System for improving supervision management efficiency

Abstract

The invention provides a system for improving supervision management efficiency, and the system comprises an on-site monitoring module which is used for supervising the construction progress and safety construction through an edge algorithm, and transmitting supervision data to a server for processing; the server is used for constructing a construction progress information base and a constructor information base, receiving the real-time supervision data acquired by the field monitoring module, intelligently scheduling constructors and interacting with the mobile terminal; and the mobile terminal is used for interacting with the server, a manager obtains the real-time information of the construction site and processes the constructor scheduling instruction request sent by the server, and the constructor receives the scheduling instruction of the server and feeds back the construction progress to the server. According to the invention, on the basis of guaranteeing the personal safety of the constructors, the scheduling scheme of the constructors is dynamically adjusted according to the actual progress condition of the construction project.

Description

Technical Field

[0001] The present invention relates to the technical field of supervision management, and in particular to a system for improving supervision management efficiency. Background Art

[0002] More and more supervision companies are pursuing more efficient and high-quality project management. At present, different construction instructions are issued to construction personnel through verbal instructions during the construction process, which makes the construction management chaotic and unable to form a complete closed loop from the source to the execution. It is also difficult to trace the supervision personnel when problems occur during the construction process. In addition, during the project acceptance stage, supervision is often uploaded in the form of paper documents, and the data visualization performance is low. Management personnel cannot quickly find the project information they want to check, which greatly affects the efficiency of work.

[0003] At present, most aspects of supervision rely on human management, and the degree of intelligence is not enough. When some supervisors are not strong enough in supervision and have poor execution, it is easy to cause problems such as irregular construction operations and the quality of some projects cannot be guaranteed. In addition, due to the lack of intelligence in risk management at the construction site, it is easy for construction workers to fail to obtain danger alerts in time and avoid risks in time. At the same time, the lack of effective communication and coordination mechanisms may lead to misunderstandings and conflicts between the parties, thus affecting the smooth progress of the project. Therefore, how to improve the intelligence of construction site supervision and provide effective emergency plans has become an urgent problem to be solved in the current engineering construction supervision. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a system for improving the efficiency of supervision management, which, on the basis of ensuring the personal safety of construction personnel, realizes dynamic adjustment of the scheduling plan for construction personnel according to the actual progress of the construction project.

[0005] To achieve the above-mentioned object of the invention, the present invention provides a system for improving supervision management efficiency, the system comprising:

[0006] On-site monitoring module, which is used to monitor construction progress and safety through edge algorithms and transmit the monitoring data to the server for processing;

[0007] The server is used to build a construction progress information database and a construction personnel information database, receive real-time supervision data collected by the on-site monitoring module, perform intelligent scheduling of construction personnel, and interact with the mobile terminal;

[0008] The mobile terminal is used to interact with the server. The management personnel obtain the real-time information of the construction site and process the construction personnel scheduling instruction requests sent by the server. The construction personnel receive the scheduling instructions from the server and feedback the construction progress to the server.

[0009] Furthermore, the on-site monitoring module includes:

[0010] Video monitoring unit, used to collect construction images of the construction site through panoramic cameras;

[0011] The status monitoring unit is used to collect the working status information and identity information of the construction personnel and is connected with the video monitoring unit signal;

[0012] The safety assessment unit is used to integrate the construction images of the video monitoring unit and the work status information of the construction personnel in the corresponding construction images to assess the safety status of the current construction site;

[0013] The progress assessment unit is used to conduct progress assessment on the construction site in the construction image by combining the construction progress information database and the construction progress feedback from the construction personnel.

[0014] Furthermore, the safety monitoring unit includes a smart safety helmet, which includes a camera, a Bluetooth tag, a voice broadcast subunit, a control main board and a power supply. The camera, Bluetooth tag, voice broadcast subunit and control main board are electrically connected to the power supply respectively. The camera is electrically connected to the control main board for collecting work status information of construction personnel and identifying identity information of construction personnel. The Bluetooth module is electrically connected to the control main board for locating the construction site of the construction personnel. The voice broadcast subunit is electrically connected to the control main board for broadcasting feedback instructions of the safety assessment unit. The control main board is connected to the panoramic camera signal.

[0015] Furthermore, the security assessment unit is specifically used to perform the following operations:

[0016] S11. Collect data from historical construction safety cases, build a safety assessment model for the construction site through a neural network, and determine dangerous construction behaviors and hazard sources based on the safety assessment model;

[0017] S12, input the construction image into the YOLOV8 model to identify the borders of the hazard source and the construction personnel, and generate corresponding boundary coordinate sets based on the boundary boxes;

[0018] S13, arranging the corresponding boundary coordinate sets of the construction personnel's trajectories into a first sequence in chronological order, and inputting them into BiLSTM to predict and quantify the future trajectories of the construction personnel, thereby obtaining a first prediction vector;

[0019] S14, arranging the corresponding boundary coordinate sets of the hazard source trajectory into a second sequence in chronological order, and inputting the second sequence into BiLSTM to predict and quantify the future trajectory of the hazard source, thereby obtaining a second prediction vector;

[0020] S15. The working status information of the construction personnel, the first prediction vector and the second prediction vector are simultaneously input into the safety assessment model, and if the output prediction result exceeds the risk threshold, a warning instruction is generated.

[0021] Furthermore, if the output prediction result exceeds the risk threshold, a warning instruction is generated, including:

[0022] S21, the safety assessment model outputs the individual risk level of the construction personnel and the scenario risk level of the construction site, as well as a comprehensive risk level integrating the individual risk level and the scenario risk level;

[0023] S22. When the scene risk level exceeds the preset scene safety threshold, a first-level risk instruction is generated, and a voice reminder is given to the construction workers at the corresponding construction site through the smart safety helmet;

[0024] S23. When the personal risk level exceeds the preset personal safety threshold, a secondary risk instruction is generated, and a voice reminder is given to the corresponding construction personnel through the smart safety helmet;

[0025] S24. When the comprehensive risk level exceeds the preset comprehensive safety threshold, a third-level risk instruction is generated, and voice reminders are given to all construction workers through smart safety helmets.

[0026] Furthermore, the progress evaluation unit is specifically configured to perform the following operations:

[0027] S31. Generate standard progress information of different construction stages of each construction site based on the construction progress information database, input the standard progress information into machine learning for training, and obtain a construction progress evaluation model;

[0028] S32. When the construction personnel provide feedback on the construction progress, the construction images at the same time are captured and input into the construction progress assessment model for recognition to obtain real-time construction progress feedback;

[0029] S33, comparing the real-time construction progress feedback with the construction progress feedback from the construction personnel, and if they match, comparing the real-time construction progress feedback with the standard progress information, and if they match, feeding back the real-time construction progress to the mobile terminal, and if they do not match, feeding back the real-time construction progress to the server;

[0030] S34. If the real-time construction progress feedback does not match the construction progress feedback from the construction personnel, a progress confirmation instruction is fed back to the mobile terminal manager, and then step S33 is executed.

[0031] Furthermore, a construction progress information database is constructed, including:

[0032] S41, collecting construction project information and generating a construction project information database;

[0033] S42. Based on the construction project information database, a visual BIM three-dimensional model of the construction project is constructed based on BIM technology;

[0034] S43, mapping the three-dimensional terrain data of the construction site with the construction image, building a construction progress information database, and updating the construction progress information database in real time through a progress evaluation unit.

[0035] Furthermore, a construction personnel information database is constructed, including:

[0036] S51, collecting the real-name information of all construction personnel and generating a basic information database of construction personnel;

[0037] S52, updating the basic information database in real time through a status monitoring unit to build a real-time status information database;

[0038] S53: updating the real-time status information database through the safety assessment unit to build a construction personnel information database.

[0039] Furthermore, the real-time monitoring data collected by the on-site monitoring module is received to intelligently dispatch the construction personnel, including:

[0040] S61, subtracting the real-time construction progress feedback received from the progress assessment unit transmission unit from the standard progress information to obtain the remaining construction progress;

[0041] S62, encoding the start time, duration and required construction personnel of the remaining construction progress into a character string;

[0042] S63, based on the code string in step S62, randomly select two parent codes to perform a crossover operation to obtain a new child code, and use the new child code as the search space;

[0043] S64, randomly selecting a child code, performing a mutation operation on the child code and dynamically adjusting the construction plan;

[0044] S65. A fitness function is constructed with the goal of minimizing construction period and cost while maximizing quality, and weight coefficients are introduced respectively to guide the genetic algorithm to search for the optimal scheduling solution, generate scheduling instructions and send them to the mobile terminal for confirmation.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The present invention provides a system for improving the efficiency of supervision management. The present invention integrates the edge algorithm into the on-site monitoring module to realize the supervision of construction progress and safe construction. The server uses a genetic algorithm to combine the real-time data fed back by the on-site monitoring module with the real-time updated construction progress information database and construction personnel information database to generate the optimal scheduling plan for the construction personnel. The management personnel can monitor the construction site around the clock through the mobile terminal. The present invention not only ensures the personal safety of the construction personnel, but also realizes the dynamic adjustment of the construction personnel according to the actual progress of the construction project. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0048] Figure 1 A schematic diagram of the structure of a system for improving supervision management efficiency provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0050] Reference Figure 1 , a system for improving supervision management efficiency, the system comprising:

[0051] The on-site monitoring module is used to monitor the construction progress and safe construction through edge algorithms, and transmit the supervision data to the server for processing.

[0052] It should be noted that the integration of edge algorithms into the on-site monitoring module can timely process and analyze the collected data to prevent data loss during transmission. For example, by analyzing the image data collected by the panoramic camera, the construction status of the equipment at the construction site can be monitored in real time, so as to timely discover and solve problems. At the same time, the data can be analyzed to predict future trends and risks. By integrating edge algorithms, the on-site monitoring module can automatically issue instructions to control the construction site based on the analysis results. For example, when it is detected that the construction environment or the working status of the construction personnel does not meet the construction standards, the smart safety helmet is issued with a reminder instruction to warn the on-site construction personnel to ensure their personal safety. The supervision data is transmitted to the server for storage and archiving for further analysis. In the actual construction process, the deployment of personnel is essential. The server performs intelligent analysis of the on-site supervision data and dynamically dispatches the construction personnel to ensure smooth completion within the construction period.

[0053] As a preferred embodiment, the on-site monitoring module includes:

[0054] The video monitoring unit is used to collect construction images of the construction site through a panoramic camera.

[0055] The status monitoring unit is used to collect the working status information and identity information of the construction personnel and is connected to the signal of the video monitoring unit.

[0056] The safety assessment unit is used to integrate the construction images of the video surveillance unit and the work status information of the construction personnel in the corresponding construction images to assess the safety status of the current construction site.

[0057] The progress assessment unit is used to conduct progress assessment on the construction site in the construction image by combining the construction progress information database and the construction progress feedback from the construction personnel.

[0058] It should be noted that the video monitoring unit collects images of the construction site through a panoramic camera, so as to identify the danger sources and construction workers in the scene images for the subsequent image recognition algorithm. The state monitoring unit, through the monitoring equipment, recognizes the facial images of the construction workers through the smart safety helmet in this embodiment, obtains the working status and identity information of the construction workers, and at the same time, the video monitoring unit and the state monitoring unit are connected by signal. When the construction workers are under the panoramic camera of a construction site, the monitoring equipment of the state monitoring unit recognizes the identity information of the construction workers and binds it with the panoramic camera of the construction site. When the management personnel need to find the construction workers, they can quickly locate the construction site without checking the images one by one, which improves the management personnel's supervision efficiency.

[0059] The safety assessment unit and progress assessment unit are integrated with edge algorithms to analyze the data collected by the video surveillance unit and the status monitoring unit in real time. The safety assessment unit collects and analyzes historical construction accident cases to assess whether a safety accident will occur at the current construction site, and promptly issues early warnings to construction personnel through the status monitoring unit to prevent construction accidents and ensure the personal safety of construction personnel. The progress assessment unit collects and analyzes the construction site images uploaded by construction personnel at the same time of the construction progress, assesses the actual construction progress, and is reviewed by management personnel, doubly ensuring the monitoring of the construction progress and improving the efficiency of supervision of the construction progress.

[0060] The safety monitoring unit includes a smart safety helmet, which includes a camera, a Bluetooth tag, a voice broadcast subunit, a control mainboard and a power supply. The camera, the Bluetooth tag, the voice broadcast subunit and the control mainboard are electrically connected to the power supply respectively. The camera is electrically connected to the control mainboard for collecting the work status information of the construction personnel and identifying the identity information of the construction personnel. The Bluetooth module is electrically connected to the control mainboard for locating the construction site of the construction personnel. The voice broadcast subunit is electrically connected to the control mainboard for broadcasting the feedback instructions of the safety assessment unit. The control mainboard is connected to the panoramic camera signal.

[0061] In this embodiment, the safety monitoring unit uses a smart helmet to monitor the working status of the construction workers. On the basis of ensuring the standard dress of the construction workers, the smart helmet integrates a camera, a Bluetooth tag and a voice broadcast subunit, wherein the camera analyzes the facial image of the construction workers, including but not limited to identifying the fatigue degree and identity information of the construction workers, that is, analyzing the number of yawns, eye blinking frequency, and whether the eyes are focused, etc. of the construction workers. The analysis method can adopt the existing detection algorithm on the market, which will not be explained here. The Bluetooth tag is connected to the panoramic camera signal through the main control module to bind the construction workers to the construction site, so that the management personnel can quickly locate the construction site where the construction workers are located. Assuming that when the construction workers move from construction site No. 1 to construction site No. 2, the Bluetooth tag of the smart helmet worn by the construction workers is connected to the panoramic camera of construction site No. 2, and the management personnel can quickly locate that the construction workers are at construction site No. 2. The voice broadcast subunit voice broadcasts the evaluation results of the safety assessment unit to the corresponding construction workers to ensure the personal safety of the construction workers and improve the supervision efficiency of the management personnel.

[0062] As a preferred embodiment, the security assessment unit is specifically used to perform the following operations:

[0063] S11. Collect data from historical construction safety cases, build a safety assessment model for the construction site through a neural network, and determine dangerous construction behaviors and hazard sources based on the safety assessment model;

[0064] S12, input the construction image into the YOLOV8 model to identify the borders of the hazard source and the construction personnel, and generate corresponding boundary coordinate sets based on the boundary boxes;

[0065] S13, arranging the corresponding boundary coordinate sets of the construction personnel's trajectories into a first sequence in chronological order, and inputting them into BiLSTM to predict and quantify the future trajectories of the construction personnel, thereby obtaining a first prediction vector;

[0066] S14, arranging the corresponding boundary coordinate sets of the hazard source trajectory into a second sequence in chronological order, and inputting the second sequence into BiLSTM to predict and quantify the future trajectory of the hazard source, thereby obtaining a second prediction vector;

[0067] S15. The working status information of the construction personnel, the first prediction vector and the second prediction vector are simultaneously input into the safety assessment model, and if the output prediction result exceeds the risk threshold, a warning instruction is generated.

[0068] To conduct a safety assessment on the construction site, it is first necessary to conduct an in-depth analysis of the safety accidents that have occurred in history, explore the correlation between the precursor information of construction dangers and the types of accidents, and provide an effective early warning mechanism for building safety. That is, this embodiment conducts an in-depth analysis of the safety accidents that have occurred in history through a neural network, constructs a safety assessment model for the construction site, and determines dangerous construction behaviors and sources of danger. It can be understood that the present invention is not limited to the in-depth analysis of the safety accidents that have occurred in history through a neural network, and all algorithms that can realize the analysis function are applicable. Before the safety assessment model conducts a safety assessment on the construction site, it is necessary to finely process the images collected by the panoramic camera to improve the accuracy of the safety assessment model. First, the YOLOV8 model is used to identify the borders of the sources of danger and construction personnel, and the personal risks and scene risks of the construction site are judged respectively. At the same time, the personal risks and scene risks are integrated to judge the safety of the entire construction site, where personal risks include but are not limited to the fatigue of construction personnel exceeding the work standard, and rest and adjustment are required; scene risks include but are not limited to the stacking of materials exceeding the specified height; the fusion of personal risks and scene risks includes but is not limited to construction personnel standing under the hoisted objects.

[0069] By identifying the borders of the hazard source and the construction worker, and generating the corresponding boundary coordinate sets based on the boundary boxes, the location information of the hazard source and the construction worker is quantified, and the trajectory is combined into a sequence of the corresponding boundary coordinate sets in chronological order. The boundary coordinates provide complete information about the edges of the hazard source and the construction worker. For example, when the hazard source and the construction worker come into contact, the edge contacts first. This setting avoids the phenomenon of untimely evaluation caused by using only the center coordinates. The trajectory of the composed sequence is predicted by BiLSTM. The bidirectional characteristics of the BiLSTM model can consider both historical and future trajectory information, which improves the accuracy of trajectory prediction for construction workers and hazard sources. The safety assessment model comprehensively considers the future trajectory of construction workers and hazard sources and the working status information of construction workers. If the prediction results are output, an early warning instruction is generated to improve the efficiency of safety monitoring of the construction site and ensure the personal safety of construction workers.

[0070] If the output prediction result exceeds the risk threshold, a warning instruction is generated, including:

[0071] S21. The safety assessment model outputs the individual risk level of the construction personnel and the scenario risk level of the construction site, as well as a comprehensive risk level that integrates the individual risk level and the scenario risk level.

[0072] S22. When the scene risk level exceeds the preset scene safety threshold, a first-level risk instruction is generated, and a voice reminder is given to the construction workers at the corresponding construction site through the smart safety helmet.

[0073] S23. When the personal risk level exceeds the preset personal safety threshold, a secondary risk instruction is generated, and a voice reminder is given to the corresponding construction personnel through the smart safety helmet.

[0074] S24. When the comprehensive risk level exceeds the preset comprehensive safety threshold, a third-level risk instruction is generated, and voice reminders are given to all construction workers through smart safety helmets.

[0075] In this embodiment, the early warning system can help managers manage the construction site more effectively and reduce construction delays caused by safety issues. By comparing the prediction results with the risk threshold, possible dangerous situations can be identified in advance, so that preventive measures can be taken to avoid accidents. Level 1 risk instructions include but are not limited to failure to set up a safety net around the construction site, that is, the scene risk level exceeds the threshold, and a voice reminder to set up a safety net is given to the construction personnel through the smart safety helmet to prevent safety accidents. Level 2 risk instructions include but are not limited to construction personnel’s fatigue level exceeding the work standard, that is, the personal risk level exceeds the threshold, and a voice reminder to the construction personnel to leave work is given through the smart safety helmet. Level 3 risk instructions include but are not limited to standing under the hoisted object, that is, the comprehensive risk level exceeds the threshold, and a voice reminder to the construction personnel to avoid the transported object is given through the smart safety helmet.

[0076] As a preferred embodiment, the progress evaluation unit is specifically configured to perform the following operations:

[0077] S31. Generate standard progress information for different construction stages of each construction site based on the construction progress information database, input the standard progress information into machine learning for training, and obtain a construction progress evaluation model.

[0078] S32. When the construction workers provide feedback on the construction progress, the construction images at the same time are captured and input into the construction progress evaluation model for identification to obtain real-time construction progress feedback.

[0079] S33. Compare the real-time construction progress feedback with the construction progress feedback from the construction personnel. If they match, compare the real-time construction progress feedback with the standard progress information. If they match, feedback the real-time construction progress to the mobile terminal. If they do not match, feedback the real-time construction progress to the server.

[0080] S34. If the real-time construction progress feedback does not match the construction progress feedback from the construction personnel, a progress confirmation instruction is fed back to the mobile terminal manager, and then step S33 is executed.

[0081] In this embodiment, a machine learning model is used to analyze historical data, learn the time and logical relationship between different construction activities, so as to divide the construction progress information base more accurately and obtain a construction progress evaluation model. The construction progress evaluation model can help managers to understand the project progress in a timely manner, quickly respond to progress deviations, and improve the efficiency and effectiveness of project management. At the same time, the progress evaluation unit updates the construction progress information base in real time to ensure that the construction progress evaluation model can make predictions based on the latest data. When the construction personnel feedback the construction progress, that is, when a certain stage or the construction is completed on the day, in order to prevent the construction personnel from reporting inaccurately, the panoramic camera collects reports and submits the construction site images at the same time for analysis to see if the progress of the two is consistent. At the same time, the management personnel conduct an audit to double guarantee the correct reporting of the construction progress.

[0082] The server is used to build a construction progress information database and a construction personnel information database, receive real-time supervision data collected by the on-site monitoring module, intelligently schedule construction personnel, and interact with the mobile terminal. In this embodiment, after the server builds the basic construction progress information database and the construction personnel information database, the monitoring data transmitted by the on-site monitoring module are used to update the construction progress information database and the construction personnel information database in real time, providing an information source for the intelligent scheduling algorithm.

[0083] Build a construction progress information database, including:

[0084] S41. Collect construction project information and generate a construction project information database.

[0085] S42. According to the construction project information database, a visual BIM three-dimensional model of the construction project is constructed based on BIM technology.

[0086] S43, mapping the three-dimensional terrain data of the construction site with the construction image, building a construction progress information database, and updating the construction progress information database in real time through a progress evaluation unit.

[0087] In this embodiment, through the generated construction progress information database, the standardization and shared management of project information can be realized, and the progress of the project can be dynamically mastered. BIM technology can help construction projects establish three-dimensional visual construction models, so that all project participants can intuitively understand the situation of the construction site, which is convenient for resource scheduling and optimization during the construction process. By mapping the three-dimensional terrain data of the construction site with the construction image, the changes in the construction site can be immediately reflected in the model, which is convenient for managers to adjust the construction plan in time, effectively monitor the construction quality, and ensure that each link meets the design requirements and quality standards. Building a construction progress information database can provide comprehensive, real-time and accurate data support for construction projects, improve project management efficiency, optimize resource allocation, improve construction quality and safety, strengthen risk management, support data-driven decision-making, improve project transparency, and support remote monitoring and management, thereby improving the execution efficiency and quality of the entire construction project.

[0088] Build a construction personnel information database, including:

[0089] S51. Collect the real-name information of all construction workers and generate a basic information database for the construction workers.

[0090] S52: Update the basic information database in real time through a status monitoring unit to build a real-time status information database.

[0091] S53: updating the real-time status information database through the safety assessment unit to build a construction personnel information database.

[0092] In this embodiment, real-name management requires all personnel involved in the construction to register with their real names, which helps to establish an accurate and comprehensive personnel information database. Through the real-name management system, workers' attendance, working hours, work status and other information can be recorded in real time, so that managers can instantly grasp the dynamic information of the construction site, facilitate the rational allocation of human resources, and improve project management efficiency. At the same time, the construction personnel information database is updated in real time through the safety assessment unit, which helps managers to have a comprehensive understanding of the construction personnel and improve supervision efficiency.

[0093] As a preferred embodiment, receiving the real-time monitoring data collected by the on-site monitoring module and performing intelligent scheduling on the construction personnel specifically includes:

[0094] S61. Subtract the real-time construction progress feedback received from the progress assessment unit transmission unit from the standard progress information to obtain the remaining construction progress.

[0095] S62: Encode the start time, duration and required construction personnel of the remaining construction progress into a character string.

[0096] S63. Based on the encoding character string in step S62, two parent encodings are randomly selected to perform a crossover operation to obtain a new child encoding, and the new child encoding is used as the search space.

[0097] S64. Randomly select a child code, perform mutation operations on the child code, and dynamically adjust the construction plan.

[0098] S65. A fitness function is constructed with the goal of minimizing construction period and cost while maximizing quality, and weight coefficients are introduced respectively to guide the genetic algorithm to search for the optimal scheduling solution, generate scheduling instructions and send them to the mobile terminal for confirmation.

[0099] In this embodiment, the process of biological evolution is simulated by genetic algorithm, including basic genetic operations such as individual selection, crossover and mutation, and the optimal solution or satisfactory solution of the problem, i.e., the optimal scheduling scheme, is found in the constructed search space. Through the crossover operation, the new offspring coding combines the characteristics of the two parent codings, and can generate new solutions. The mutation operation allows the offspring coding to be randomly adjusted, so that the construction plan can flexibly respond to the changes and uncertainties of the construction site. At the same time, the algorithm can be prevented from falling into the local optimal solution, and the possibility of finding the global optimal solution is increased. The fitness function of the genetic algorithm introduces a weight coefficient, which can adjust the focus of the optimization target according to the actual situation of the project, so that the scheduling scheme is more adapted to the project needs. The scheduling instructions are sent through the mobile terminal and wait for confirmation. The management personnel can adjust the scheduling scheme in combination with temporary changes, which improves the convenience of the construction site management personnel. Combining genetic algorithms and construction progress information bases to dynamically adjust the construction plan can not only optimize the construction scheduling, improve efficiency and quality, but also enhance the adaptability and flexibility of the project, provide scientific decision-making support for project managers, and ultimately improve the management level and success rate of the entire project.

[0100] The mobile terminal is used to interact with the server, so that the manager can obtain real-time information of the construction site and process the construction personnel scheduling instruction request sent by the server. The construction personnel receive the scheduling instruction of the server and feedback the construction progress to the server. In this embodiment, through the mobile terminal, the manager can make decisions quickly and improve management efficiency. For example, the efficiency of managing projects through mobile phones or tablets is improved. Whether in the office or on the construction site, the mobile terminal application can ensure the timely update and transmission of information, and improve the flexibility and response speed of project management.

[0101] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A system for improving supervision management efficiency, characterized in that: The system comprises: On-site monitoring module, which is used to monitor construction progress and safety through edge algorithms and transmit the monitoring data to the server for processing; The server is used to build a construction progress information database and a construction personnel information database, receive real-time supervision data collected by the on-site monitoring module, perform intelligent scheduling of construction personnel, and interact with the mobile terminal; The mobile terminal is used to interact with the server. The management personnel obtain the real-time information of the construction site and process the construction personnel scheduling instruction requests sent by the server. The construction personnel receive the scheduling instructions from the server and feedback the construction progress to the server.

2. The system for improving supervision management efficiency according to claim 1, characterized in that: The on-site monitoring module includes: Video monitoring unit, used to collect construction images of the construction site through panoramic cameras; The status monitoring unit is used to collect the working status information and identity information of the construction personnel and is connected with the video monitoring unit signal; The safety assessment unit is used to integrate the construction images of the video monitoring unit and the work status information of the construction personnel in the corresponding construction images to assess the safety status of the current construction site; The progress assessment unit is used to conduct progress assessment on the construction site in the construction image by combining the construction progress information database and the construction progress feedback from the construction personnel.

3. The system for improving supervision management efficiency according to claim 2, characterized in that: The safety monitoring unit includes a smart safety helmet, which includes a camera, a Bluetooth tag, a voice broadcast subunit, a control mainboard and a power supply. The camera, the Bluetooth tag, the voice broadcast subunit and the control mainboard are electrically connected to the power supply respectively. The camera is electrically connected to the control mainboard for collecting the work status information of the construction personnel and identifying the identity information of the construction personnel. The Bluetooth module is electrically connected to the control mainboard for locating the construction site of the construction personnel. The voice broadcast subunit is electrically connected to the control mainboard for broadcasting the feedback instructions of the safety assessment unit. The control mainboard is connected to the panoramic camera signal.

4. The system for improving supervision management efficiency according to claim 2, characterized in that: The security assessment unit is specifically used to perform the following operations: S11. Collect data from historical construction safety cases, build a safety assessment model for the construction site through a neural network, and determine dangerous construction behaviors and hazard sources based on the safety assessment model; S12, input the construction image into the YOLOV8 model to identify the borders of the hazard source and the construction personnel, and generate corresponding boundary coordinate sets based on the boundary boxes; S13, arranging the corresponding boundary coordinate sets of the construction personnel's trajectories into a first sequence in chronological order, and inputting them into BiLSTM to predict and quantify the future trajectory of the construction personnel, thereby obtaining a first prediction vector; S14, arranging the corresponding boundary coordinate sets of the hazard source trajectory into a second sequence in chronological order, and inputting the second sequence into BiLSTM to predict and quantify the future trajectory of the hazard source, thereby obtaining a second prediction vector; S15. The working status information of the construction personnel, the first prediction vector and the second prediction vector are simultaneously input into the safety assessment model, and if the output prediction result exceeds the risk threshold, a warning instruction is generated.

5. The system for improving supervision management efficiency according to claim 4, characterized in that: If the output prediction result exceeds the risk threshold, a warning instruction is generated, including: S21, the safety assessment model outputs the individual risk level of the construction personnel and the scenario risk level of the construction site, as well as a comprehensive risk level integrating the individual risk level and the scenario risk level; S22. When the scene risk level exceeds the preset scene safety threshold, a first-level risk instruction is generated, and a voice reminder is given to the construction workers at the corresponding construction site through the smart safety helmet; S23. When the personal risk level exceeds the preset personal safety threshold, a secondary risk instruction is generated, and a voice reminder is given to the corresponding construction personnel through the smart safety helmet; S24. When the comprehensive risk level exceeds the preset comprehensive safety threshold, a third-level risk instruction is generated, and voice reminders are given to all construction workers through smart safety helmets.

6. The system for improving supervision management efficiency according to claim 2, characterized in that: The progress evaluation unit is specifically used to perform the following operations: S31. Generate standard progress information of different construction stages of each construction site based on the construction progress information database, input the standard progress information into machine learning for training, and obtain a construction progress evaluation model; S32. When the construction personnel provide feedback on the construction progress, the construction images at the same time are captured and input into the construction progress assessment model for recognition to obtain real-time construction progress feedback; S33, comparing the real-time construction progress feedback with the construction progress feedback from the construction personnel, and if they match, comparing the real-time construction progress feedback with the standard progress information, and if they match, feeding back the real-time construction progress to the mobile terminal, and if they do not match, feeding back the real-time construction progress to the server; S34. If the real-time construction progress feedback does not match the construction progress feedback from the construction personnel, a progress confirmation instruction is fed back to the mobile terminal manager, and then step S33 is executed.

7. The system for improving supervision management efficiency according to claim 6, characterized in that: Build a construction progress information database, including: S41, collecting construction project information and generating a construction project information database; S42. Construct a visual BIM three-dimensional model of the construction project based on the construction project information database and BIM technology; S43, mapping the three-dimensional terrain data of the construction site with the construction image, building a construction progress information database, and updating the construction progress information database in real time through a progress evaluation unit.

8. The system for improving supervision management efficiency according to claim 5, characterized in that: Build a construction personnel information database, including: S51, collecting the real-name information of all construction personnel and generating a basic information database of construction personnel; S52, updating the basic information database in real time through a status monitoring unit to build a real-time status information database; S53: updating the real-time status information database through the safety assessment unit to build a construction personnel information database.

9. The system for improving supervision management efficiency according to claim 6, characterized in that: Receive real-time monitoring data collected by the on-site monitoring module and conduct intelligent scheduling of construction personnel, including: S61, subtracting the real-time construction progress feedback received from the progress assessment unit transmission unit from the standard progress information to obtain the remaining construction progress; S62, encoding the start time, duration and required construction personnel of the remaining construction progress into a character string; S63, based on the code string in step S62, randomly select two parent codes to perform a crossover operation to obtain a new child code, and use the new child code as the search space; S64, randomly selecting a child code, performing a mutation operation on the child code and dynamically adjusting the construction plan; S65. A fitness function is constructed with the goal of minimizing construction period and cost while maximizing quality, and weight coefficients are introduced respectively to guide the genetic algorithm to search for the optimal scheduling solution, generate scheduling instructions and send them to the mobile terminal for confirmation.

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