include event process records, time and geographic location information, and response measures implementation records. Response effect evaluation information includes risk level comparison information before and after the implementation of safety measures, accident rate change data, and cost-benefit analysis results. Hotspot location marking information includes the coordinates of each risk area, risk type information, and accident data statistics.

[0067] See also Figure 2 ,Based on the construction log, by analyzing the construction log, identifying multiple violations and assessing their severity, matching risk scores for multiple violations, and generating a standardized risk indicator table, the specific steps are:

[0068] S101: Based on the construction log, extract the illegal behaviors recorded in the log, including not wearing a safety helmet and illegal equipment operation, and generate a record of illegal events;

[0069] In sub-step S101, based on the daily records of the construction site, violation data are extracted, including failure to wear a safety helmet and improper operation of equipment. Each violation event is classified and recorded according to the time, location, personnel involved and specific behavior. The records are verified using data to ensure completeness and accuracy. The process involves using data screening algorithms to filter out erroneous and incomplete log entries, and using regular expressions to match keywords related to violations to ensure that each violation can be effectively recorded. At the same time, logical checks are applied to ensure that the data is not duplicated. The generated violation event records provide clear evidence of violations, which is convenient for subsequent risk assessments.

[0070] S102: Based on the violation event records, perform severity assessments on multiple violation behaviors according to the risks and impacts of the violation behaviors, match risk scores for multiple violation types, and generate a risk score matching list;

[0071] In the above content, the severity of various violations is assessed according to the risk and impact of the violations, and the risk scores are matched using the formula , calculate the risk score;

[0072] In the formula, and is a quantitative score for the violation, and is the weight assigned based on the severity and prevalence of the behavior, is the risk score;

[0073] Detailed explanation of the formula and the process of formula calculation and derivation:

[0074] Assume target violation , , weight , ,calculate :

[0075] ;

[0076] result The comprehensive risk score for the violation is 6.5. The score reflects the potential danger of the violation and the urgency of the attention required. The calculation process is used to provide a quantitative method for risk management and help formulate targeted security supervision strategies.

[0077] S103: Based on the risk score matching list, taking into account industry standards and safety regulations, the risk scores of various violations are adjusted and optimized to generate a standardized risk indicator table;

[0078] In sub-step S103, the risk scores of violations are adjusted and optimized according to the risk score matching list. The process takes into account the latest requirements of industry standards and current safety regulations, analyzes the legal consequences and severity of different violations stipulated in current regulations, and uses data normalization technology to standardize risk scores to ensure that data from different sources are compared under the same standard. The risk scores are adjusted in combination with expert recommendations to ensure that each risk score accurately reflects the potential hazards of the violation. The generated standardized risk indicator table provides a scientific basis for safety management and helps management formulate more effective safety control measures.

[0079] See also Figure 3 Based on the standardized risk indicator table, the construction site is monitored in real time, and according to the actual risk events, the severity of multiple risk events is evaluated and the risk level is calculated. The specific steps for generating real-time risk rating results are as follows:

[0080] S201: Based on the standardized risk indicator table, through real-time monitoring of the construction site, identify and record violations, including the type, time and location of the violation, and generate real-time violation event data;

[0081] In sub-step S201, a real-time monitoring system is used to capture violations at the construction site. By combining video surveillance and sensor data, image recognition technology is used, and deep learning models such as convolutional neural networks are used to automatically identify violations such as not wearing a safety helmet and improper operation of equipment. The system records the type, time, location and other information of the violation in real time. Each violation is marked with a timestamp and geographic location data to ensure the accuracy and traceability of the information. The captured data is transmitted to a central database for processing through a real-time data stream processing platform such as Apache Kafka. The generated real-time violation event data is designed to respond to violations immediately and provide a fast feedback loop.

[0082] S202: Based on the real-time violation event data, by matching with the risk indicators, the severity of multiple security violation behaviors is evaluated, and the risk level is calculated to generate an event risk rating record;

[0083] In sub-step S202, based on the real-time violation event data obtained from the real-time monitoring system, a risk assessment algorithm is used to match the existing risk indicators, and a risk scoring model, including multivariate linear regression, is used to estimate the potential danger and urgency of each violation. The violations are analyzed based on their type, the context in which they occur, and the possible consequences, and corresponding risk scores are assigned accordingly. The scores reflect the severity of the violations, and the results are output in the form of event risk rating records. Each record indicates the risk level of each violation, enabling the security management team to respond according to risk priorities.

[0084] S203: Calculate the risk level of the target event based on the event risk rating record and the risk levels and occurrence frequencies of multiple violations in the target risk event, and generate a real-time risk rating result;

[0085] The specific formula for calculating the risk level of the target event is:

[0086] ;

[0087] in, Representative The weight coefficient of each violation, Representative The risk level of the violation, Represents the target risk event The number of violations that occurred, Represents the calculated overall risk level, An index representing different violations.

[0088] formula

[0089] ;

[0090] Detailed explanation of the formula and the process of formula calculation and derivation:

[0091] The formula multiplies and sums the risk levels, occurrence frequencies, and weight coefficients of multiple violations to obtain a quantitative total risk score, thereby assessing the risk level of the target risk event.

[0092] Parameter meaning and setting value

[0093] For the The weight coefficient of each violation reflects the contribution of the potential risk of the violation to the total risk. For the The risk level of the violation, For the The number of violations. Assume that in a risk event, there are two violations, including not wearing a helmet and improper operation of equipment. The weight of not wearing a helmet is 0.3, the risk level is 4, and it occurs 20 times. The weight of improper operation of equipment is 0.7, the risk level is 5, and it occurs 10 times.

[0094] Substitute the parameters into the formula for calculation:

[0095] ;

[0096] The calculation result 59 shows that the risk level of the target risk event is relatively high. The overall risk level prompts the project management team to take more stringent safety measures and monitoring to reduce the accident rate and protect the safety of workers.

[0097] See also Figure 4 Based on the real-time risk rating results, by analyzing project data and employee role information, identify the responsible persons and managers related to the current risk event, and match and send risk notification information according to the responsible person's role. The specific steps for generating risk message notification records are as follows:

[0098] S301: Based on the real-time risk rating results, analyze the types, occurrence time, and impact areas of multiple risk events to generate risk event analysis data;

[0099] In sub-step S301, based on the real-time risk rating results, data analysis techniques, including data clustering and time series analysis methods, are used to analyze different types of risk events. Data processing is performed through Python's Pandas library to extract the key attributes of each risk event, including event type, occurrence time and affected area. Time series analysis, such as the ARIMA model, is used to predict the occurrence trend of risk events. Clustering methods such as DBSCAN are used to analyze the risk density in different regions and times, and generate risk event analysis data containing risk levels, impact ranges and potential trends. The data provides a scientific basis for risk management and preventive measures, helping security teams identify potential risk hotspots and optimize resource allocation and emergency response strategies.

[0100] S302: Based on the risk event analysis data, by analyzing the project data and employee role information, identify the responsible persons and managers related to the current risk event, and generate the responsible person identification result;

[0101] In sub-step S302, risk event analysis data is used in combination with project data and employee role information in the project management database to perform responsible person identification. The graph database technology Neo4j is used to build a project and employee relationship network. The responsible persons and managers associated with the target risk event are determined through network analysis tools. The process includes analyzing the nodes and edges in the network and identifying key responsibility nodes, i.e., employees and managers associated with risk events. The generated responsible person identification results list the associated responsible persons for each risk event, providing a clear basis for subsequent accountability and risk management.

[0102] S303: Using the identification result of the responsible person, configure notification information, including the location information, time information, and type information of the risk event, and send it to the responsible person and the manager to generate a risk message notification record;

[0103] In sub-step S303, risk message notifications are configured and sent based on the identification results of the responsible persons. An automated notification system is used in combination with the SMTP protocol for email notifications. SMS and in-application notification functions are integrated through the API to ensure multi-channel dissemination of information. The notification information includes the location, time, and type of the risk event, ensuring that each responsible person and manager can obtain the specific circumstances of the event in real time and ensuring the accuracy and consistency of the notification content. The generated risk message notification records provide records and tracking for each notification sent, thereby enhancing the efficiency and effectiveness of risk notifications.

[0104] See also Figure 5 , using risk message notification records, real-time record of the response process of multiple risk events, including risk level, responsibility allocation, processing status, event time and location. The specific steps for generating risk event records are:

[0105] S401: Based on the risk message notification record, real-time tracking of the responses of multiple responsible persons to the risk notification, recording the processing status and time of the risk event, and generating risk processing tracking records;

[0106] In sub-step S401, based on the risk message notification records, a real-time monitoring system is implemented to track the response of the responsible person to the risk notification. An event-driven architecture is used to ensure that relevant behaviors are recorded in real time when the responsible person responds to the risk notification. The process uses WebSocket technology to achieve real-time data transmission. When the responsible person takes action such as confirming receipt of the notification and updating the processing status, the timestamp and processing status are automatically recorded. The generated risk processing tracking record provides time and status updates for each response behavior, allowing the management team to understand the progress of risk event processing in real time, thereby evaluating the timeliness and effectiveness of the response measures.

[0107] S402: Based on the risk processing tracking record, the response process information of the risk event is recorded in real time, including the risk level, responsible person, processing status, time and location information, and the location information record data is generated;

[0108] In sub-step S402, risk processing tracking records are used to record the response process information of risk events. Through the SQL database management system, the key information of each risk event is structured and stored, including risk level, responsible person, processing status, time and specific location. The recording process involves data indexing and query optimization technology to ensure that risk event information can be quickly retrieved and updated. The generated location information record data accurately reflects the geographical location and time node of each event, providing a basis for geographic information system analysis and risk positioning.

[0109] S403: Based on the location information record data, the risk event record is classified according to the time information to generate a risk event record;

[0110] In sub-step S403, based on the location information record data, the time series analysis method is used to classify and organize the risk event records, the Python programming language and the Pandas library are used to process time-related data, and the event records are sorted and classified by timestamp to ensure that the risk events in each time period are accurately classified. Statistical analysis methods, such as frequency distribution and probability density function, are applied to analyze the distribution characteristics of risk events in different time periods. The generated risk event records provide a time-ordered overview of events for risk management, helping the management team to identify high-risk periods and optimize future risk prevention strategies accordingly.

[0111] See also Figure 6 , based on the risk event records, the actual effects of security response measures in multiple risk events are evaluated in real time. The specific steps for generating response effect evaluation information are as follows:

[0112] S501: Based on the risk event records, evaluate the risk level before and after the implementation of the response measures and generate risk level assessment data;

[0113] In sub-step S501, based on risk event records, a multi-factor risk assessment model is used to evaluate the change in risk level before and after the implementation of response measures. Combined with decision tree and risk matrix technology, the initial risk level of each risk event and the risk level after the implementation of measures are calculated and compared. Through comparative analysis, risk level assessment data is generated. The data shows the actual effect of each risk event response measure, such as the percentage of risk reduction and the absolute level change. The evaluation process helps identify the most effective risk response measures, provides a basis for optimizing existing security strategies, and enhances prevention and response capabilities.

[0114] S502: Based on the risk level assessment data, by calculating the change range of the risk level before and after the execution of various security measures, the processing effect of various measures on the risk event is evaluated, and the measure effect analysis result is generated;

[0115] In sub-step S502, based on the risk level assessment data, the change range of risk levels before and after the implementation of various security measures is analyzed, and the effect of these measures on the handling of risk events is evaluated. The difference analysis method is used according to the formula , calculate the total change value of risk level;

[0116] In the formula, Represents the total change in risk level, It is The risk level before the implementation of measures for each risk event, is the risk level after the measures are implemented, is the total number of risk events assessed;

[0117] Detailed explanation of the formula and the process of formula calculation and derivation:

[0118] Assume there are three risk events, and the risk levels before the measures are implemented are , , The risk levels after execution are , , , substitute the parameters into the formula for calculation:

[0119] ;

[0120] result It shows that the overall risk level has dropped by 6 levels through the implementation of safety measures, indicating the overall effectiveness of the measures, evaluating the contribution of each safety measure to reducing the risk level, and providing data support and decision-making basis for safety management and risk control.

[0121] S503: Based on the result of the measure effect analysis, by evaluating the response effects of various risk events, matching the optimal response measures for various risk events and constructing a response measure matching list, generating response effect evaluation information;

[0122] In sub-step S503, based on the results of the measure effect analysis, optimization algorithms, such as genetic algorithms, are used to match the optimal response measures for multiple risk events. The process analyzes the response effect of each measure on different events, calculates the overall effectiveness and cost-effectiveness ratio, and determines the optimal combination of measures for each event type. The generated response effect evaluation information provides a matching list, which shows the recommended response measures and their expected effects for each risk event, improves the pertinence and efficiency of risk management, and provides a strategic template for rapid response to similar risk events in the future.

[0123] See also Figure 7 Based on the response effect evaluation information and the location information of multiple risk events, the risk distribution map is drawn by marking the risk areas and the locations of risk events, and the diffusion path of risk events is analyzed. The specific steps for generating hotspot location marking information are as follows:

[0124] S601: Based on the response effect evaluation information, the geographic coordinate information is calculated according to the location data of multiple risk events, and an event geographic coordinate set is generated;

[0125] In sub-step S601, based on the response effect evaluation information, the specific location data of each risk event is extracted, and the geographic coordinates are calculated using geographic information system technology. The process uses geocoding services such as Google Maps API to convert address data into geographic coordinates, including longitude and latitude. The location data is batch processed through automated scripts to ensure that the coordinate information of each event is accurate. The generated event geographic coordinate set provides precise spatial data for subsequent steps, making the drawing of risk maps more accurate and practical, and laying the foundation for geospatial analysis.

[0126] S602: Using the event geographic coordinate set, draw a risk distribution map according to the coordinate data of the locations where multiple risk events occurred;

[0127] In sub-step S602, the generated event geographic coordinate set is used to draw a risk distribution map through GIS software ArcGIS and QGIS. The map shows the spatial distribution of risks based on the geographic coordinate points of risk events, and represents different risk levels through color coding and symbol size, making high-risk areas easier to identify visually. It includes basic map drawing, layer overlay and spatial query function application, providing risk information with more dimensions. The generated risk distribution map provides an intuitive tool for understanding the spatial attributes and patterns of risks.

[0128] S603: Based on the risk distribution map, analyze the spatial relationship between risk events, evaluate the risk hotspot areas and risk diffusion paths, and generate hotspot location marking information;

[0129] In sub-step S603, based on the risk distribution map, spatial analysis is performed to identify the spatial relationship between risk events. Hotspot analysis technology and kernel density estimation are used to assess the risk hotspot areas and their diffusion paths. The analysis process involves advanced analysis tools in GIS software to reveal risk-intensive geographical areas and potential risk diffusion trends. The generated hotspot location marker information marks the areas where risks are concentrated and the direction of diffusion. This information is crucial for formulating risk prevention measures and emergency response strategies related to geographical locations, thereby improving the spatial accuracy and efficiency of management decisions.

[0130] See also Figure 8 A system for hierarchical control of construction project safety risks, the system for hierarchical control of construction project safety risks is used to execute the above-mentioned method for hierarchical control of construction project safety risks, the system comprises:

[0131] The log analysis module analyzes and identifies various violations based on construction logs, including failure to wear a safety helmet and equipment operation violations. It evaluates the severity of various violations and generates a standardized risk indicator table.

[0132] The real-time monitoring module analyzes the activities on the construction site in real time based on the standardized risk indicator table, identifies risk events, classifies them and assesses their risk levels, and generates real-time risk rating results;

[0133] The risk notification module is based on real-time risk rating results. It analyzes project data and employee roles, identifies responsible persons and managers related to target risk events, matches and sends risk notification information according to roles, and generates risk message notification records.

[0134] The processing record module records the response process of multiple risk events based on risk message notification records, including the risk level, responsible person, processing status and specific location of the event, and generates risk event records;

[0135] The effect evaluation module is based on risk event records. By comparing the risk levels before and after event processing, it evaluates the effectiveness of various response measures, analyzes the geographical distribution and diffusion path of risk events, and generates hotspot location marking information.

[0136] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for hierarchical management and control of construction project safety risks, characterized in that: The following steps are involved: Based on the construction log, by analyzing the construction log, identify various violations and assess their severity, match risk scores for various violations, and generate a standardized risk indicator table; Based on the standardized risk indicator table, the construction site is monitored in real time, and according to the actual risk events, the severity of multiple risk events is evaluated and the risk level is calculated to generate a real-time risk rating result; Based on the standardized risk index table, the construction site is monitored in real time, and according to the actual risk events, the severity of multiple risk events is evaluated and the risk level is calculated. The steps of generating the real-time risk rating result are as follows: Based on the standardized risk indicator table, by real-time monitoring of the construction site, identifying and recording violations, including the type, time and location information of the violation events, and generating real-time violation event data; Based on the real-time violation event data, by matching with risk indicators, the severity of multiple security violation behaviors is evaluated, and the risk level is calculated to generate an event risk rating record; According to the event risk rating record, the risk level of the target event is calculated according to the risk level and occurrence frequency of multiple violations in the target risk event, and a real-time risk rating result is generated; The specific formula for calculating the risk level of the target event is: ； in, represents the weight coefficient of the ith violation, r i represents the risk level of the ith violation, f i represents the number of occurrences of the i-th violation in the target risk event, R represents the calculated overall risk level, and i represents the index of different violations; Based on the real-time risk rating results, by analyzing project data and employee role information, identify the responsible persons and managers related to the current risk event, match and send risk notification information according to the responsible person's role, and generate a risk message notification record; Based on the real-time risk rating results, by analyzing project data and employee role information, identifying the responsible persons and managers related to the current risk event, and matching and sending risk notification information according to the responsible person roles, the steps of generating risk message notification records are as follows: Based on the real-time risk rating results, data clustering and time series analysis methods are used to analyze different types of risk events. Data processing is performed through Python's Pandas library to extract key attributes of each risk event, including event type, occurrence time, and affected area. The ARIMA model is used to predict the occurrence trend of risk events. The clustering method DBSCAN is used to analyze the risk density in different regions and times to generate risk event analysis data. Using the risk event analysis data, combined with the project data and employee role information in the project management database, the responsible person identification is performed, and the graph database technology Neo4j is used to build a project and employee relationship network. Through the network analysis tool, the responsible persons and managers associated with the target risk event are determined, including analyzing the nodes and edges in the network, identifying the employees and managers associated with the risk event, and generating the responsible person identification results; Using the risk message notification record, the response process of multiple risk events is recorded in real time, including risk level, responsibility allocation, processing status, event time and location, to generate risk event records; The risk message notification record is used to record the response process of multiple risk events in real time, including risk level, responsibility allocation, processing status, event time and location. The steps for generating risk event records are as follows: Based on the location information record data, the time series analysis method is used to classify and organize the risk event records. The Python programming language and Pandas library are used to process time-related data. Event records are sorted and classified by timestamps. The frequency distribution and probability density function are applied to analyze the distribution characteristics of risk events in different time periods and generate risk event records. Based on the risk event records, the actual effects of safety response measures in multiple risk events are evaluated in real time to generate response effect evaluation information; Based on the response effect evaluation information, according to the occurrence location information of multiple risk events, by marking the risk areas and the locations of risk events, a risk distribution map is drawn, and the diffusion path of the risk events is analyzed to generate hotspot location marking information; Based on the response effect evaluation information, according to the occurrence location information of multiple risk events, by marking the risk areas and the locations of risk events, drawing a risk distribution map, and analyzing the diffusion path of the risk events, the steps of generating hotspot location marking information are specifically as follows: Using the event geographic coordinate set, the GIS software ArcGIS and QGIS are used to draw risk distribution maps. The maps show the spatial distribution of risks based on the geographic coordinate points of risk events, and use color coding and symbol size to indicate different risk levels, thus generating risk distribution maps. Based on the risk distribution map, spatial analysis is performed to identify the spatial relationship between risk events, and kernel density estimation is used to evaluate risk hotspots and their diffusion paths, revealing risk-intensive geographical areas and potential risk diffusion trends, and generating hotspot location marking information.

2. The method for hierarchical management and control of construction project safety risks according to claim 1 is characterized in that: The standardized risk indicator table includes the risk score for workers not wearing safety equipment, the risk score for mechanical equipment operation violations, and the risk level of construction areas not marked as required; the real-time risk rating results include the risk event level, risk event frequency information, and risk event impact assessment results; the risk message notification record includes the risk event responsible person identification result, notification information content matching result, and notification information response status; the risk event record includes event process record, time and geographic location information, and response measure implementation record; the response effect evaluation information includes risk level comparison information before and after the implementation of safety measures, accident rate change data, and cost-benefit analysis results; the hotspot location marking information includes the coordinates of each risk area, risk type information, and accident data statistics.

3. The method for hierarchical management and control of construction project safety risks according to claim 1 is characterized in that: Based on the construction log, by analyzing the construction log, identifying multiple violations and assessing their severity, matching risk scores for multiple violations, and generating a standardized risk indicator table, the specific steps are as follows: Based on the construction log, extract the violations recorded in the log, including failure to wear a safety helmet and equipment operation violations, and generate violation event records; Based on the violation event records, a severity assessment is performed on a plurality of violation behaviors according to the risks and impacts of the violation behaviors, risk scores are matched for a plurality of violation types, and a risk score matching list is generated; Based on the risk score matching list, the risk scores of various violations are adjusted and optimized in consideration of industry standards and safety regulations to generate a standardized risk indicator table.

4. The method for hierarchical management and control of construction project safety risks according to claim 1 is characterized in that: Based on the real-time risk rating result, by analyzing the project data and employee role information, identifying the responsible persons and managers related to the current risk event, and matching and sending risk notification information according to the responsible person roles, the step of generating the risk message notification record also includes: According to the risk event analysis data, by analyzing the project data and employee role information, the responsible persons and managers related to the current risk event are identified, and the responsible person identification results are generated; Using the responsible person identification result, notification information is configured, including location information, time information, and type information of the risk event, and sent to the responsible person and manager to generate a risk message notification record.

5. The method for hierarchical management and control of construction project safety risks according to claim 1 is characterized in that: The risk message notification record is used to record the response process of multiple risk events in real time, including risk level, responsibility allocation, processing status, event time and location. The step of generating the risk event record also includes: Based on the risk message notification record, the responses of multiple responsible persons to the risk notification are tracked in real time, the processing status and time of the risk event are recorded, and the risk processing tracking record is generated.

6. The method for hierarchical management and control of construction project safety risks according to claim 1 is characterized in that: Based on the risk event records, the actual effects of the safety response measures in multiple risk events are evaluated in real time, and the steps of generating response effect evaluation information are specifically as follows: Based on the risk event records, assess the risk levels before and after the implementation of the response measures, and generate risk level assessment data; Based on the risk level assessment data, by calculating the change range of the risk level before and after the execution of various safety measures, the treatment effect of various measures on the risk event is evaluated, and the result of the measure effect analysis is generated; Based on the measure effect analysis results, by evaluating the response effects of various risk events, optimal response measures are matched for various risk events and a response measure matching list is constructed to generate response effect evaluation information.

7. The method for hierarchical management and control of construction project safety risks according to claim 1 is characterized in that: Based on the response effect evaluation information, according to the occurrence location information of multiple risk events, by marking the risk areas and the locations of the risk events, drawing a risk distribution map, and analyzing the diffusion path of the risk events, the step of generating hotspot location marking information also includes: Based on the response effect evaluation information, the geographic coordinate information is calculated according to the location data of multiple risk events, and an event geographic coordinate set is generated.

8. A system for hierarchical management and control of construction project safety risks, characterized in that: According to the method for hierarchical management and control of construction project safety risks according to any one of claims 1 to 7, the system comprises: The log analysis module analyzes and identifies various violations based on construction logs, including failure to wear a safety helmet and equipment operation violations. It evaluates the severity of various violations and generates a standardized risk indicator table. The real-time monitoring module analyzes the activities at the construction site in real time based on the standardized risk indicator table, identifies risk events, classifies them and assesses their risk levels, and generates real-time risk rating results; Based on the real-time risk rating results, the risk notification module analyzes project data and employee roles, identifies responsible persons and managers related to target risk events, matches and sends risk notification information according to roles, and generates risk message notification records; The processing record module records the response process of multiple risk events based on the risk message notification record, including the risk level, responsible person, processing status and specific location of the event, and generates a risk event record; The effect evaluation module is based on the risk event records, compares the risk levels before and after event processing, evaluates the effectiveness of multiple response measures, analyzes the geographical distribution and diffusion path of risk events, and generates hotspot location marking information.

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