An AI-based building engineering information integration management system and method

Abstract

This invention discloses a construction project information integration management system and method based on an AI model, belonging to the field of construction project information integration management technology. The invention includes a construction project information filtering module, a construction project information integration module, an abnormal building characteristic value prediction module, a construction project quality assessment module, and a construction project management module. The construction project information filtering module is used to filter out heterogeneous data from various construction project sub-projects. The construction project information integration module is used to obtain the heterogeneity index of each construction project sub-project. The abnormal building characteristic value prediction module is used to predict the abnormal building characteristic values ​​of each construction project sub-project. The construction project quality assessment module is used to assess the real-time construction quality of each construction project sub-project. This invention selectively calls construction parameters for each construction project sub-project, reducing the workload of the system in integrating construction information and improving the system's information integration efficiency.

Description

Technical Field

[0001] This invention relates to the field of building engineering information integration and management technology, specifically a building engineering information integration and management system and method based on an AI model. Background Technology

[0002] With the rapid development of information technology, information-based management of construction projects has emerged as an important means for the transformation and upgrading of the construction industry. Information-based management of construction projects refers to the effective integration and optimization of human, material, and financial resources during the construction process using modern information technology to improve construction efficiency, reduce costs, and ensure project quality and safety.

[0003] Currently, during the construction process, the construction status of each sub-area of ​​the building is monitored by zone to quickly extract abnormal information from the construction project information. However, this process does not take into account the construction impact between different sub-areas. Furthermore, in the existing technology, when integrating construction project information, the analysis of multiple dimensions of construction project information is carried out separately, and the integrated processing result is obtained based on the single analysis result. This reduces the effectiveness of information integration and processing, while increasing the amount of construction project information to be integrated and processed. Summary of the Invention

[0004] The purpose of this invention is to provide an AI-based building engineering information integration management system and method to solve the problems raised in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a building engineering information integration and management system based on an AI model, the system comprising a building engineering information filtering module, a building engineering information integration module, an abnormal building characteristic value prediction module, a building engineering quality assessment module, and a building engineering management module;

[0006] The building engineering information filtering module is used to filter out heterogeneous data of each building engineering sub-project based on the building technology data and building construction data of each building engineering sub-project;

[0007] The building engineering information integration module is used to find the related heterogeneous data of each building engineering sub-project, and to integrate the found related heterogeneous data to obtain the heterogeneity index of each building engineering sub-project.

[0008] The abnormal building feature value prediction module is used to predict the abnormal building feature values ​​of each building engineering sub-project based on the heterogeneity index of each building engineering sub-project.

[0009] The construction engineering quality assessment module selectively retrieves construction parameters for each construction engineering sub-project based on abnormal building characteristic values, and constructs a safety risk assessment model for each construction engineering sub-project based on the retrieved construction parameters to assess the real-time construction quality of each construction engineering sub-project.

[0010] The construction project management module manages the construction status of each construction project sub-project based on the real-time construction quality assessment results and abnormal construction characteristic values ​​of each sub-project.

[0011] Furthermore, the building engineering information filtering module includes a partitioning unit and a heterogeneous data filtering unit;

[0012] The division unit divides the construction area into several construction sub-projects based on the construction area of ​​each construction team at the selected construction progress stage. A randomly selected construction sub-project is called the selected construction sub-project.

[0013] The heterogeneous data filtering unit acquires the construction technology data and construction data of each construction sub-project at the selected construction progress stage. Based on the acquired information, it matches the construction technology data R of the selected sub-project at the selected construction progress stage with the construction data Q of the selected sub-project at the selected construction progress stage. If R≤Q≤R*(1+τ), the match is successful; if R>Q, the match is unsuccessful. The unmatched construction data is taken as the heterogeneous data of the selected sub-project at the selected construction progress stage, where τ represents the error coefficient. Since both construction technology data and construction data have temporal sequence, if the data can be matched successfully, it means that the construction team can complete the construction task; otherwise, it means that the construction team cannot complete the construction task.

[0014] Furthermore, the building engineering information integration module includes a heterogeneous data search unit and a heterogeneous data integration unit;

[0015] The heterogeneous data finding unit searches for related heterogeneous data based on the corresponding construction sub-projects and the relationships between them. Specifically, the searching method is as follows: if the influence coefficient U between construction sub-project A and construction sub-project B... AB If the value is greater than 0.5, the heterogeneous data corresponding to the construction sub-project B is considered to be related heterogeneous data to the heterogeneous data corresponding to the construction sub-project A; otherwise, the heterogeneous data corresponding to the construction sub-project B is not considered to be related heterogeneous data to the heterogeneous data corresponding to the construction sub-project A.

[0016] When t B -tA When >0, U AB =exp(-(t B -t A ));

[0017] When t B -t A When ≤0, U AB =0;

[0018] Where exp() represents an exponential function with base e and e = 2.72, t A This indicates the end time of sub-project A of the construction project, as defined by the building requirements, at the selected construction schedule stage. B This indicates the start time of the selected construction schedule phase for sub-project B of the construction project, which is formulated according to the building requirements.

[0019] The heterogeneous data integration unit stores the heterogeneous data corresponding to the selected engineering sub-project and the associated heterogeneous data of the selected engineering sub-project in a set M, and predicts the heterogeneity index of the selected engineering sub-project based on the set M. It then traverses all construction engineering sub-projects within the selected construction progress stage and predicts the heterogeneity index of each construction engineering sub-project.

[0020] Furthermore, the specific formula for the heterogeneous data integration and processing unit to predict the heterogeneity index of the selected engineering sub-project is as follows:

[0021] ;

[0022] Where q represents the construction time of the selected engineering sub-project in the selected construction progress stage according to the building requirements, j=1,2,…,m represents the numbering of the building engineering sub-projects corresponding to each associated heterogeneous data stored in set M, m represents the total number of numbers, X m Y represents the construction technical data of the construction project sub-project numbered m at the selected construction schedule stage. m This represents the construction data for the construction project sub-project numbered m at the selected construction progress stage, where T represents the construction time length corresponding to the selected construction progress stage, max indicates the maximum value, and t... m g represents the end time of the selected construction schedule phase for the construction sub-project numbered m. m p represents the start time of the selected construction schedule phase for the construction sub-project numbered m. m W represents the construction time of a construction sub-project numbered m, as specified in the building requirements, during the selected construction schedule stage. W represents the heterogeneity index of the selected sub-project.

[0023] Furthermore, the abnormal building feature value prediction module acquires the heterogeneity index of the selected engineering sub-project, as well as the heterogeneity index of the building engineering sub-project corresponding to each associated heterogeneous data of the selected engineering sub-project, and based on... Predict abnormal building characteristic values ​​for selected sub-projects, where W j U represents the heterogeneity index of the construction sub-project numbered j. j This represents the influence coefficient between the selected engineering sub-project and the construction engineering sub-project numbered j. It iterates through all construction engineering sub-projects and generates abnormal building characteristic values ​​for each construction engineering sub-project.

[0024] Furthermore, the building engineering quality assessment module includes a risk analysis unit and a building quality assessment unit;

[0025] The risk analysis unit acquires abnormal building characteristic values ​​for each building engineering sub-project. If the abnormal building characteristic value is greater than or equal to a set threshold, the construction parameters of the corresponding building engineering sub-project are retrieved. If the abnormal building characteristic value is less than the set threshold, the construction parameters of the corresponding building engineering sub-project are not retrieved. Based on the retrieved construction parameters, a safety risk assessment model for each building engineering sub-project is constructed. The construction parameters include building construction data, building material consumption, and the effective working time of the construction team.

[0026] The building quality assessment unit obtains the safety risk coefficients of each building project sub-project based on the safety risk assessment model constructed by the risk analysis unit, maps the obtained safety risk coefficients to the range [0,1], and calculates the difference between the value 1 and the mapped value obtained by each safety risk coefficient to obtain the building quality assessment value of each building project.

[0027] Furthermore, the specific method by which the risk analysis unit constructs a safety risk assessment model for each sub-project of the construction project based on the invoked construction parameters is as follows:

[0028] Each construction project sub-project is numbered, and the numbering result is: c=1,2,…,v; v represents the total number of construction project sub-projects obtained by dividing the construction area at the selected construction progress stage.

[0029] Build a security risk assessment model The safety risk coefficient of the construction project sub-project numbered v is predicted, where J v This represents the amount of building materials consumed by the construction project sub-project numbered v during the selected construction schedule phase. This indicates that the construction data Q for the sub-project numbered v of the construction project was completed within the selected construction schedule phase. v The minimum amount of building materials required at that time, Q vW represents the construction data for the construction project sub-project numbered v within the selected construction schedule phase. v G represents the effective working hours of the construction team corresponding to the construction sub-project numbered v within the selected construction progress stage. v This represents the maximum construction data that the construction team corresponding to the construction project sub-project numbered v, obtained according to the construction requirements, can complete per unit of time. hour, ,when hour,

[0030] ,when hour, ,when hour, P v This represents the safety risk coefficient of the construction project sub-project numbered v.

[0031] Furthermore, the construction project management module includes a management priority analysis unit and a construction management unit;

[0032] The management priority analysis unit calculates the absolute value of the difference between the building quality assessment value of the selected engineering sub-project and the value 1. It then calculates the product between the obtained absolute value of the difference and the abnormal building characteristic value of the selected engineering sub-project to obtain the management priority judgment value of the selected engineering sub-project. The unit then traverses all the engineering sub-projects and generates the management priority judgment value of each engineering sub-project. Finally, it determines the management priority of each engineering sub-project in descending order of the management priority judgment value.

[0033] The construction management unit, based on the determined management priority, notifies the construction teams of each sub-project of the construction project to carry out reconstruction of the corresponding sub-project.

[0034] A method for integrating and managing construction project information based on an AI model, the method comprising:

[0035] S10: Based on the building technology data and building construction data of each building engineering sub-project, filter out the heterogeneous data of each building engineering sub-project;

[0036] S20: Find the related heterogeneous data of each construction project sub-project, and integrate the found related heterogeneous data to obtain the heterogeneity index of each construction project sub-project.

[0037] S30: Based on the heterogeneity index of each construction project sub-project, predict the abnormal building characteristic values ​​of each construction project sub-project;

[0038] S40: Based on the abnormal building characteristic values ​​of each building engineering sub-project, selectively retrieve the construction parameters of each building engineering sub-project, and construct a safety risk assessment model for each building engineering sub-project based on the retrieved construction parameters to assess the real-time building quality of each building engineering sub-project.

[0039] S50: Based on the real-time building quality assessment results of each building project sub-project and the abnormal building characteristic values ​​of each building project sub-project, manage the construction status of each building project sub-project.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] 1. This invention uses heterogeneous data from various construction engineering sub-projects to predict the heterogeneity index of each sub-project. The predicted heterogeneity index not only reflects the construction completion status of each sub-project, but also reflects the impact of each sub-project on the construction of other sub-projects, which is beneficial for a comprehensive analysis of abnormal situations in each sub-project.

[0042] 2. Based on the heterogeneous data of each construction project sub-project, this invention predicts the abnormal building characteristic values ​​of each construction project sub-project. Based on the prediction results, it selectively calls the construction parameters of each construction project sub-project, which reduces the workload of the system in integrating construction information and further improves the system's efficiency in integrating information.

[0043] 3. This invention predicts the safety risk coefficients of each sub-project of a construction project by constructing a safety risk assessment model. This process takes into account the construction requirements of each sub-project and the effective working time of each construction team, avoiding the impact of extended construction time caused by factors such as delays in building materials and climate on the prediction results. Based on the prediction results and the abnormal building characteristic values ​​of each sub-project, the reconstruction situation of each sub-project is analyzed, which helps to ensure that the construction project can be rectified in a short time and further improves the system's effectiveness. Attached Figure Description

[0044] Figure 1 This is a schematic diagram illustrating the working principle of an AI-based building engineering information integration management system and method according to the present invention.

[0045] Figure 2 This is a schematic diagram of the workflow of an AI-based building engineering information integration management system and method according to the present invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Example: Figure 1 and Figure 2 As shown, the present invention provides a technical solution for a building engineering information integration management system and method based on an AI model. The building engineering information integration management system based on an AI model includes a building engineering information filtering module, a building engineering information integration module, an abnormal building characteristic value prediction module, a building engineering quality assessment module, and a building engineering management module.

[0048] The building project information filtering module is used to filter out heterogeneous data from each building project sub-project based on the building technology data and building construction data of each building project sub-project.

[0049] The construction project information filtering module includes a partitioning unit and a heterogeneous data filtering unit;

[0050] The construction project area is divided into several sub-projects based on the construction area of ​​each construction team in the selected construction progress stage. A randomly selected sub-project is called a selected sub-project. The selected construction progress stage refers to a random construction progress stage among the various construction progress stages of the construction project. Each sub-project corresponds to a construction team.

[0051] The heterogeneous data filtering unit acquires the construction technology data and construction data of each construction sub-project at the selected construction progress stage. Based on the acquired information, it matches the construction technology data R of the selected sub-project at the selected construction progress stage with the construction data Q of the selected sub-project at the selected construction progress stage. If R≤Q≤R*(1+τ), the match is successful; if R>Q, the match is unsuccessful. The unmatched construction data is taken as the heterogeneous data of the selected sub-project at the selected construction progress stage. Here, τ represents the error coefficient. Construction technology data refers to the construction data formulated according to the construction requirements, and construction data refers to the construction data reported by the construction team. For example, when the construction team corresponding to the selected sub-project works for one day, let the construction technology data be 10 square meters of cement laid, and the construction data be 8 square meters of cement laid. The error coefficient τ=5%. In this case, the construction technology data is greater than the construction data, so the match is unsuccessful, and the construction team fails to complete the construction task.

[0052] The building engineering information integration module is used to find related heterogeneous data of heterogeneous data of various building engineering sub-projects, and to integrate and process the found related heterogeneous data to obtain the heterogeneity index of each building engineering sub-project.

[0053] The building engineering information integration module includes a heterogeneous data search unit and a heterogeneous data integration unit;

[0054] The heterogeneous data association unit searches for related heterogeneous data based on the corresponding construction project sub-projects and the relationships between these sub-projects. Specifically, the search method is as follows: if the influence coefficient U between construction project sub-project A and construction project sub-project B... AB If the value is greater than 0.5, the heterogeneous data corresponding to the construction sub-project B is considered to be related heterogeneous data to the heterogeneous data corresponding to the construction sub-project A; otherwise, the heterogeneous data corresponding to the construction sub-project B is not considered to be related heterogeneous data to the heterogeneous data corresponding to the construction sub-project A.

[0055] When t B -t A When >0, U AB =exp(-(t B -t A ));

[0056] When t B -t A When ≤0, U AB =0;

[0057] Where exp() represents an exponential function with base e and e = 2.72, t A This indicates the end time of sub-project A of the construction project, as defined by the building requirements, at the selected construction schedule stage. B This indicates the start time of the selected construction schedule phase for sub-project B of the construction project, which is formulated according to the building requirements.

[0058] The heterogeneous data integration unit stores the heterogeneous data corresponding to the selected engineering sub-project and the associated heterogeneous data in set M, and predicts the heterogeneity index of the selected engineering sub-project based on set M. The specific prediction formula is as follows:

[0059] ;

[0060] Where q represents the construction time of the selected engineering sub-project in the selected construction progress stage according to the building requirements, j=1,2,…,m represents the numbering of the building engineering sub-projects corresponding to each associated heterogeneous data stored in set M, m represents the total number of numbers, X mY represents the construction technical data of the construction project sub-project numbered m at the selected construction schedule stage. m This represents the construction data for the construction project sub-project numbered m during the selected construction progress stage. T represents the construction time length corresponding to the selected construction progress stage, where T = the end time of the selected construction progress stage - the start time of the selected construction progress stage. max indicates the maximum value. t m g represents the end time of the selected construction schedule phase for the construction sub-project numbered m. m p represents the start time of the selected construction schedule phase for the construction sub-project numbered m. m W represents the construction time of the selected construction schedule stage for the construction sub-project numbered m according to the building requirements; W represents the heterogeneity index of the selected sub-project.

[0061] Traverse all construction sub-projects within the selected construction progress stage and predict the heterogeneity index of each construction sub-project.

[0062] The abnormal building characteristic value prediction module is used to predict the abnormal building characteristic values ​​of each building engineering sub-project based on the heterogeneity index of each building engineering sub-project.

[0063] The abnormal building feature value prediction module acquires the heterogeneity index of the selected engineering sub-project, as well as the heterogeneity index of the corresponding building engineering sub-projects for each associated heterogeneous data of the selected engineering sub-project. Based on the acquired information, according to... Predict abnormal building characteristic values ​​for selected sub-projects, where W j U represents the heterogeneity index of the construction sub-project numbered j. j The influence coefficient between the selected engineering sub-project and the construction engineering sub-project numbered j is represented by H, which represents the abnormal building characteristic value of the selected engineering sub-project. The abnormal building characteristic value of each construction engineering sub-project is generated by traversing all construction engineering sub-projects in the construction engineering sub-projects.

[0064] The building construction quality assessment module selectively retrieves construction parameters for each building construction sub-project based on abnormal building characteristic values, and constructs a safety risk assessment model for each building construction sub-project based on the retrieved construction parameters to assess the real-time building quality of each building construction sub-project.

[0065] The building engineering quality assessment module includes a risk analysis unit and a building quality assessment unit;

[0066] The risk analysis unit acquires abnormal building characteristic values ​​for each construction project sub-project. If the abnormal building characteristic value is greater than or equal to a set threshold, the construction parameters for the corresponding construction project sub-project are retrieved. If the abnormal building characteristic value is less than the set threshold, the construction parameters for the corresponding construction project sub-project are not retrieved. Based on the retrieved construction parameters, a safety risk assessment model for each construction project sub-project is constructed. The specific method is as follows:

[0067] Each construction project sub-project is numbered, and the numbering result is: c=1,2,…,v; v represents the total number of construction project sub-projects obtained by dividing the construction area at the selected construction progress stage.

[0068] Build a security risk assessment model The safety risk coefficient of the construction project sub-project numbered v is predicted, where J v This represents the amount of building materials consumed by the construction project sub-project numbered v during the selected construction schedule phase. This indicates that the construction data Q for the sub-project numbered v of the construction project was completed within the selected construction schedule phase. v The minimum amount of building materials required at that time, Q v W represents the construction data for the construction project sub-project numbered v within the selected construction schedule phase. v G represents the effective working hours of the construction team corresponding to the construction sub-project numbered v within the selected construction progress stage. v This represents the maximum construction data that the construction team corresponding to the construction project sub-project numbered v, obtained according to the construction requirements, can complete per unit of time. hour, ,when hour,

[0069] ,when hour, ,when hour, P v This represents the safety risk coefficient of the construction project sub-project numbered v;

[0070] Construction parameters include building construction data, building material consumption, and the effective working hours of the construction team;

[0071] The building quality assessment unit obtains the safety risk coefficients of each building project sub-project based on the safety risk assessment model constructed by the risk analysis unit, maps the obtained safety risk coefficients to the range [0,1], and calculates the difference between the value 1 and the mapped value obtained by each safety risk coefficient to obtain the building quality assessment value of each building project.

[0072] The construction project management module manages the construction status of each construction project sub-project based on the real-time construction quality assessment results and abnormal construction characteristic values ​​of each construction project sub-project.

[0073] The construction project management module includes a management priority analysis unit and a construction management unit;

[0074] The management priority analysis unit calculates the absolute value of the difference between the building quality assessment value of the selected sub-project and the value 1. It then calculates the product of the obtained absolute value of the difference and the abnormal building characteristic value of the selected sub-project to obtain the management priority judgment value of the selected sub-project. The unit then iterates through all the sub-projects and generates the management priority judgment value for each sub-project. Based on the management priority judgment value in descending order, the management priority of each sub-project is determined, and the sub-projects with the larger management priority judgment value are given priority in management.

[0075] Based on the determined management priority, the construction management unit notifies the construction teams of each sub-project of the construction project to carry out the reconstruction of the corresponding sub-project.

[0076] A method for integrating and managing construction project information based on an AI model, the method comprising:

[0077] S10: Based on the building technology data and building construction data of each building engineering sub-project, filter out the heterogeneous data of each building engineering sub-project;

[0078] S20: Find the related heterogeneous data of each construction project sub-project, and integrate the found related heterogeneous data to obtain the heterogeneity index of each construction project sub-project.

[0079] S30: Based on the heterogeneity index of each construction project sub-project, predict the abnormal building characteristic values ​​of each construction project sub-project;

[0080] S40: Based on the abnormal building characteristic values ​​of each building engineering sub-project, selectively retrieve the construction parameters of each building engineering sub-project, and construct a safety risk assessment model for each building engineering sub-project based on the retrieved construction parameters to assess the real-time building quality of each building engineering sub-project.

[0081] S50: Based on the real-time building quality assessment results of each building project sub-project and the abnormal building characteristic values ​​of each building project sub-project, manage the construction status of each building project sub-project.

[0082] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A building engineering information integration and management system based on an AI model, characterized in that: The system includes a building project information filtering module, a building project information integration module, an abnormal building characteristic value prediction module, a building project quality assessment module, and a building project management module. The building engineering information filtering module is used to filter out heterogeneous data of each building engineering sub-project based on the building technology data and building construction data of each building engineering sub-project; The building engineering information integration module is used to find the related heterogeneous data of each building engineering sub-project, and to integrate the found related heterogeneous data to obtain the heterogeneity index of each building engineering sub-project. The building engineering information integration module includes a heterogeneous data search unit and a heterogeneous data integration unit; The heterogeneous data finding unit searches for related heterogeneous data based on the corresponding construction sub-projects and the relationships between them. Specifically, the searching method is as follows: if the influence coefficient U between construction sub-project A and construction sub-project B... AB If the value is greater than 0.5, the heterogeneous data corresponding to the construction sub-project B is considered to be related heterogeneous data to the heterogeneous data corresponding to the construction sub-project A; otherwise, the heterogeneous data corresponding to the construction sub-project B is not considered to be related heterogeneous data to the heterogeneous data corresponding to the construction sub-project A. When t B -t A When >0, U AB =exp(-(t B -t A )); When t B -t A When ≤0, U AB =0; Where exp() represents an exponential function with base e and e = 2.72, t A This indicates the end time of sub-project A of the construction project, as defined by the building requirements, at the selected construction schedule stage. B This indicates the start time of the selected construction schedule phase for sub-project B of the construction project, which is formulated according to the building requirements. The abnormal building feature value prediction module is used to predict the abnormal building feature values ​​of each building engineering sub-project based on the heterogeneity index of each building engineering sub-project. The construction engineering quality assessment module selectively retrieves construction parameters for each construction engineering sub-project based on abnormal building characteristic values, and constructs a safety risk assessment model for each construction engineering sub-project based on the retrieved construction parameters to assess the real-time construction quality of each construction engineering sub-project. The construction project management module manages the construction status of each construction project sub-project based on the real-time construction quality assessment results and abnormal construction characteristic values ​​of each sub-project.

2. The construction engineering information integration and management system based on an AI model according to claim 1, characterized in that: The building engineering information filtering module includes a partitioning unit and a heterogeneous data filtering unit; The division unit divides the construction area into several construction sub-projects based on the construction area of ​​each construction team at the selected construction progress stage. A randomly selected construction sub-project is called the selected construction sub-project. The heterogeneous data filtering unit acquires the building technology data and building construction data of each building project sub-project at the selected construction progress stage. Based on the acquired information, it matches the building technology data R of the selected project sub-project at the selected construction progress stage with the building construction data Q of the selected project sub-project at the selected construction progress stage. If R≤Q≤R*(1+τ), the match is successful. If R>Q, the match is unsuccessful. The unmatched construction data is taken as the heterogeneous data of the selected project sub-project at the selected construction progress stage, where τ represents the error coefficient.

3. The construction engineering information integration and management system based on an AI model according to claim 2, characterized in that: The heterogeneous data integration unit stores the heterogeneous data corresponding to the selected engineering sub-project and the associated heterogeneous data of the selected engineering sub-project in a set M, and predicts the heterogeneity index of the selected engineering sub-project based on the set M. It then traverses all construction engineering sub-projects within the selected construction progress stage and predicts the heterogeneity index of each construction engineering sub-project.

4. The construction engineering information integration and management system based on an AI model according to claim 3, characterized in that: The specific formula used by the heterogeneous data integration and processing unit to predict the heterogeneity index of selected engineering sub-projects is as follows: ； Where q represents the construction time of the selected engineering sub-project in the selected construction progress stage according to the building requirements, and the building engineering sub-projects corresponding to each associated heterogeneous data stored in set M are numbered, m represents the total number of numbers, and X m Y represents the construction technical data of the construction project sub-project numbered m at the selected construction schedule stage. m This represents the construction data for the construction project sub-project numbered m at the selected construction progress stage, where T represents the construction time length corresponding to the selected construction progress stage, max indicates the maximum value, and t... m g represents the end time of the selected construction schedule phase for the construction sub-project numbered m. m p represents the start time of the selected construction schedule phase for the construction sub-project numbered m. m W represents the construction time of a construction sub-project numbered m, as specified in the building requirements, during the selected construction schedule stage. W represents the heterogeneity index of the selected sub-project.

5. The construction engineering information integration and management system based on an AI model according to claim 4, characterized in that: The abnormal building feature value prediction module obtains the heterogeneity index of the selected engineering sub-project, as well as the heterogeneity index of the building engineering sub-project corresponding to each associated heterogeneous data of the selected engineering sub-project, and based on... Predict abnormal building characteristic values ​​for selected sub-projects, where W j U represents the heterogeneity index of the construction sub-project numbered j. j This represents the influence coefficient between the selected engineering sub-project and the construction engineering sub-project numbered j. It iterates through all construction engineering sub-projects and generates abnormal building characteristic values ​​for each construction engineering sub-project.

6. The construction engineering information integration and management system based on an AI model according to claim 5, characterized in that: The building engineering quality assessment module includes a risk analysis unit and a building quality assessment unit; The risk analysis unit acquires abnormal building characteristic values ​​for each building engineering sub-project. If the abnormal building characteristic value is greater than or equal to a set threshold, the construction parameters of the corresponding building engineering sub-project are retrieved. If the abnormal building characteristic value is less than the set threshold, the construction parameters of the corresponding building engineering sub-project are not retrieved. Based on the retrieved construction parameters, a safety risk assessment model for each building engineering sub-project is constructed. The construction parameters include building construction data, building material consumption, and the effective working time of the construction team. The building quality assessment unit obtains the safety risk coefficients of each building project sub-project based on the safety risk assessment model constructed by the risk analysis unit, maps the obtained safety risk coefficients to the range [0,1], and calculates the difference between the value 1 and the mapped value obtained by each safety risk coefficient to obtain the building quality assessment value of each building project.

7. The construction engineering information integration and management system based on an AI model according to claim 6, characterized in that: The specific method by which the risk analysis unit constructs a safety risk assessment model for each sub-project of the construction project based on the invoked construction parameters is as follows: Each construction project sub-project is numbered, and the numbering result is: c=1,2,…,v; v represents the total number of construction project sub-projects obtained by dividing the construction area at the selected construction progress stage. Build a security risk assessment model The safety risk coefficient of the construction project sub-project numbered v is predicted, where J v This represents the amount of building materials consumed by the construction project sub-project numbered v during the selected construction schedule phase. This indicates that the construction data Q for the sub-project numbered v of the construction project was completed within the selected construction schedule phase. v The minimum amount of building materials required at that time, Q v W represents the construction data for the construction project sub-project numbered v within the selected construction schedule phase. v G represents the effective working hours of the construction team corresponding to the construction sub-project numbered v within the selected construction progress stage. v This represents the maximum construction data that the construction team corresponding to the construction project sub-project numbered v, obtained according to the construction requirements, can complete per unit of time. hour, ,when hour, ,when hour, ,when hour, P v This represents the safety risk coefficient of the construction project sub-project numbered v.

8. The construction engineering information integration and management system based on an AI model according to claim 7, characterized in that: The construction project management module includes a management priority analysis unit and a construction management unit; The management priority analysis unit calculates the absolute value of the difference between the building quality assessment value of the selected engineering sub-project and the value 1. It then calculates the product between the obtained absolute value of the difference and the abnormal building characteristic value of the selected engineering sub-project to obtain the management priority judgment value of the selected engineering sub-project. The unit then traverses all the engineering sub-projects and generates the management priority judgment value of each engineering sub-project. Finally, it determines the management priority of each engineering sub-project in descending order of the management priority judgment value. The construction management unit, based on the determined management priority, notifies the construction teams of each sub-project of the construction project to carry out reconstruction of the corresponding sub-project.

9. A method for integrating and managing building engineering information based on an AI model, applicable to the building engineering information integration and management system based on an AI model as described in any one of claims 1-8, characterized in that: The method includes: S10: Based on the building technology data and building construction data of each building engineering sub-project, filter out the heterogeneous data of each building engineering sub-project; S20: Find the related heterogeneous data of each construction project sub-project, and integrate the found related heterogeneous data to obtain the heterogeneity index of each construction project sub-project. S30: Based on the heterogeneity index of each construction project sub-project, predict the abnormal building characteristic values ​​of each construction project sub-project; S40: Based on the abnormal building characteristic values ​​of each building engineering sub-project, selectively retrieve the construction parameters of each building engineering sub-project, and construct a safety risk assessment model for each building engineering sub-project based on the retrieved construction parameters to assess the real-time building quality of each building engineering sub-project. S50: Based on the real-time building quality assessment results of each building project sub-project and the abnormal building characteristic values ​​of each building project sub-project, manage the construction status of each building project sub-project.

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