Building engineering supervision information management method and system based on big data

Abstract

The invention discloses a big data-based constructional engineering supervision information management method and system, and relates to the technical field of constructional engineering supervision, and the method comprises the steps: collecting project and supervision data through a data collection module, processing and cleaning data through a data processing module, carrying out the calculation through an information management module, and carrying out the analysis and decision through an analysis module. According to the invention, through quantitatively evaluating the cooperative work condition among the projects in the engineering project, the overall cooperative efficiency of the project is reflected, the project party is assisted to specifically improve the cooperative efficiency, reduce disputes and promote the project to proceed smoothly, the project risk can be comprehensively evaluated, risk early warning and decision support can be provided, and the project risk can be comprehensively evaluated. According to the method and the system, the configuration of supervision resources is managed and adjusted according to the actual condition of the project, so that the effective utilization of the resources is ensured, the supervision efficiency is improved, and the cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of construction engineering supervision, and in particular to a construction engineering supervision information management method and system based on big data. Background Art

[0002] In the current field of construction engineering, with the continuous expansion of project scale and increasing complexity, the number of project parties involved in the construction process of engineering projects has also increased. The coordinated operation between them is crucial to the smooth progress of engineering projects. Engineering supervision is a professional service activity that monitors Party B's engineering construction on behalf of Party A. The purpose of supervision is to ensure the quality and safety of engineering construction, improve the level of engineering construction, and give full play to the investment benefits. With the rapid development of big data technology, its application in various fields is becoming more and more extensive, providing new ideas and means for the information management of construction engineering supervision. By utilizing big data technology, it is possible to achieve comprehensive, real-time and accurate collection and analysis of engineering project-related data, providing strong data support for supervision work.

[0003] However, the current existing methods may lack quantitative evaluation methods for the collaborative operation between various project parties, which may make it difficult for supervisors to accurately judge the quality of the collaborative situation, and thus make supervisors lack data support when making decisions. In addition, the existing methods may rely more on the experience and subjective judgment of supervisors to assess the risks of engineering projects, and may lack scientific and objective risk assessment methods. In addition, when multiple engineering projects are supervised at the same time, the allocation of supervision resources may rely more on the experience and subjective judgment of supervisors, and may lack a scientific and reasonable resource allocation system. Summary of the Invention

[0004] The purpose of the present invention is to provide a construction project supervision information management method and system based on big data, which solves the problems raised in the above background technology.

[0005] To achieve the above objectives, the present invention provides a construction project supervision information management method based on big data, comprising the following steps:

[0006] Step S1: Using the data collection module, the design change submission time, the actual upload volume of acceptance materials, the construction log update rate, and the number of problems that have been rectified in the construction project are collected;

[0007] Step S2: Input the design change submission time, the actual upload volume of acceptance materials, the construction log update rate, and the number of rectified issues in the construction project into the data processing module. The data processing module cleans and standardizes the input data and stores the data in the database.

[0008] Step S3: The design change submission time, the actual upload volume of acceptance materials, the construction log update rate, and the number of rectified problems in the construction project are extracted from the database and input into the information management module. The information management module outputs the collaborative effectiveness score, risk level, and supervision resource allocation value.

[0009] Step S4: Input the synergy effectiveness score, risk level and supervision resource configuration value into the analysis module. The analysis module makes decisions on project rectification, project suspension and adjustment of supervision resources based on the input data.

[0010] Optionally, the information management module includes: a synergy effectiveness submodule, a supervision risk assessment submodule and a supervision resource allocation submodule.

[0011] Optionally, the calculation formula of the synergistic efficiency submodule is as follows:

[0012] ;

[0013] in:

[0014] CTR refers to the synergy effectiveness score, N refers to the number of synergy indicators, i refers to the index of the synergy indicator, CTW i Refers to the weight of the i-th category synergy indicator, CTS i Refers to the score of the i-th category synergy indicator, CTS i，max Refers to the full score of the i-th category collaborative indicator, QA refers to the weighted adjustable impact factor;

[0015] Refers to the standardized score value of the synergy indicator;

[0016] The processing process of the collaborative efficiency submodule is as follows: based on the design change submission time, the actual upload volume of acceptance materials, the construction log update rate and the number of problems that have been rectified in the construction project, the collaborative efficiency submodule outputs the design change response speed, material acceptance synchronization rate, construction log update timeliness and quality problem closed-loop rate. The output data corresponds to the score CTS of the i-th type of collaborative indicator. i , and based on the weight CTW of the i-th type of collaborative indicator i Output the synergy performance score CTR.

[0017] Optionally, the calculation formula of the supervision risk assessment submodule is as follows:

[0018] ;

[0019] in:

[0020] RPL refers to risk level, RPD refers to engineering quality defect rate;

[0021] The processing process of the supervision risk assessment submodule is as follows:

[0022] Comprehensively assess risk based on the input of the collaborative effectiveness score (CTR) and the engineering quality defect rate (RPD) to output the risk level (RPL);

[0023] When the RPL output is 3, it corresponds to a red alarm and construction must be suspended immediately and corrected;

[0024] When the RPL output is 2, it corresponds to a yellow warning, and the frequency of supervisory visits should be increased, with a focus on inspecting high-risk processes;

[0025] When the PRL output is 1, corresponding to the green situation, the normal supervision process should be maintained.

[0026] Optionally, the calculation formula of the supervision resource allocation submodule is as follows:

[0027] ;

[0028] in:

[0029] RSA refers to the supervision resource allocation value, 100-CTR refers to the synergy efficiency compensation coefficient, KK refers to the total supervision resource base of the project, which is analyzed based on the project's construction area, and SL refers to the historical project similarity correction coefficient, with a value range of 0.8-1.2;

[0030] The processing process of the supervision resource allocation submodule is as follows: combining the synergy efficiency score value CTR and the risk level RPL to comprehensively analyze the supervision resource configuration value RSA, so as to adjust the supervision resources in a targeted manner according to the risk level RPL, and feedback to the supervision resource allocation submodule through 100-CTR to invest more resources in the case of poor synergy efficiency, so as to output the supervision resource configuration value RSA, and adjust the allocation of supervision resources accordingly based on the supervision resource configuration value RSA.

[0031] Optionally, the collaborative indicators in the collaborative effectiveness submodule include: design change response speed A, material acceptance synchronization rate B, construction log update timeliness C, and quality problem closed-loop rate D;

[0032] The weight CTW of the synergy index of the i-th category in the synergy effectiveness submodule i Specifically:

[0033] The weight of synergy indicator A CTW A =0.25;

[0034] The weight of the collaborative indicator B CTW B =0.3;

[0035] The weight of the collaborative index C CTW C =0.2;

[0036] The weight of the collaborative indicator D is CTW D =0.25.

[0037] Optionally, the supervision resources in the supervision resource allocation submodule include: drone inspections, on-site inspections by supervision engineers, third-party supervision and testing, and supervision management coordination;

[0038] The resource allocation for drone inspections accounts for 15% of the supervision resource allocation value RSA;

[0039] The resource allocation for on-site inspections by the supervisory engineer accounts for 30% of the supervisory resource allocation value RSA;

[0040] The resource allocation for third-party supervision and testing accounts for 50% of the supervision resource allocation value RSA;

[0041] The resource allocation coordinated by the supervision management accounts for 5% of the supervision resource allocation value RSA.

[0042] A construction project supervision information management system based on big data, comprising:

[0043] Data collection module: used to collect design change submission time, actual upload volume of acceptance materials, construction log update rate and number of problems rectified in construction projects;

[0044] Data processing module: used to clean and standardize data on design change submission time, actual upload volume of acceptance materials, construction log update rate, and number of rectified issues in construction projects, and store the data in the database;

[0045] Information management module: used to calculate the design change submission time, the actual upload volume of acceptance materials, the construction log update rate and the number of rectified problems in the construction project after processing by the data processing module, so as to output the collaborative efficiency score, risk level and supervision resource allocation value;

[0046] Analysis module: used to analyze the synergy effectiveness score, risk level and supervision resource allocation value, and make corresponding decisions on project rectification, project suspension and adjustment of supervision resources.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] 1. The present invention outputs a collaborative effectiveness score through a collaborative effectiveness submodule. The calculation of the score can quantitatively evaluate the collaborative work efficiency of each participant in the engineering project to accurately reflect the overall collaborative effectiveness of the project, thereby integrating the supervision information of multiple projects to analyze the collaborative situation of multiple projects. Through quantitative evaluation, the project parties can clearly understand the scores of each collaborative indicator, so that the collaborative efficiency can be improved in a targeted manner. The improvement of collaborative effectiveness can reduce disputes between project parties caused by poor collaboration, promote the smooth progress of the project, and when the collaborative effectiveness score is low, it can also trigger countermeasures to increase the collaboration between projects.

[0049] 2. The present invention outputs the risk level through the supervision risk assessment submodule. The calculation of the risk level can comprehensively assess the risk situation of the engineering project, and provide risk warning and decision-making support for engineering supervision. Through the output risk level, the project party can timely understand the risk status of the project and then take corresponding measures to prevent and control risks. The risk level assessment result provides a basis for the decision-making of engineering supervision, and has excellent information analysis and management effects.

[0050] 3. The present invention outputs the supervision resource configuration value through the supervision resource allocation submodule. The calculation of the supervision resource configuration value can dynamically adjust the configuration of supervision resources according to the actual situation of the project to ensure the effective utilization of supervision resources. By dynamically adjusting and allocating supervision resource configuration, it can ensure the investment of supervision resources in key links and high-risk project areas, thereby improving supervision efficiency. Reasonable resource allocation can avoid waste of resources and reduce the cost of project supervision. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A flowchart of the steps of the construction project supervision information management method based on big data;

[0052] Figure 2 This is the overall structural diagram of the construction project supervision information management system based on big data;

[0053] Figure 3 This is a structural diagram of the information management module in the construction project supervision information management system based on big data. DETAILED DESCRIPTION

[0054] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0055] Existing supervision information management systems lack quantitative assessment methods for the efficiency of collaborative operations between project parties, making it difficult for supervisors to accurately judge the quality of collaboration and resulting in a lack of data support for decision-making. Furthermore, traditional supervision information management and supervision methods often rely on supervisors' experience and subjective judgment to assess project risks, lacking scientific and objective risk assessment methods. Furthermore, when multiple projects are being supervised simultaneously, the allocation of supervision resources often relies on supervisors' experience and subjective judgment, lacking a scientific and reasonable resource allocation system.

[0056] This supervision information management method can use big data technology to evaluate and analyze the collaborative operation efficiency between various project parties, and then can intuitively reflect the collaborative status between various project parties, provide decision-making support for supervision personnel, improve collaborative operation efficiency, and then effectively avoid disputes between project parties, and ensure the smooth progress of engineering projects. In addition, this method can predict and evaluate potential risks in engineering projects, and combine big data technology to comprehensively and real-time collect and analyze relevant data of engineering projects. It can accurately identify risk points in engineering projects so that supervision personnel can take corresponding measures to prevent and control risks in a timely manner to reduce the risk level of engineering projects. In addition, this system method can reasonably allocate supervision resources according to the actual situation of the engineering project and supervision needs, and can analyze the number of supervision resources required for each project to ensure the full utilization and reasonable allocation of supervision resources, and improve the efficiency and accuracy of supervision work.

[0057] Example 1:

[0058] See also Figures 1 to 3 , this implementation provides a construction project supervision information management method based on big data, including the following steps:

[0059] Step S1: Using the data collection module, the design change submission time, the actual upload volume of acceptance materials, the construction log update rate, and the number of problems that have been rectified in the construction project are collected;

[0060] Step S2: Input the design change submission time, the actual upload volume of acceptance materials, the construction log update rate, and the number of rectified issues in the construction project into the data processing module. The data processing module cleans and standardizes the input data and stores the data in the database.

[0061] Step S3: The design change submission time, the actual upload volume of acceptance materials, the construction log update rate, and the number of rectified problems in the construction project are extracted from the database and input into the information management module. The information management module outputs the collaborative effectiveness score, risk level, and supervision resource allocation value.

[0062] Step S4: Input the synergy effectiveness score, risk level, and supervision resource allocation value into the analysis module. The analysis module makes decisions on project rectification, project suspension, and adjustment of supervision resources based on the input data.

[0063] The information management module includes a synergy effectiveness submodule, a supervision risk assessment submodule and a supervision resource allocation submodule.

[0064] In this embodiment: the collaborative work efficiency of each participant in the project can be quantitatively evaluated through the collaborative efficiency submodule, thereby accurately reflecting the overall collaborative efficiency of the project. Through quantitative evaluation, the project party can clearly understand the scores of each collaborative indicator, and then improve the collaborative efficiency in a targeted manner. The improvement of collaborative efficiency helps to reduce disputes between project parties caused by poor collaboration and promote the smooth progress of the project. The supervision risk assessment submodule can comprehensively evaluate the risk situation of the project and provide risk warning and decision support for project supervision. By outputting the risk level, the project party can timely understand the risk status of the project and take corresponding measures to prevent and control risks. The risk level assessment results can provide a basis for decision-making in project supervision, such as whether to suspend construction and increase the frequency of supervision. The supervision resource allocation submodule can dynamically adjust the configuration of supervision resources according to the actual situation of the project to ensure the effective use of supervision resources. By dynamically adjusting the configuration of supervision resources, it can ensure that supervision resources are invested in key links and high-risk areas, improve supervision efficiency, and reasonable resource allocation can avoid resource waste and reduce the cost of project supervision.

[0065] Then, multiple sub-modules are combined to form a complete construction project supervision information management method system based on big data, which realizes the comprehensive optimization and improvement of engineering supervision work. This method system has quantitative evaluation and dynamic adjustment of resource allocation mechanism, which can significantly improve the efficiency and quality of engineering supervision and ensure the smooth progress of the project. This method can comprehensively evaluate and warn the risk level of the project and reduce the losses and impacts caused by risks. This method can dynamically adjust the resource allocation mechanism to ensure the investment of supervision resources in key links and high-risk areas, and improve the utilization efficiency of resources. This method can quantitatively evaluate the synergy effect, which helps promote the collaboration of all parties involved in the project, reduce the occurrence of disputes and contradictions, and improve the overall benefits of the project.

[0066] See also Figures 1 to 3 , the processing process of the synergy effectiveness submodule is as follows:

[0067] ;

[0068] in:

[0069] CTR refers to the synergy effectiveness score, N refers to the number of synergy indicators, i refers to the index of the synergy indicator, CTWi Refers to the weight of the i-th category synergy indicator, CTS i Refers to the score of the i-th category synergy indicator, CTS i，max Refers to the full score of the i-th category collaborative indicator, QA refers to the weighted adjustable impact factor;

[0070] Refers to the standardized score value of the synergy indicator, which is used to unify the dimensions of the scores of different synergy indicators;

[0071] The processing process of the collaborative efficiency submodule is as follows: Based on the design change submission time, the actual upload volume of acceptance materials, the construction log update rate and the number of problems that have been rectified in the construction project, the collaborative efficiency submodule outputs the design change response speed, material acceptance synchronization rate, construction log update timeliness and quality problem closed-loop rate. The output data corresponds to the score CTS of the i-th type of collaborative indicator. i , and based on the weight CTW of the i-th type of collaborative indicator i Output synergy effectiveness score CTR;

[0072] The synergy indicators in the synergy effectiveness submodule include:

[0073] Design change response speed (A), which measures the response speed of all parties involved in the project to design changes. A faster response speed helps reduce project delays and cost increases caused by design changes;

[0074] Material acceptance synchronization rate B, this indicator reflects the collaborative efficiency of material acceptance work. Higher synchronization helps reduce waiting time and resource waste during the material acceptance process.

[0075] Construction log update timeliness C, this indicator measures the update status of the construction log. Timely log updates help supervisors understand the situation on the construction site in a timely manner and provide a basis for decision-making

[0076] The closed-loop rate (D) of quality issues reflects the closed-loop management effect of quality issue handling. A higher closed-loop rate helps reduce the recurrence of quality issues and improve the overall quality of the project.

[0077] The weight of the synergy index of the i-th category in the synergy effectiveness submodule CTW i Specifically:

[0078] The weight of synergy indicator A CTW A =0.25;

[0079] The weight of the collaborative indicator B CTW A =0.3;

[0080] The weight of the collaborative index C CTW A =0.2;

[0081] The weight of the collaborative indicator D is CTW A =0.25;

[0082] In this embodiment: the score CTS of the i-th type of collaborative indicator i具体 As shown in the following table:

[0083] Index i of the synergy indicator Name of the synergy indicator Data source <![CDATA[Weight CTW of the i-th type of collaborative index i > <![CDATA[Full score value CTS of the i-th type of collaborative indicator i，max > A Design change response speed BIM system log data 25% 100 B Material acceptance synchronization rate ERP system acceptance record data 30% 100 C Timeliness of construction log updates Construction log supervision data 20% 100 D Closed-loop rate of quality issues Quality incident reporting data 25% 100

[0084] Design change response speedA:

[0085] First: A = A1 - A2;

[0086] Where: A1 refers to the specified response time for design changes, and A2 refers to the actual response time for design changes;

[0087] Secondly: determine whether the design change response speed A is greater than or equal to 0. If A is greater than or equal to 0, then CTS A =100, if A is less than or equal to 0, then 5 points will be deducted from the full score of 100 for every hour exceeded, with the lowest score being 0;

[0088] Material acceptance synchronization rate B:

[0089] First: B = B1 - B2;

[0090] Where: B1 refers to the target upload volume of acceptance materials, and B2 refers to the actual upload volume of acceptance materials;

[0091] Secondly: determine whether the material acceptance synchronization rate B is equal to 0. If B is equal to 0, then CTS B =100, if B is greater than 0, then 5 points will be deducted from the full score of 100 for each difference, with the lowest score being 0;

[0092] Timeliness of construction log update C:

[0093] Calculate whether the construction log update rate in the last three days is greater than or equal to 80%. If so, CTS C =100, otherwise CTS C The output value of is deducted according to the number of unupdated entries;

[0094] Quality problem closed-loop rate D:

[0095] First: D = D1 - D2;

[0096] Where: D1 refers to the total number of problems found in construction projects, and D2 refers to the number of problems that have been rectified in construction projects;

[0097] Secondly: Is the closed-loop rate D of quality issues equal to 0? If D is equal to 0, then CTS D =100, if D is greater than 0, then 5 points will be deducted from the full score of 100 for each difference, with the lowest score being 0;

[0098] The collaborative effectiveness score CTR in this submodule uses a quantitative approach to comprehensively evaluate the collaborative work of all parties involved in the project, helping supervisors to intuitively understand the collaborative status of the project. CTR can be used as an important basis for resource allocation. When CTR is low, it indicates that there are bottlenecks or problems in the collaborative work of the project, and it is necessary to increase relevant resource investment to improve collaborative effectiveness. By analyzing the changing trends and influencing factors of CTR, supervisors can identify unreasonable links in the collaborative process and put forward optimization suggestions, thereby improving the overall efficiency of the project. Good collaborative effectiveness is an important basis for ensuring project quality. Improving CTR helps reduce communication barriers and misunderstandings in the project and reduce quality risks caused by collaborative problems. The calculation process of CTR involves multiple collaborative indicators, and the data of these indicators usually come from the supervision information management system. Therefore, the calculation process of CTR promotes information sharing and integration, and improves the efficiency of information utilization.

[0099] When the synergy effectiveness score CTR is lower than the safe value, it indicates that there are serious problems in project collaboration and urgent measures need to be taken to improve synergy effectiveness;

[0100] Organize collaborative meetings: Hold collaborative meetings with all project parties to analyze the reasons why the CTR is lower than the safety value, clarify the responsibilities of all parties, and develop collaborative improvement measures;

[0101] Adjust the collaborative process: Based on the results of the collaborative meeting, adjust and optimize the project's collaborative process to eliminate bottlenecks and obstacles and improve collaborative efficiency;

[0102] Increase collaborative resource investment: For links with low collaborative efficiency, increase relevant resource investment, such as adding supervisors and introducing collaborative tools, to improve collaborative efficiency;

[0103] Establish a collaborative incentive and penalty mechanism: Establish a collaborative incentive and penalty mechanism for all parties involved in the project to encourage and urge them to actively participate in collaborative work and improve collaborative effectiveness. For example, a collaborative effectiveness reward fund can be set up to reward teams or individuals with high collaborative effectiveness.

[0104] Strengthen collaboration training: Organize collaboration training for all project parties to improve their collaboration awareness and capabilities. Training content can include the use of collaboration tools and understanding of collaboration processes.

[0105] See also Figures 1 to 3 ,The processing process of the supervision risk assessment submodule is as follows:

[0106] ;

[0107] in:

[0108] RPL refers to risk level;

[0109] RPD refers to the project quality defect rate. The calculation formula for RPD is RPD = (number of unqualified items + number of uninspected items × 50%) / (total number of inspected items) × 100%. Unqualified items refer to unqualified items confirmed by third-party inspections and parallel inspections by supervisors. The number of uninspected items refers to items that were not inspected as planned. The number of uninspected items × 50% means that the uninspected items are converted into unqualified items at a rate of 50%.

[0110] The processing process of the supervision risk assessment submodule is as follows:

[0111] Comprehensively assess risk based on the input of the collaborative effectiveness score (CTR) and the engineering quality defect rate (RPD) to output the risk level (RPL);

[0112] When the RPL output is 3, it corresponds to a red alert. Construction should be suspended immediately and rectification should be carried out. A comprehensive safety inspection and quality rectification should be carried out. A third-party supervision and testing agency should be brought in to conduct an independent assessment of key parts and links. Communication with the owner and design company should be strengthened to jointly develop a risk response plan.

[0113] When the RPL output is 2, it corresponds to a yellow warning. The frequency of supervisory visits should be increased, with a focus on inspecting high-risk processes. The frequency of on-site video inspections should be increased, key construction links should be monitored, and the frequency of high-tech means such as drone inspections should be increased to improve monitoring efficiency and accuracy. Special inspections should be organized to conduct in-depth investigations and rectifications of potential problems.

[0114] When the PRL output is 1, corresponding to the green situation, the regular supervision process should be maintained, and safety inspections and quality spot checks should be conducted regularly on the construction site to ensure that construction activities comply with regulations. Communication with the construction unit should be strengthened to keep abreast of construction progress and potential problems.

[0115] In this embodiment: This sub-module can provide accurate and timely information support for risk assessment. Through the intuitive display of risk levels, supervisors can intuitively understand the project risk status and make decisions quickly. Based on data analysis, the overall supervision information management system can provide early warning of potential risks and gain time for taking preventive measures. Based on the risk assessment results, the overall supervision information management system can dynamically adjust the allocation of supervision resources to ensure sufficient investment in key links and high-risk areas. By optimizing resource allocation, the efficiency and effectiveness of supervision work can be improved and project risks can be reduced. Based on this sub-module, during the risk assessment and response process, all parties can jointly analyze problems, formulate plans, implement rectifications, and form a joint force to promote the smooth progress of the project.

[0116] See also Figures 1 to 3 ,The processing process of the supervision resource allocation submodule is as follows:

[0117] ;

[0118] in:

[0119] RSA refers to the supervision resource allocation value. The resource allocation result generates a task work order, which can be automatically assigned to the corresponding supervisor. The unit of the supervision resource allocation value RSA can be man-hours / week, which converts the man-hours into specific action frequency.

[0120] 100-CTR refers to the synergy compensation coefficient;

[0121] KK refers to the total supervision resource base of the project, which is analyzed based on the project's construction area. The calculation formula of KK can be: KK = project construction area m2 × 0.3 man-hours / m2 + project underground engineering area m2 × 2 man-hours / m2;

[0122] SL refers to the historical project similarity correction coefficient, which ranges from 0.8 to 1.2. When the geological complexity of the project is higher, it is closer to 1.2, and when the geological complexity is lower, it is closer to 0.8.

[0123] The processing process of the supervision resource allocation submodule is as follows: the synergy efficiency score CTR and the risk level RPL are combined to comprehensively analyze the supervision resource allocation value RSA, so as to adjust the supervision resources in a targeted manner according to the risk level RPL. The 100-CTR is fed back to the supervision resource allocation submodule to allocate more resources to the situation of poor synergy efficiency, and the supervision resource allocation value RSA is output. Based on the supervision resource allocation value RSA, the allocation of supervision resources is adjusted accordingly.

[0124] The supervision resources in the supervision resource allocation submodule include: drone inspections, on-site inspections by supervision engineers, third-party supervision and testing, and supervision management coordination;

[0125] The resource allocation for drone inspections accounts for 15% of the supervisory resource allocation value (RSA). Drone inspections can be used to take aerial photos of construction progress, monitor compliance in material storage areas, and check nighttime lighting and safety warning signs.

[0126] The resource allocation for on-site inspections by supervision engineers accounts for 30% of the supervision resource allocation value RSA;

[0127] The resource allocation for third-party supervision and testing accounts for 50% of the supervision resource allocation value RSA. The third-party supervision and testing can be strength spot checks and waterproof engineering closed water tests. The means of third-party supervision are technical means well known in the technical field;

[0128] The resource allocation for supervision management and coordination accounts for 5% of the supervision resource allocation value RSA. Supervision management and coordination can be divided into meetings, reports, problem rectification and tracking.

[0129] In this embodiment: the supervision resource allocation value RSA calculated by this submodule is the supervision resource value for investment in the project based on the analysis of the project's coordination and risk situation. The abstract numerical value is converted into the concept of working hours, and combined with the proportion of each supervision resource in the supervision resource allocation value RSA, the working hours obtained by drone inspection, on-site inspection by supervision engineers, third-party supervision and testing, and supervision management coordination are calculated in a targeted manner. Then, the time for each supervision resource investment is formulated within a certain construction period, thereby improving the pertinence of project supervision. In areas with higher risk levels or decreased coordination efficiency, the frequency and scope of drone inspections can be increased to promptly discover and deal with potential problems. For key construction links or high-risk areas, more supervision engineers can be arranged for on-site inspections to ensure construction quality and safety. When independent and objective evaluation of project quality is required, a third-party supervision and testing agency can be introduced to provide fair evaluation results. When coordination problems arise among the project parties, supervision management coordination can be strengthened to promote communication and cooperation among the project parties.

[0130] This sub-module can more accurately calculate the configuration value of supervision resources by comprehensively considering multiple factors, including the project's synergy, risk level, and total resource base. This means that supervision resources can be dynamically adjusted according to the actual needs and risk conditions of the project, avoiding waste and idleness of resources and improving resource utilization efficiency. The RSA calculated by Formula 3 can clarify the specific allocation of various supervision resources, such as drone inspections, on-site inspections by supervision engineers, and third-party supervision and testing. This helps to optimize the structure of supervision resources, ensure sufficient investment of various resources in key links and high-risk areas, and improve the comprehensiveness and depth of supervision work. When the project has higher risks or reduced synergy, this sub-module can quickly Quickly adjust the configuration of supervision resources and increase the supervision intensity of key links, which will help improve the response speed of supervision work, ensure that problems can be discovered and handled in a timely manner, and reduce project risks. This sub-module can reasonably allocate supervision resources to ensure the collaboration of all parties involved in the project in the supervision work. The effective cooperation of supervision resources such as drone inspections, on-site inspections by supervision engineers, third-party supervision and testing, and supervision management coordination can form a comprehensive supervision system to jointly promote the smooth progress of the project. Through the efficient configuration of supervision resources, this sub-module can ensure sufficient investment of supervision resources at critical moments, improve supervision efficiency and quality, help reduce project risks, reduce losses and impacts caused by risks, and thus improve the overall benefits of the project.

[0131] It is worth noting that the risk level RPL calculated in the supervision risk assessment submodule affects the weighted adjustable impact factor QA in the synergy efficiency submodule, and then adjusts the weight CTW of the i-th type of synergy indicator in a targeted manner. i, thereby continuously optimizing the synergy effectiveness score CTR according to the risk level. The specific processing process is as follows:

[0132] First: QA new =QA old × (1 / RPL);

[0133] Second: Set the iteration termination condition:

[0134] Termination condition 1: The number of iterations is 100;

[0135] Termination condition 2: |CTR new -CTR old |<0.5;

[0136] in:

[0137] QA new Refers to the weighted adjustable impact factor after iteration, QA old Refers to the weighted adjustable impact factor before iteration. The initial value can be set to 1, CTR new Refers to the synergistic effectiveness score and CTR after iteration old Refers to the synergy effectiveness score after iteration;

[0138] In this embodiment: Since the risk level RPL output is 1, 2 and 3, when the output is 1, it corresponds to the green situation, so QA new Remain unchanged to achieve the current weight CTW of the i-th category synergy indicator i And the synergy effectiveness score CTR, when the risk level RPL output is 2 and 3, 1 / RPL is output as 1 / 2 and 1 / 3, which can reduce the QA value to 1 / 2 and 1 / 3 of the original value to a certain extent, thereby reducing the weight of the i-th type of synergy indicator CTW i and the synergy effectiveness score CTR, thereby reducing the contribution in the synergy effectiveness score CTR to a certain range, thereby forcing the relevant parties to give priority to rectifying the problem;

[0139] This iterative approach dynamically influences CTWi, enabling the synergy effectiveness score (CTR) to more sensitively reflect the project's actual situation when higher project risks emerge, thereby prompting stakeholders to more quickly implement corrective measures. By dynamically adjusting CTWi, the synergy effectiveness score (CTR) can more sensitively reflect the project's actual situation when higher project risks emerge, thereby prompting stakeholders to take corrective measures more quickly. When risk assessment results are high, reducing the weight of the synergy indicator effectively sends a signal to stakeholders that the current project's top priority is risk reduction, rather than pursuing excessive synergy effectiveness. This helps guide stakeholders to invest more resources in risk prevention and problem solving. This iterative approach enables dynamic adjustment of the supervision information management method based on the project's actual situation, enhancing its flexibility and applicability. This helps supervisors better cope with complex and changing project environments and improve the efficiency and effectiveness of supervision work. By dynamically adjusting weights and the synergy effectiveness score (CTR), project parties can be encouraged to pay closer attention to the project's overall situation and risk profile, thereby strengthening collaboration and jointly promoting the smooth progress of the project.

[0140] In the specific implementation process, the multiple sub-modules in this method are used to form a construction engineering supervision information management system based on big data, and the score CTS of the i-th type of collaborative indicator and the weight CTW of the i-th type of collaborative indicator are used to calculate the construction engineering supervision information management system based on big data. i The collaborative efficiency submodule takes the input of , and outputs the collaborative efficiency score CTR. By calculating the collaborative efficiency score CTR, the collaborative work efficiency of each participant in the project can be quantitatively evaluated, thereby accurately reflecting the overall collaborative efficiency of the project. Through quantitative evaluation, the project parties can clearly understand the scores of each collaborative indicator, and thus can improve the collaborative efficiency in a targeted manner. The improvement of collaborative efficiency can reduce disputes between project parties caused by poor collaboration and promote the smooth progress of the project.

[0141] The collaborative effectiveness score (CTR) and the engineering quality defect rate (RPD) are input into the supervision risk assessment submodule, which then outputs the risk level (RPL). The calculation of the RPL comprehensively assesses the risk status of the project, providing risk warning and decision-making support for project supervision. By outputting the risk level, the project party can promptly understand the project's risk status and take appropriate measures for risk prevention and control. The risk level assessment results can provide a basis for project supervision decisions, such as whether to suspend construction and increase the frequency of supervision.

[0142] The synergy performance score value CTR and risk level RPL are input into the supervision resource allocation submodule, and the supervision resource allocation submodule outputs the supervision resource configuration value RSA. The calculation of the supervision resource configuration value RSA can dynamically adjust the configuration of supervision resources according to the actual situation of the project to ensure the effective utilization of supervision resources. By dynamically adjusting the supervision resource configuration, it can ensure the investment of supervision resources in key links and high-risk areas, thereby improving supervision efficiency. Reasonable resource allocation can avoid waste of resources and reduce the cost of project supervision.

[0143] Example 2: Please refer to Figure 1 、 Figure 2 and Figure 3 , a construction project supervision information management system based on big data, including:

[0144] Data collection module: used to collect design change submission time, actual upload volume of acceptance materials, construction log update rate and number of problems rectified in construction projects;

[0145] Data processing module: used to clean and standardize data on design change submission time, actual upload volume of acceptance materials, construction log update rate, and number of rectified issues in construction projects, and store the data in the database;

[0146] Information Management Module: This module is used to calculate the design change submission time, the actual upload volume of acceptance materials, the construction log update rate, and the number of rectified issues in the construction project after processing by the data processing module, in order to output the collaborative effectiveness score, risk level, and supervision resource allocation value;

[0147] Analysis module: used to analyze the synergy effectiveness score, risk level and supervision resource allocation value, and make corresponding decisions on project rectification, project suspension and adjustment of supervision resources.

[0148] In this embodiment: the data processing module first needs to clean the input data. Data cleaning is to delete duplicate records, such as repeated submissions of design changes, and then correct abnormal values ​​to avoid affecting the normal input of subsequent data into the formula of this method. Then the data is standardized. The normalization processing method of the maximum and minimum values can be used to normalize data of different dimensions to a certain range to achieve data unification. The processed data is then input into the database for storage. Structured data can be stored in the MySQL database, and unstructured data can be stored in MongoDB. After the analysis module makes a decision, it can automatically push the rectification task in the form of a mobile app notification, and then perform on-site execution. Combined monitoring is carried out through drone inspections and on-site monitoring by supervision engineers. The construction party then submits a rectification report through the APP to update the data in the sub-module of this method.

[0149] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A construction project supervision information management method based on big data, characterized in that: The following steps are involved: Step S1: Using the data collection module, the design change submission time, the actual upload volume of acceptance materials, the construction log update rate, and the number of problems that have been rectified in the construction project are collected; Step S2: Input the design change submission time, the actual upload volume of acceptance materials, the construction log update rate, and the number of rectified issues in the construction project into the data processing module. The data processing module cleans and standardizes the input data and stores the data in the database. Step S3: The design change submission time, the actual amount of acceptance materials uploaded, the construction log update rate, and the number of corrected problems in the construction project are extracted from the database and input into the information management module. The information management module then outputs the collaborative effectiveness score, risk level, and supervision resource allocation value. Step S4: Input the synergy effectiveness score, risk level and supervision resource configuration value into the analysis module. The analysis module makes decisions on project rectification, project suspension and adjustment of supervision resources based on the input data.

2. The method for managing construction project supervision information based on big data according to claim 1, characterized in that: The information management module includes a synergy effectiveness submodule, a supervision risk assessment submodule and a supervision resource allocation submodule.

3. The construction project supervision information management method based on big data according to claim 2 is characterized by: The calculation formula of the synergistic efficiency submodule is as follows: ； in: CTR refers to the synergy effectiveness score, N refers to the number of synergy indicators, i refers to the index of the synergy indicator, CTW i Refers to the weight of the i-th category synergy indicator, CTS i Refers to the score of the i-th category synergy indicator, CTS i，max Refers to the full score of the i-th category collaborative indicator, QA refers to the weighted adjustable impact factor; Refers to the standardized score value of the synergy indicator; The processing process of the collaborative efficiency submodule is as follows: based on the design change submission time, the actual upload volume of acceptance materials, the construction log update rate and the number of problems that have been rectified in the construction project, the collaborative efficiency submodule outputs the design change response speed, material acceptance synchronization rate, construction log update timeliness and quality problem closed-loop rate. The output data corresponds to the score CTS of the i-th type of collaborative indicator. i , and based on the weight CTW of the i-th type of collaborative indicator i Output the synergy performance score CTR.

4. The method for managing construction project supervision information based on big data according to claim 3 is characterized by: The calculation formula of the supervision risk assessment submodule is as follows: ； in: RPL refers to risk level, RPD refers to engineering quality defect rate; The processing process of the supervision risk assessment submodule is as follows: Comprehensively assess risk based on the input of the collaborative effectiveness score (CTR) and the engineering quality defect rate (RPD) to output the risk level (RPL); When the RPL output is 3, it corresponds to a red alarm and construction must be suspended immediately and corrected; When the RPL output is 2, it corresponds to a yellow warning, and the frequency of supervisory visits should be increased, with a focus on inspecting high-risk processes; When the PRL output is 1, corresponding to the green situation, the normal supervision process should be maintained.

5. The method for managing construction project supervision information based on big data according to claim 4 is characterized in that: The calculation formula of the supervision resource allocation submodule is as follows: ； in: RSA refers to the supervision resource allocation value, 100-CTR refers to the synergy efficiency compensation coefficient, KK refers to the total supervision resource base of the project, which is analyzed based on the project's construction area, and SL refers to the historical project similarity correction coefficient, with a value range of 0.8-1.2; The processing process of the supervision resource allocation submodule is as follows: combining the synergy efficiency score value CTR and the risk level RPL to comprehensively analyze the supervision resource configuration value RSA, so as to adjust the supervision resources in a targeted manner according to the risk level RPL, and feedback to the supervision resource allocation submodule through 100-CTR to invest more resources in the case of poor synergy efficiency, so as to output the supervision resource configuration value RSA, and adjust the allocation of supervision resources accordingly based on the supervision resource configuration value RSA.

6. The method for managing construction project supervision information based on big data according to claim 2, characterized in that: The collaborative indicators in the collaborative effectiveness submodule include: design change response speed A, material acceptance synchronization rate B, construction log update timeliness C and quality problem closed-loop rate D; The weight CTW of the synergy index of the i-th category in the synergy effectiveness submodule i Specifically: The weight of synergy indicator A CTW A =0.25; The weight of the collaborative indicator B CTW B =0.3; The weight of the collaborative index C CTW C =0.2; The weight of the collaborative indicator D is CTW D =0.

25.

7. The method for managing construction project supervision information based on big data according to claim 5, characterized in that: The supervision resources in the supervision resource allocation submodule include: drone inspections, on-site inspections by supervision engineers, third-party supervision and testing, and supervision management coordination; The resource allocation for drone inspections accounts for 15% of the supervision resource allocation value RSA; The resource allocation for on-site inspections by the supervisory engineer accounts for 30% of the supervisory resource allocation value RSA; The resource allocation for third-party supervision and testing accounts for 50% of the supervision resource allocation value RSA; The resource allocation coordinated by the supervision management accounts for 5% of the supervision resource allocation value RSA.

8. A construction project supervision information management system based on big data, characterized by: include: Data collection module: used to collect design change submission time, actual upload volume of acceptance materials, construction log update rate and number of problems rectified in construction projects; Data processing module: used to clean and standardize data on design change submission time, actual upload volume of acceptance materials, construction log update rate, and number of rectified issues in construction projects, and store the data in the database; Information management module: used to calculate the design change submission time, the actual upload volume of acceptance materials, the construction log update rate and the number of rectified problems in the construction project after processing by the data processing module, so as to output the collaborative efficiency score, risk level and supervision resource allocation value; Analysis module: used to analyze the synergy effectiveness score, risk level and supervision resource allocation value, and make corresponding decisions on project rectification, project suspension and adjustment of supervision resources.

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