Intelligent risk prevention and control system and method for highway construction

Abstract

The invention discloses an intelligent risk prevention and control system and method for highway construction, and relates to the technical field of intelligent analysis, and the method comprises the following steps: carrying out the first analysis of accident time, obtaining a first risk prevention and control strategy, calculating the proportion of each man-made reason, constructing a safety evaluation equation, and setting the monitoring rule of each man-made reason. And obtaining a current safety score, dividing a current safety level, and sending an early warning signal. Accident sites, accident types, accident time and corresponding accident reasons are recorded in detail, the accident reasons are divided into natural reasons and man-made reasons, accident data are analyzed more accurately, safety management work is more scientific and systematized by constructing a safety evaluation equation, monitoring rules are set, and the safety management efficiency is improved. The construction monitoring video is utilized to score each man-made reason, and the current safety score is obtained according to the risk assessment equation, so that potential safety hazards can be found in time, and accidents are prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent analysis, and in particular to an intelligent risk prevention and control system and method for highway construction. Background Art

[0002] In recent years, with the rapid development of information technologies such as big data, cloud computing, and the Internet of Things, the data collection, processing, and analysis capabilities in highway construction have been significantly improved. By building a digital construction platform, information-based construction technology has achieved real-time monitoring and management of the construction process, improving construction efficiency and quality. At the same time, information-based construction technology also provides construction personnel with more intuitive and three-dimensional construction scenes through technologies such as virtual reality and augmented reality, which helps to improve the safety and accuracy of construction.

[0003] At present, a Chinese invention patent with publication number CN113887962B discloses a method for identifying and preventing risks in highway reconstruction and expansion construction operations. The method identifies and classifies risk factors in highway reconstruction and expansion construction operations, conducts a survey on risk factors in highway reconstruction and expansion construction operations, quantifies risks in highway reconstruction and expansion construction operations, constructs and analyzes a risk model for highway reconstruction and expansion construction operations, and summarizes the analysis results. However, the relevant technology does not prevent and control risks in different ways based on subjective and objective risk factors, lacks the pertinence and meticulousness of analysis and early warning, does not identify construction risks through automated judgment means, and does not quantify construction risks. This is not conducive to the objectivity and rapid responsiveness of the analysis, and has certain limitations. Summary of the Invention

[0004] The technical problem solved by the present invention is that the relevant technologies do not prevent and control risks in different ways based on subjective and objective risk factors, lack the pertinence and meticulousness of analysis and early warning, do not identify construction risks through automated judgment methods, and do not quantify construction risks, which is not conducive to the objectivity and rapid responsiveness of analysis and has certain limitations.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, a method for intelligent risk prevention and control in highway construction comprises the following steps:

[0006] Step S100: Acquire accident data, including accident location, accident type, accident time, and corresponding accident cause, and classify the accident cause corresponding to each accident type into natural cause and human cause;

[0007] Step S200: Select any accident location, obtain the accident type of the accident at the accident location caused by natural causes, obtain the accident time corresponding to the accident type, perform a first analysis on the accident time, and obtain a first risk prevention and control strategy based on the first analysis result;

[0008] Step S300: Count the number of times any human cause occurs at each accident site, record it as the second number, calculate the proportion of each human cause based on the second number, and construct a safety assessment equation based on the proportion of each human cause;

[0009] Step S400: Set monitoring rules for each human factor, obtain the current construction monitoring video, score each human factor in the current monitoring video according to the monitoring rules, and obtain the current safety score according to the risk assessment equation;

[0010] Step S500: Set a security score threshold, divide the current security level according to the security score threshold, and send an early warning signal according to the current security level.

[0011] As a preferred solution of the intelligent risk prevention and control method for highway construction described in the present invention, the accident location is represented by the province, city, and district / county to which the accident occurred;

[0012] The accident time is expressed as the year and month when the accident occurred;

[0013] The types of accidents mentioned include collapse, object strike, fall from height, explosion and vehicle damage;

[0014] The causes of the collapse include continuous rainfall, faulty operations, lack of safety training, failure to set up emergency escape routes, and operational management errors;

[0015] The causes of object strike accidents include incorrect operation, lack of safety measures, lack of safety training and operational management errors;

[0016] Causes of falls from heights include extreme cold weather, lack of safety measures at work, lack of safety training, and operational management errors;

[0017] The causes of the explosion include incorrect operation, lack of safety training and operational management errors;

[0018] The cause of the vehicle injury accident was operational management error;

[0019] The cause of the accident is summarized based on expert experience. The continuous rainfall is represented by the weather in which the rainfall cycle exceeds the first day and the average daily rainfall exceeds a first value. The first day and the first value are obtained through historical experience, and are represented by values ​​that can make the ground humidity greater than the first humidity. The extremely cold weather is represented by the weather in which the temperature is lower than the first temperature and the air humidity is greater than the second value. The first temperature and the second value are obtained through historical experience, and are represented by values ​​that can make the ground friction less than the first friction.

[0020] As a preferred solution of the intelligent risk prevention and control method for highway construction described in the present invention, the natural causes of collapse include continuous rainfall, and the human causes of collapse include incorrect operation, lack of safety training, failure to set up emergency escape routes, and operational management errors;

[0021] The natural cause of falls from heights is extreme cold weather, while the man-made causes of falls from heights include lack of safety measures at work, lack of safety training, and errors in work management;

[0022] Accidents caused by object impact, explosion and vehicle damage are all human factors.

[0023] As a preferred solution of the intelligent risk prevention and control method for highway construction described in the present invention, the first analysis method includes:

[0024] Select any accident location, obtain the accident type that occurred at the accident location, and set filtering conditions, including whether the accident type is collapse or fall from height, and whether the accident cause is continuous rainfall or extreme cold weather;

[0025] According to the screening conditions, the accident types occurring at the accident site are screened and recorded as the first accident. The accident time of the first accident is obtained, and the number of first accidents in each month whose accident time belongs to the first accident is counted in months, and recorded as the first number. The first number of extremely cold weather and the first number of continuous rainfall are sorted in descending order respectively, and the first number of extremely cold weather with the largest value and the first number of continuous rainfall with the largest value are selected, and the corresponding months are set as the extremely cold month and the continuous rainfall month.

[0026] As a preferred solution of the intelligent risk prevention and control method for highway construction described in the present invention, the configuration method of the first risk prevention and control strategy includes:

[0027] Traverse the accident sites, obtain the first mapping relationship between the extremely cold month and the continuous rainy month corresponding to each accident site, and establish the first mapping relationship between the accident site and the extremely cold month and the continuous rainy month;

[0028] The current construction site is obtained, and the extremely cold months and continuous rainy months of the current construction site are obtained according to the first mapping relationship. The first risk prevention and control strategy is set according to the extremely cold months and continuous rainy months. The first risk prevention and control strategy includes:

[0029] Stop construction during extremely cold months and months with continuous rainfall, set up an electronic fence around the construction area, and place warning signs of the first size and first color around the electronic fence;

[0030] One month before the extreme cold month, the drainage system around the electric fence will be cleaned and unblocked, and the road sections around the electric fence that are prone to ice formation will be paved with sand;

[0031] Obtain the collapse range of the current construction site in a rainy month. The collapse range is obtained based on expert experience. A bounding box is set according to the degree of collapse. The electronic fence is contained in the bounding box. The bounding box represents the impact range of the collapse at the current construction site. In the month before the continuous rainy month, set a warning sign of the second size and second color around the bounding box.

[0032] As a preferred solution of the intelligent risk prevention and control method for highway construction described in the present invention, the calculation method of the proportion of each human factor includes:

[0033] The number of times any human cause occurred at each accident site is counted, recorded as the second number, the total number of times each human cause occurred at each accident site is counted, recorded as the third number, and the ratio of the second number to the third number is calculated and set as the proportion of the human cause.

[0034] As a preferred solution of the intelligent risk prevention and control method for highway construction described in the present invention, the calculation expression of the safety assessment equation is:

[0035] ;

[0036] in, For the safety assessment score, For the Man-made reasons, For the The proportion of human factors, is the number of types of human factors, y∈[0,100]. The larger the safety assessment score, the greater the degree of danger.

[0037] As a preferred solution of the intelligent risk prevention and control method for highway construction described in the present invention, the method for setting the monitoring rules for each human factor includes:

[0038] Obtain a current construction monitoring video, perform frame segmentation and windowing processing on the current construction monitoring video to obtain a current construction monitoring image, obtain an operating tool and its corresponding power, where the power is expressed as the average power during the operation, and wirelessly transmit the operating tool power to a monitoring terminal;

[0039] Retrieving a construction database, inputting the working tool into the construction database, matching a standard power corresponding to the working tool, and comparing the standard power with the average power;

[0040] When the standard power is greater than the power or when the standard power is less than the power, a difference between the power and the standard power is calculated, and an absolute value is taken to obtain a first value, the first value is set as an allowable error, the first value is compared with the first value, when the first value is greater than or equal to the first value, the score of the erroneous operation is set to the first score, otherwise, the score of the erroneous operation is set to the second score, when the standard power is equal to the average power, the score of the erroneous operation is set to a third score, wherein the third score is less than the second score, and the second score is less than the first score;

[0041] Taking the protective belt and the protective cap as the first key feature, calculating the first similarity between the first key feature and the current construction monitoring image using the cosine similarity formula, setting the second value as the first similarity threshold, and comparing the first similarity with the second value. When the first similarity is greater than or equal to the second value, it indicates that the corresponding first key feature exists in the current construction monitoring image; when the first similarity is less than the second value, it indicates that the corresponding first key feature does not exist in the current construction monitoring image;

[0042] Traversing each current construction monitoring image, when the protective belt and the protective cap appear simultaneously in any current construction monitoring image, setting the score for lack of work safety measures to a fourth score; when the protective belt and the protective cap do not appear simultaneously in any current construction monitoring image, and the protective belt or the protective cap does not appear in any current construction monitoring image, setting the score for lack of work safety measures to a fifth score; when the protective belt or the protective cap appears in any current construction monitoring image, and the protective belt and the protective cap do not appear simultaneously in any current construction monitoring image, setting the score for lack of work safety measures to a sixth score, wherein the fourth score is less than the sixth score, and the sixth score is less than the fifth score;

[0043] Setting the escape route as the second key feature, calculating a second similarity between the second key feature and the current construction monitoring image using a cosine similarity formula, comparing the second similarity with a second value, and when the second similarity is greater than or equal to the second value, setting the score of not having an emergency escape route set to a seventh score; otherwise, setting the score of not having an emergency escape route set to an eighth score, where the eighth score is greater than the seventh score;

[0044] The safety administrator is set as the third key feature, a third similarity between the third key feature and the current construction monitoring image is calculated using a cosine similarity formula, the third similarity is compared with the second value, and when the second similarity is greater than or equal to the third value, the score for the operation management error is set to the ninth score; otherwise, the score for not setting up an emergency escape route is set to the tenth score;

[0045] Obtain the number of personnel training certificates, count the number of people in the surveillance video, calculate the ratio of the number of people in the surveillance video to the number of personnel training certificates, and record it as a first ratio. When the first ratio is greater than 0.8, set the score for lack of safety training to the eleventh score; otherwise, set the score for lack of safety training to the twelfth score, where the twelfth score is greater than the eleventh score.

[0046] As a preferred embodiment of the intelligent risk prevention and control method for highway construction described in the present invention, the method further comprises: obtaining a score for each human factor, calculating a sum of the scores for each human factor and recording the sum as a total score, calculating a ratio of the score for each human factor to the total score, setting the ratio of the score for the human factor to the total score as the ratio of the corresponding human factor, setting 100 as the full score, calculating the product of the full score and the ratio, setting the product of the full score and the ratio as the actual score of the corresponding human factor, substituting each actual score into a safety assessment equation to obtain a safety assessment score, setting a third value and a fourth value as a safety score threshold, wherein the third value is less than the fourth value;

[0047] The current security level classification methods include:

[0048] comparing the safety assessment score with the safety score threshold; when the safety assessment score is less than or equal to a third value, setting the current safety level to the first level; when the safety assessment score is greater than the third value and less than or equal to a fourth value, setting the current safety level to the second level; and when the safety assessment score is greater than the fourth value, setting the current safety level to the third level, wherein the first level, the second level, and the third level represent the degree of danger in descending order;

[0049] When the current safety level is the first level, a signal light of the first color and the first brightness is displayed, and the actual score of each human cause is displayed. When the current safety level is the second level, a signal light of the second color and the second brightness is displayed, and the actual score of each human cause is displayed. When the current safety level is the third level, a signal light of the third color and the third brightness is displayed, and the actual score of each human cause is displayed.

[0050] In the second aspect, an intelligent risk prevention and control system for highway construction includes a collection module, an analysis module, and an early warning module;

[0051] The acquisition module acquires accident data, including accident location, accident type, accident time, and corresponding accident cause, and classifies the accident cause corresponding to each accident type into natural cause and man-made cause;

[0052] The analysis module selects any accident location, obtains the accident type of the accident at the accident location where the cause is natural cause, obtains the accident time corresponding to the accident type, performs a first analysis on the accident time, obtains a first risk prevention and control strategy based on the first analysis result, counts the number of any human cause occurring at each accident location, records it as a second number, calculates the proportion of each human cause based on the second number, constructs a safety assessment equation based on the proportion of each human cause, sets monitoring rules for each human cause, obtains the current construction monitoring video, scores each human cause in the current monitoring video based on the monitoring rules, and obtains the current safety score based on the risk assessment equation;

[0053] The early warning module sets a security score threshold, divides the current security level according to the security score threshold, and sends an early warning signal according to the current security level.

[0054] The beneficial effects of the present invention are as follows: by recording the accident location, accident type, accident time and corresponding accident cause in detail, and distinguishing the accident causes into natural causes and human causes, the accident data can be analyzed more accurately, and accurate basic information can be provided for subsequent risk prevention and control. By counting the number of human causes and calculating the proportion, a safety assessment equation is constructed, making safety management work more scientific and systematic, which helps to discover and solve potential human risk factors, set monitoring rules, use construction monitoring videos to score each human cause, and obtain the current safety score according to the risk assessment equation. Such a real-time monitoring and scoring mechanism can timely discover safety hazards and prevent accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A schematic diagram of the basic process of an intelligent risk prevention and control method for highway construction provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0057] Example, see Figure 1 , as an embodiment of the present invention, provides an intelligent risk prevention and control method for highway construction, comprising the following steps:

[0058] Step S100: Acquire accident data, including accident location, accident type, accident time, and corresponding accident cause, and classify the accident cause corresponding to each accident type into natural cause and human cause;

[0059] Step S200: Select any accident location, obtain the accident type of the accident at the accident location caused by natural causes, obtain the accident time corresponding to the accident type, perform a first analysis on the accident time, and obtain a first risk prevention and control strategy based on the first analysis result;

[0060] Step S300: Count the number of times any human cause occurs at each accident site, record it as the second number, calculate the proportion of each human cause based on the second number, and construct a safety assessment equation based on the proportion of each human cause;

[0061] Step S400: Set monitoring rules for each human factor, obtain the current construction monitoring video, score each human factor in the current monitoring video according to the monitoring rules, and obtain the current safety score according to the risk assessment equation;

[0062] Step S500: Set a security score threshold, divide the current security level according to the security score threshold, and send an early warning signal according to the current security level.

[0063] The present invention records the accident location, type, time and corresponding cause of the accident in detail, and distinguishes the causes of the accident into natural causes and human causes, so as to more accurately analyze the accident data and provide accurate basic information for subsequent risk prevention and control. By counting the number of human causes and calculating the proportion, a safety assessment equation is constructed, making safety management work more scientific and systematic, which helps to discover and solve potential human risk factors, set monitoring rules, use construction monitoring videos to score each human cause, and obtain the current safety score according to the risk assessment equation. Such a real-time monitoring and scoring mechanism can timely discover safety hazards and prevent accidents.

[0064] The accident location is the province, city, district, or county where the accident occurred;

[0065] The accident time is expressed as the year and month when the accident occurred;

[0066] The types of accidents mentioned include collapse, object strike, fall from height, explosion and vehicle damage;

[0067] The causes of the collapse include continuous rainfall, faulty operations, lack of safety training, failure to set up emergency escape routes, and operational management errors;

[0068] The causes of object strike accidents include incorrect operation, lack of safety measures, lack of safety training and operational management errors;

[0069] Causes of falls from heights include extreme cold weather, lack of safety measures at work, lack of safety training, and operational management errors;

[0070] The causes of the explosion include incorrect operation, lack of safety training and operational management errors;

[0071] The cause of the vehicle injury accident was operational management error;

[0072] The cause of the accident is summarized based on expert experience. The continuous rainfall is represented by the weather in which the rainfall cycle exceeds the first day and the average daily rainfall exceeds a first value. The first day and the first value are obtained through historical experience, and are represented by values ​​that can make the ground humidity greater than the first humidity. The extremely cold weather is represented by the weather in which the temperature is lower than the first temperature and the air humidity is greater than the second value. The first temperature and the second value are obtained through historical experience, and are represented by values ​​that can make the ground friction less than the first friction.

[0073] The natural causes of the collapse include continuous rainfall, while the human causes include incorrect operation, lack of safety training, failure to set up emergency escape routes and operational management errors;

[0074] The natural cause of falls from heights is extreme cold weather, while the man-made causes of falls from heights include lack of safety measures at work, lack of safety training, and errors in work management;

[0075] Accidents caused by object impact, explosion and vehicle damage are all human factors.

[0076] In specific implementation, by refining the accident location to the province, city and district level, and accurately determining the accident time to the year and month, the high-risk areas and time periods where the accident occurred can be located more accurately, thereby achieving more targeted risk prevention and control. Differentiating the causes of accidents into natural causes and human causes will help to formulate different risk prevention and control strategies for these two types of causes, thereby improving the pertinence and effectiveness of prevention and control measures. For accidents caused by natural causes, such as collapse, object strikes, falls from heights, etc., by analyzing the accident time, risk prevention and control strategies related to specific weather conditions are obtained, such as the impact of continuous rainfall and extreme cold weather on construction safety, so that preventive measures can be taken in advance, monitoring rules can be set, and construction monitoring videos can be used to score various human causes in the current construction. The current safety score is obtained based on the risk assessment equation, real-time monitoring and dynamic early warning can be achieved, and safety hazards can be discovered and dealt with in a timely manner.

[0077] The first analysis method includes:

[0078] Select any accident location, obtain the accident type that occurred at the accident location, and set filtering conditions, including whether the accident type is collapse or fall from height, and whether the accident cause is continuous rainfall or extreme cold weather;

[0079] According to the screening conditions, the accident types occurring at the accident site are screened and recorded as the first accident. The accident time of the first accident is obtained, and the number of first accidents in each month whose accident time belongs to the first accident is counted in months, and recorded as the first number. The first number of extremely cold weather and the first number of continuous rainfall are sorted in descending order respectively, and the first number of extremely cold weather with the largest value and the first number of continuous rainfall with the largest value are selected, and the corresponding months are set as the extremely cold month and the continuous rainfall month.

[0080] The configuration method of the first risk prevention and control strategy includes:

[0081] Traverse the accident sites, obtain the first mapping relationship between the extremely cold month and the continuous rainy month corresponding to each accident site, and establish the first mapping relationship between the accident site and the extremely cold month and the continuous rainy month;

[0082] The current construction site is obtained, and the extremely cold months and continuous rainy months of the current construction site are obtained according to the first mapping relationship. The first risk prevention and control strategy is set according to the extremely cold months and continuous rainy months. The first risk prevention and control strategy includes:

[0083] Stop construction during extremely cold months and months with continuous rainfall, set up an electronic fence around the construction area, and place warning signs of the first size and first color around the electronic fence;

[0084] One month before the extreme cold month, the drainage system around the electric fence will be cleaned and unblocked, and the road sections around the electric fence that are prone to ice formation will be paved with sand;

[0085] Obtain the collapse range of the current construction site in a rainy month. The collapse range is obtained based on expert experience. A bounding box is set according to the degree of collapse. The electronic fence is contained in the bounding box. The bounding box represents the impact range of the collapse at the current construction site. In the month before the continuous rainy month, set a warning sign of the second size and second color around the bounding box.

[0086] The calculation method of the proportion of each human factor includes:

[0087] The number of times any human cause occurred at each accident site is counted, recorded as the second number, the total number of times each human cause occurred at each accident site is counted, recorded as the third number, and the ratio of the second number to the third number is calculated and set as the proportion of the human cause.

[0088] The calculation expression of the safety assessment equation is:

[0089] ;

[0090] in, For the safety assessment score, For the Man-made reasons, For the The proportion of human factors, is the number of types of human factors, y∈[0,100]. The larger the safety assessment score, the greater the degree of danger.

[0091] In specific implementation, by counting and analyzing the number of accidents under specific natural conditions (continuous rainfall and extreme cold weather), we can accurately identify months with high accident rates (extreme cold months and months with continuous rainfall), allowing for more stringent prevention and control measures to be taken during these months. By screening for two types of accidents, collapse and falls from height, we can develop more targeted risk prevention and control strategies, such as strengthening the design and maintenance of drainage systems during months with continuous rainfall and strengthening anti-slip and insulation measures during months with extreme cold. By accurately identifying high-risk months, we can optimize resource allocation, such as increasing the frequency of safety inspections and strengthening safety training for construction workers in high-risk months, thereby improving resource utilization efficiency. By defining specific numerical values ​​for continuous rainfall and extreme cold weather, we can better adapt to the climatic characteristics of different regions, implement environmental adaptability management, and enhance the construction process's ability to respond to extreme weather. By setting up electronic fences and warning signs to clearly define the boundaries of the construction area, we remind construction workers and passing vehicles to pay attention and reduce the risk of accidentally entering the construction area. One month before the extreme cold month, we will clean and unclog the drainage system and lay sand on icy roads to prevent accidents caused by icing in advance and improve construction site safety.

[0092] The methods for setting monitoring rules for various human factors include:

[0093] Obtain a current construction monitoring video, perform frame segmentation and windowing processing on the current construction monitoring video to obtain a current construction monitoring image, obtain an operating tool and its corresponding power, where the power is expressed as the average power during the operation, and wirelessly transmit the operating tool power to a monitoring terminal;

[0094] Retrieving a construction database, inputting the working tool into the construction database, matching a standard power corresponding to the working tool, and comparing the standard power with the average power;

[0095] When the standard power is greater than the power or when the standard power is less than the power, a difference between the power and the standard power is calculated, and an absolute value is taken to obtain a first value, the first value is set as an allowable error, the first value is compared with the first value, when the first value is greater than or equal to the first value, the score of the erroneous operation is set to the first score, otherwise, the score of the erroneous operation is set to the second score, when the standard power is equal to the average power, the score of the erroneous operation is set to a third score, wherein the third score is less than the second score, and the second score is less than the first score;

[0096] Taking the protective belt and the protective cap as the first key feature, calculating the first similarity between the first key feature and the current construction monitoring image using the cosine similarity formula, setting the second value as the first similarity threshold, and comparing the first similarity with the second value. When the first similarity is greater than or equal to the second value, it indicates that the corresponding first key feature exists in the current construction monitoring image; when the first similarity is less than the second value, it indicates that the corresponding first key feature does not exist in the current construction monitoring image;

[0097] Traversing each current construction monitoring image, when the protective belt and the protective cap appear simultaneously in any current construction monitoring image, setting the score for lack of work safety measures to a fourth score; when the protective belt and the protective cap do not appear simultaneously in any current construction monitoring image, and the protective belt or the protective cap does not appear in any current construction monitoring image, setting the score for lack of work safety measures to a fifth score; when the protective belt or the protective cap appears in any current construction monitoring image, and the protective belt and the protective cap do not appear simultaneously in any current construction monitoring image, setting the score for lack of work safety measures to a sixth score, wherein the fourth score is less than the sixth score, and the sixth score is less than the fifth score;

[0098] Setting the escape route as the second key feature, calculating a second similarity between the second key feature and the current construction monitoring image using a cosine similarity formula, comparing the second similarity with a second value, and when the second similarity is greater than or equal to the second value, setting the score of not having an emergency escape route set to a seventh score; otherwise, setting the score of not having an emergency escape route set to an eighth score, where the eighth score is greater than the seventh score;

[0099] The safety administrator is set as the third key feature, a third similarity between the third key feature and the current construction monitoring image is calculated using a cosine similarity formula, the third similarity is compared with the second value, and when the second similarity is greater than or equal to the third value, the score for the operation management error is set to the ninth score; otherwise, the score for not setting up an emergency escape route is set to the tenth score;

[0100] Obtain the number of personnel training certificates, count the number of people in the surveillance video, calculate the ratio of the number of people in the surveillance video to the number of personnel training certificates, and record it as a first ratio. When the first ratio is greater than 0.8, set the score for lack of safety training to the eleventh score; otherwise, set the score for lack of safety training to the twelfth score, where the twelfth score is greater than the eleventh score.

[0101] During the specific implementation, by acquiring construction monitoring videos in real time and performing frame processing, the situation at the construction site is monitored in real time, and potential safety hazards are discovered in a timely manner. By comparing the actual power and standard power of the operating tools, abnormal situations during the operation process, such as equipment failure or improper operation, are discovered in a timely manner. By identifying key features such as protective belts, protective helmets, and escape routes, it is ensured that construction personnel comply with safety regulations and reduce accidents caused by lack of safety measures. By ensuring that construction personnel comply with safety regulations and receive safety training, construction quality is improved and project quality problems caused by improper operation are reduced. Through quantitative evaluation, safety management resources are allocated more reasonably and resource utilization efficiency is improved.

[0102] Obtaining a score for each human cause, calculating the sum of the scores for each human cause and recording it as the total score, calculating the ratio of the score for each human cause to the total score, setting the ratio of the score for the human cause to the total score as the proportion of the corresponding human cause, setting 100 as the full score, calculating the product of the full score and the proportion, setting the product of the full score and the proportion as the actual score of the corresponding human cause, substituting each actual score into the safety assessment equation to obtain a safety assessment score, and setting the third value and the fourth value as the safety score threshold, wherein the third value is less than the fourth value;

[0103] The current security level classification methods include:

[0104] comparing the safety assessment score with the safety score threshold; when the safety assessment score is less than or equal to a third value, setting the current safety level to the first level; when the safety assessment score is greater than the third value and less than or equal to a fourth value, setting the current safety level to the second level; and when the safety assessment score is greater than the fourth value, setting the current safety level to the third level, wherein the first level, the second level, and the third level represent the degree of danger in descending order;

[0105] When the current safety level is the first level, a signal light of the first color and the first brightness is displayed, and the actual score of each human cause is displayed. When the current safety level is the second level, a signal light of the second color and the second brightness is displayed, and the actual score of each human cause is displayed. When the current safety level is the third level, a signal light of the third color and the third brightness is displayed, and the actual score of each human cause is displayed.

[0106] In specific implementation, by calculating the scores and total scores of each human cause, the safety risks in the construction process are quantified, providing quantitative data support for safety management. By calculating the ratio of the scores of each human cause to the total score, the impact of different human causes on construction safety is analyzed to help identify the main risk factors. By setting a safety score threshold, the safety assessment score is compared with the safety score threshold, the current safety level is divided, and risk warning and hierarchical management are achieved. By displaying the actual score of each human cause, construction personnel and managers are helped to understand the current main risk factors and take targeted improvement measures.

[0107] The present invention records the accident location, type, time and corresponding cause of the accident in detail, and distinguishes the causes of the accident into natural causes and human causes, so as to more accurately analyze the accident data and provide accurate basic information for subsequent risk prevention and control. By counting the number of human causes and calculating the proportion, a safety assessment equation is constructed, making safety management work more scientific and systematic, which helps to discover and solve potential human risk factors, set monitoring rules, use construction monitoring videos to score each human cause, and obtain the current safety score according to the risk assessment equation. Such a real-time monitoring and scoring mechanism can timely discover safety hazards and prevent accidents.

[0108] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium may be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0109] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that modifications or equivalent replacements of the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention should be included in the scope of the claims of the present invention.

Claims

1. An intelligent risk prevention and control method for highway construction, characterized in that: The following steps are involved: Step S100: Acquire accident data, including accident location, accident type, accident time, and corresponding accident cause, and classify the accident cause corresponding to each accident type into natural cause and human cause; Step S200: Select any accident location, obtain the accident type of the accident at the accident location caused by natural causes, obtain the accident time corresponding to the accident type, perform a first analysis on the accident time, and obtain a first risk prevention and control strategy based on the first analysis result; Step S300: Count the number of times any human cause occurs at each accident site, record it as the second number, calculate the proportion of each human cause based on the second number, and construct a safety assessment equation based on the proportion of each human cause; Step S400: Set monitoring rules for each human factor, obtain the current construction monitoring video, score each human factor in the current monitoring video according to the monitoring rules, and obtain the current safety score according to the risk assessment equation; Step S500: Set a security score threshold, divide the current security level according to the security score threshold, and send an early warning signal according to the current security level.

2. The intelligent risk prevention and control method for highway construction according to claim 1, characterized in that: The accident location is the province, city, district, or county where the accident occurred; The accident time is expressed as the year and month when the accident occurred; The types of accidents mentioned include collapse, object strike, fall from height, explosion and vehicle damage; The causes of the collapse include continuous rainfall, faulty operations, lack of safety training, failure to set up emergency escape routes, and operational management errors; The causes of object strike accidents include incorrect operation, lack of safety measures, lack of safety training and operational management errors; Causes of falls from heights include extreme cold weather, lack of safety measures at work, lack of safety training, and operational management errors; The causes of the explosion include incorrect operation, lack of safety training and operational management errors; The cause of the vehicle injury accident was operational management error; The cause of the accident is summarized based on expert experience. The continuous rainfall is represented by the weather in which the rainfall cycle exceeds the first day and the average daily rainfall exceeds a first value. The first day and the first value are obtained through historical experience, and are represented by values ​​that can make the ground humidity greater than the first humidity. The extremely cold weather is represented by the weather in which the temperature is lower than the first temperature and the air humidity is greater than the second value. The first temperature and the second value are obtained through historical experience, and are represented by values ​​that can make the ground friction less than the first friction.

3. The intelligent risk prevention and control method for highway construction according to claim 1, characterized in that: The natural causes of the collapse include continuous rainfall, while the human causes include incorrect operation, lack of safety training, failure to set up emergency escape routes and operational management errors; The natural cause of falls from heights is extreme cold weather, while the man-made causes of falls from heights include lack of safety measures at work, lack of safety training, and errors in work management; Accidents caused by object impact, explosion and vehicle damage are all human factors.

4. The intelligent risk prevention and control method for highway construction according to claim 1, characterized in that: The first analysis method includes: Select any accident location, obtain the accident type that occurred at the accident location, and set filtering conditions, including whether the accident type is collapse or fall from height, and whether the accident cause is continuous rainfall or extreme cold weather; According to the screening conditions, the accident types occurring at the accident site are screened and recorded as the first accident. The accident time of the first accident is obtained, and the number of first accidents in each month whose accident time belongs to the first accident is counted in months, and recorded as the first number. The first number of extremely cold weather and the first number of continuous rainfall are sorted in descending order respectively, and the first number of extremely cold weather with the largest value and the first number of continuous rainfall with the largest value are selected, and the corresponding months are set as the extremely cold month and the continuous rainfall month.

5. The intelligent risk prevention and control method for highway construction according to claim 1, characterized in that: The configuration method of the first risk prevention and control strategy includes: Traverse the accident sites, obtain the first mapping relationship between the extremely cold month and the continuous rainy month corresponding to each accident site, and establish the first mapping relationship between the accident site and the extremely cold month and the continuous rainy month; The current construction site is obtained, and the extremely cold months and continuous rainy months of the current construction site are obtained according to the first mapping relationship. The first risk prevention and control strategy is set according to the extremely cold months and continuous rainy months. The first risk prevention and control strategy includes: Stop construction during extremely cold months and months with continuous rainfall, set up an electronic fence around the construction area, and place warning signs of the first size and first color around the electronic fence; One month before the extreme cold month, the drainage system around the electric fence will be cleaned and unblocked, and the road sections around the electric fence that are prone to ice formation will be paved with sand; Obtain the collapse range of the current construction site in a rainy month. The collapse range is obtained based on expert experience. A bounding box is set according to the degree of collapse. The electronic fence is contained in the bounding box. The bounding box represents the impact range of the collapse at the current construction site. In the month before the continuous rainy month, set a warning sign of the second size and second color around the bounding box.

6. The intelligent risk prevention and control method for highway construction according to claim 1, characterized in that: The calculation method of the proportion of each human factor includes: The number of times any human cause occurred at each accident site is counted, recorded as the second number, the total number of times each human cause occurred at each accident site is counted, recorded as the third number, and the ratio of the second number to the third number is calculated and set as the proportion of the human cause.

7. The intelligent risk prevention and control method for highway construction according to claim 1, characterized in that: The calculation expression of the safety assessment equation is: ； in, For the safety assessment score, For the Man-made reasons, For the The proportion of human factors, is the number of types of human factors, y∈[0,100]. The larger the safety assessment score, the greater the degree of danger.

8. The intelligent risk prevention and control method for highway construction according to claim 2, characterized in that: The methods for setting monitoring rules for various human factors include: Obtain a current construction monitoring video, perform frame segmentation and windowing processing on the current construction monitoring video to obtain a current construction monitoring image, obtain an operating tool and its corresponding power, where the power is expressed as the average power during the operation, and wirelessly transmit the operating tool power to a monitoring terminal; Retrieving a construction database, inputting the working tool into the construction database, matching a standard power corresponding to the working tool, and comparing the standard power with the average power; When the standard power is greater than the power or when the standard power is less than the power, a difference between the power and the standard power is calculated, and an absolute value is taken to obtain a first value, the first value is set as an allowable error, the first value is compared with the first value, when the first value is greater than or equal to the first value, the score of the erroneous operation is set to the first score, otherwise, the score of the erroneous operation is set to the second score, when the standard power is equal to the average power, the score of the erroneous operation is set to a third score, wherein the third score is less than the second score, and the second score is less than the first score; Taking the protective belt and the protective cap as the first key feature, calculating the first similarity between the first key feature and the current construction monitoring image using the cosine similarity formula, setting the second value as the first similarity threshold, and comparing the first similarity with the second value. When the first similarity is greater than or equal to the second value, it indicates that the corresponding first key feature exists in the current construction monitoring image; when the first similarity is less than the second value, it indicates that the corresponding first key feature does not exist in the current construction monitoring image; Traversing each current construction monitoring image, when the protective belt and the protective cap appear simultaneously in any current construction monitoring image, setting the score for lack of work safety measures to a fourth score; when the protective belt and the protective cap do not appear simultaneously in any current construction monitoring image, and the protective belt or the protective cap does not appear in any current construction monitoring image, setting the score for lack of work safety measures to a fifth score; when the protective belt or the protective cap appears in any current construction monitoring image, and the protective belt and the protective cap do not appear simultaneously in any current construction monitoring image, setting the score for lack of work safety measures to a sixth score, wherein the fourth score is less than the sixth score, and the sixth score is less than the fifth score; Setting the escape route as the second key feature, calculating a second similarity between the second key feature and the current construction monitoring image using a cosine similarity formula, comparing the second similarity with a second value, and when the second similarity is greater than or equal to the second value, setting the score of not having an emergency escape route set to a seventh score; otherwise, setting the score of not having an emergency escape route set to an eighth score, where the eighth score is greater than the seventh score; The safety administrator is set as the third key feature, a third similarity between the third key feature and the current construction monitoring image is calculated using a cosine similarity formula, the third similarity is compared with the second value, and when the second similarity is greater than or equal to the third value, the score for the operation management error is set to the ninth score; otherwise, the score for not setting up an emergency escape route is set to the tenth score; Obtain the number of personnel training certificates, count the number of people in the surveillance video, calculate the ratio of the number of people in the surveillance video to the number of personnel training certificates, and record it as a first ratio. When the first ratio is greater than 0.8, set the score for lack of safety training to the eleventh score; otherwise, set the score for lack of safety training to the twelfth score, where the twelfth score is greater than the eleventh score.

9. The intelligent risk prevention and control method for highway construction according to claim 1, characterized in that: Obtaining a score for each human cause, calculating the sum of the scores for each human cause and recording it as the total score, calculating the ratio of the score for each human cause to the total score, setting the ratio of the score for the human cause to the total score as the proportion of the corresponding human cause, setting 100 as the full score, calculating the product of the full score and the proportion, setting the product of the full score and the proportion as the actual score of the corresponding human cause, substituting each actual score into the safety assessment equation to obtain a safety assessment score, and setting the third value and the fourth value as the safety score threshold, wherein the third value is less than the fourth value; The current security level classification methods include: comparing the safety assessment score with the safety score threshold; when the safety assessment score is less than or equal to a third value, setting the current safety level to the first level; when the safety assessment score is greater than the third value and less than or equal to a fourth value, setting the current safety level to the second level; and when the safety assessment score is greater than the fourth value, setting the current safety level to the third level, wherein the first level, the second level, and the third level represent the degree of danger in descending order; When the current safety level is the first level, a signal light of the first color and the first brightness is displayed, and the actual score of each human cause is displayed. When the current safety level is the second level, a signal light of the second color and the second brightness is displayed, and the actual score of each human cause is displayed. When the current safety level is the third level, a signal light of the third color and the third brightness is displayed, and the actual score of each human cause is displayed.

10. An intelligent risk prevention and control system for highway construction, the system being used to execute the intelligent risk prevention and control method for highway construction according to claim 1, characterized in that: Including collection module, analysis module and early warning module; The acquisition module acquires accident data, including accident location, accident type, accident time, and corresponding accident cause, and classifies the accident cause corresponding to each accident type into natural cause and man-made cause; The analysis module selects any accident location, obtains the accident type of the accident at the accident location where the cause is natural cause, obtains the accident time corresponding to the accident type, performs a first analysis on the accident time, obtains a first risk prevention and control strategy based on the first analysis result, counts the number of any human cause occurring at each accident location, records it as a second number, calculates the proportion of each human cause based on the second number, constructs a safety assessment equation based on the proportion of each human cause, sets monitoring rules for each human cause, obtains the current construction monitoring video, scores each human cause in the current monitoring video based on the monitoring rules, and obtains the current safety score based on the risk assessment equation; The early warning module sets a security score threshold, divides the current security level according to the security score threshold, and sends an early warning signal according to the current security level.

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