Intelligent management system for green building supervision engineering

Abstract

The invention discloses an intelligent management system for green building supervision engineering, and belongs to the technical field of engineering management. The method is used for solving the technical problems of poor local supervision reliability analysis effect and poor overall supervision reliability analysis and management effect of green building supervision in an existing scheme. Performing data analysis, digital representation and combination on supervision implementation states corresponding to a plurality of supervision data items associated with all supervision indexes implemented by the supervisor to obtain a supervision implementation supervision table; corresponding local supervision reliability data processing and analysis are carried out on different supervision indexes according to a supervision implementation supervision table obtained through earlier-stage processing; and performing overall supervision reliability data calculation on all supervision indexes supervised by the supervisor according to a local supervision reliability processing sequence obtained through earlier-stage processing to obtain a supervision overall abnormal state identifier corresponding to the supervisor, performing data analysis on the supervision overall abnormal state identifier, and adaptively performing dynamic management on supervision of the supervisor.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering management, and in particular to an intelligent management system for green building supervision engineering. Background Art

[0002] Green building supervision project refers to the process in which a professional supervision unit or individual supervises and manages the implementation of a project in accordance with relevant laws and regulations, green building standards and contract requirements during the construction of a building project. Through green supervision throughout the entire process, the application of green building technology can be effectively promoted, ensuring that construction projects meet the standards of the green building evaluation system and ultimately achieving the goal of energy conservation and emission reduction.

[0003] When implementing the existing green building supervision project management plan, it is unable to conduct local supervision reliability analysis on different aspects of green building construction supervision, and determine the corresponding overall supervision reliability status according to the results of local supervision reliability analysis on different aspects. It is also unable to dynamically manage the subsequent supervision implementation of the supervision implementer according to the overall supervision reliability status, resulting in poor local supervision reliability analysis results of green building supervision itself, as well as poor overall supervision reliability analysis and management results. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent management system for green building supervision projects, which is used to solve the technical problems of poor local supervision reliability analysis and poor overall supervision reliability analysis and management effects in green building supervision itself in existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An intelligent management system for green building supervision engineering, including a green building supervision local work supervision module, is used to count all supervision data items and supervision results corresponding to different supervision indicators in the process of supervision of green building construction by the supervision party and digitally process and combine them to obtain a supervision implementation supervision table and upload it to a supervision engineering management platform; the supervision implementation supervision table is obtained by sorting and combining the indicator implementation supervision processing sub-tables corresponding to different supervision indicators;

[0007] The green building supervision local work evaluation module is used to implement the local supervision reliability analysis corresponding to different supervision indicators according to the supervision implementation supervision table, and sort and combine the local supervision reliability analysis results corresponding to different supervision indicators to obtain the local supervision reliability processing sequence and upload it to the supervision project management platform; the local supervision reliability processing sequence is obtained by sorting and combining the supervision abnormality degrees of different indicators corresponding to different supervision indicators;

[0008] The green building supervision overall work evaluation module is used to implement overall supervision reliability analysis on all supervision indicators supervised by the supervisor according to the local supervision reliability processing sequence, and dynamically manage the supervision of the supervisor according to the overall supervision reliability analysis results.

[0009] Preferably, all supervision indicators that the supervision party supervises during the green building construction process are obtained and marked as first identification marks respectively, and all supervision data items corresponding to different supervision indicators are obtained in sequence and marked as second identification marks respectively;

[0010] And, obtaining the supervision results corresponding to different supervision data items and marking them as verification marks respectively;

[0011] Sort and combine all second identification identifiers associated with the first identification identifier and the corresponding verification identifiers to obtain an indicator implementation supervision sub-table corresponding to the corresponding supervision indicator;

[0012] When the indicator implementation supervision sub-table of different supervision indicators is digitally processed, the verification identifiers associated with different second identification identifiers in the indicator implementation monitoring table are analyzed by the supervision implementation reliable identification function, and the corresponding supervision implementation identifier BSi is output; i is a different verification identifier, i=1, 2, 3, ..., n; n is a positive integer;

[0013] The supervision implementation flag contains a value of 0 or 1, indicating whether the supervision implementation of the corresponding supervision data item is reliable or unreliable;

[0014] The supervision implementation identifications obtained by processing all verification identifications in the indicator implementation supervision table are associated and updated with their corresponding verification identifications to obtain the indicator implementation supervision processing sub-table;

[0015] The indicator implementation supervision processing sub-tables corresponding to all supervision indicators are sorted and combined to obtain the supervision implementation supervision table.

[0016] Preferably, the expression of the reliable identification function implemented by the supervisor is: Wherein, JGi is the different verification marks in the indicator implementation monitoring table; JG0i is the standard supervision result corresponding to the different verification marks in the indicator implementation monitoring table.

[0017] Preferably, the indicator implementation supervision processing subtable corresponding to different supervision indicators in the supervision implementation supervision table is obtained. When performing local supervision reliability analysis corresponding to different supervision indicators, the indicator implementation supervision processing subtables of different supervision indicators are traversed respectively to obtain the second identification identifier belonging to the different supervision implementation identifiers with a value of 1, and marked as the second abnormal identification identifier;

[0018] Analyze the total number of supervision implementation marks with a value of 1 corresponding to the supervision index;

[0019] If the total number of supervision implementation identifiers with a value of 1 is 0, a normal supervision instruction is generated and the corresponding supervision indicator is marked as a reliable supervision indicator, and the supervision abnormality of the indicator corresponding to the reliable supervision indicator is set to 0;

[0020] Otherwise, a supervision exception instruction is generated and the corresponding supervision indicator is marked as an abnormal supervision indicator. According to the abnormal supervision indicator, all the second abnormal identification identifiers obtained by traversal are traversed and matched with the preset supervision data item weight table to obtain the supervision implementation weights corresponding to different second abnormal identification identifiers.

[0021] Preferably, all the second abnormal identification marks obtained by the supervision index processing and their corresponding supervision implementation weights are calculated by the formula Calculate and obtain the corresponding indicator supervision abnormality BY; where JQj is the supervision implementation weight corresponding to different second abnormal identification identifiers; j is the different second abnormal identification identifiers associated with the abnormal supervision indicator, j = 1, 2, 3, ..., m; m is a positive integer, which is the total number of all second abnormal identification identifiers; N is the total number of all second identification identifiers associated with the abnormal supervision indicator; B is the indicator supervision abnormality classification value;

[0022] Conduct data analysis on the indicator supervision abnormality to determine the abnormal supervision status corresponding to the abnormal supervision indicator.

[0023] Preferably, if the indicator supervision abnormality is -1, an abnormal supervision low impact instruction is generated and prompted;

[0024] If the indicator supervision abnormality is -2, an abnormal supervision high impact instruction is generated and prompted;

[0025] The supervision anomaly degrees of different indicators corresponding to all supervision indicators are sorted and combined to obtain a reliable processing sequence for local supervision.

[0026] Preferably, when the overall supervision reliability analysis is performed on all supervision indicators supervised by the supervision party, the local supervision reliability processing sequence is traversed, and the total number of first anomalies N1 with a value of -1 and the total number of second anomalies N2 with a value of -2 are counted respectively;

[0027] If the total number of the first anomaly and the total number of the second anomaly are both 0, the overall reliability status of the supervision is generated and the existing supervision is maintained for the supervision party;

[0028] If the total number of first anomalies and / or the total number of second anomalies is not 0, the first overall supervision formula Calculate and obtain the first supervision overall abnormality ZY1 corresponding to the supervision party; where ZY1 and ZY2 are the index supervision abnormality coefficients with a value of -1 and -2, respectively. The index supervision abnormality coefficient is

[0029] Preferably, through the second overall regulatory formula Calculate and obtain the second supervision overall abnormality ZY2 corresponding to the supervision party; where a1 and a2 are different calculation weight coefficients, and 0<a1<a2; NZ is the total number of all supervision indicators.

[0030] Preferably, the first supervision overall abnormality and the second supervision overall abnormality obtained by calculation are calculated by the formula Calculate and obtain the supervision overall abnormal state identification BZ corresponding to the supervision party; where max(*) is a function that takes the maximum value of two values; A is the overall abnormal classification value of supervision;

[0031] Conduct data analysis on the overall abnormal status identification of supervision and adaptively manage the supervision of the supervision party dynamically.

[0032] Preferably, if the overall abnormal state indicator of the supervision is 0, a slight overall abnormal state of the supervision is generated and prompted, and at the same time, the first management plan is implemented for the supervision of the supervision party;

[0033] If the overall abnormal state of supervision is marked as 0, an overall severe abnormal state of supervision is generated and prompted, and at the same time, the second management plan is implemented for the supervision of the supervisor.

[0034] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0035] The present invention obtains indicator implementation supervision processing sub-tables corresponding to different supervision indicators by performing data analysis, digital representation and combination on the supervision implementation status corresponding to several supervision data items associated with all supervision indicators implemented by the supervision party, and processes and combines the indicator implementation supervision processing sub-tables corresponding to all supervision indicators to obtain a supervision implementation supervision table, which can not only realize data analysis and digital representation of different supervision data items, but also provide reliable local supervision analysis data support for subsequent local supervision reliability analysis corresponding to different supervision indicators.

[0036] The present invention processes and analyzes the local supervision reliability data corresponding to different supervision indicators according to the supervision implementation supervision table obtained in the previous processing, and obtains the supervision abnormality corresponding to different supervision indicators. It realizes the digital representation of the abnormal supervision status corresponding to the individual supervision indicator, and can also provide reliable supervision data support for the overall supervision reliability analysis corresponding to all supervision indicators supervised by the subsequent supervision party, thereby improving the local supervision reliability analysis effect of the green building supervision itself.

[0037] The present invention implements overall supervision reliability data calculation for all supervision indicators supervised by the supervisor according to the local supervision reliability processing sequence obtained in the previous processing, obtains the overall abnormal state identification of supervision corresponding to the supervisor, and analyzes the data of the overall abnormal state identification of supervision and adaptively manages the supervision of the supervisor, thereby improving the overall supervision reliability analysis effect and management effect of green building supervision. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The present invention will be further described below in conjunction with the accompanying drawings.

[0039] Figure 1 The present invention is a flowchart of the operation of a green building supervision project intelligent management system.

[0040] Figure 2 It is a flowchart of implementing corresponding local supervision reliability analysis for different supervision indicators in the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0042] like Figure 1 As shown, the present invention is an intelligent management system for green building supervision engineering, including a green building supervision local work supervision module, a green building supervision local work evaluation module, a green building supervision overall work evaluation module and a supervision engineering management platform;

[0043] The green building supervision local work supervision module is used to count all supervision data items and supervision results corresponding to different supervision indicators in the green building construction process supervised by the supervision party and digitally process and combine them to obtain the supervision implementation supervision table and upload it to the supervision project management platform; including:

[0044] Obtain all supervision indicators that the supervision party supervises during the green building construction process and mark them as first identification marks respectively, and sequentially obtain all supervision data items corresponding to different supervision indicators and mark them as second identification marks respectively;

[0045] It should be noted that different supervision indicators are associated with several supervision data items; specific supervision indicators include but are not limited to progress indicators, quality indicators, cost indicators and safety indicators; several specific supervision data items associated with different supervision indicators can be determined based on the existing supervision implementation plan, and can also be added, deleted and modified according to the actual application scenario;

[0046] And, obtaining the supervision results corresponding to different supervision data items and marking them as verification marks respectively;

[0047] Sort and combine all second identification identifiers associated with the first identification identifier and the corresponding verification identifiers to obtain an indicator implementation supervision sub-table corresponding to the corresponding supervision indicator;

[0048] When the indicator implementation supervision sub-table of different supervision indicators is digitally processed, the verification identifiers associated with different second identification identifiers in the indicator implementation monitoring table are analyzed by the supervision implementation reliable identification function, and the corresponding supervision implementation identifier BSi is output; i is a different verification identifier, i=1, 2, 3, ..., n; n is a positive integer;

[0049] Among them, the expression of the reliable identification function implemented by the supervisor is: Where, JGi is the different verification marks in the indicator implementation monitoring table; JG0i is the standard supervision result corresponding to the different verification marks in the indicator implementation monitoring table, and the standard supervision result is determined according to the existing supervision requirement data;

[0050] It should be noted that the supervision implementation identifier is used to digitally represent the supervision implementation status corresponding to different supervision data items of different supervision indicators;

[0051] The supervision implementation flag contains a value of 0 or 1, indicating whether the supervision implementation of the corresponding supervision data item is reliable or unreliable;

[0052] The supervision implementation identifications obtained by processing all verification identifications in the indicator implementation supervision table are associated and updated with their corresponding verification identifications to obtain the indicator implementation supervision processing sub-table;

[0053] Sort and combine the indicator implementation supervision processing sub-tables corresponding to all supervision indicators to obtain the supervision implementation supervision table;

[0054] In an embodiment of the present invention, by performing data analysis and digitally representing and combining the supervision implementation status corresponding to several supervision data items associated with all supervision indicators implemented by the supervision party, an indicator implementation supervision processing sub-table corresponding to different supervision indicators is obtained, and the indicator implementation supervision processing sub-tables corresponding to all supervision indicators are processed and combined to obtain a supervision implementation supervision table, which can not only realize data analysis and digital representation of different supervision data items, but also provide reliable local supervision analysis data support for subsequent local supervision reliability analysis corresponding to different supervision indicators.

[0055] The green building supervision local work evaluation module is used to implement the corresponding local supervision reliability analysis for different supervision indicators according to the supervision implementation supervision table, and sort and combine the local supervision reliability analysis results corresponding to different supervision indicators to obtain the local supervision reliability processing sequence and upload it to the supervision project management platform; including:

[0056] like Figure 2 As shown, the indicator implementation supervision processing subtable corresponding to different supervision indicators in the supervision implementation supervision table is obtained. When the local supervision reliability analysis corresponding to different supervision indicators is implemented, the indicator implementation supervision processing subtables of different supervision indicators are traversed respectively to obtain the second identification identifier belonging to the different supervision implementation identifiers with a value of 1, and marked as the second abnormal identification identifier;

[0057] Analyze the total number of supervision implementation marks with a value of 1 corresponding to the supervision index;

[0058] If the total number of supervision implementation identifiers with a value of 1 is 0, a normal supervision instruction is generated and the corresponding supervision indicator is marked as a reliable supervision indicator, and the supervision abnormality of the indicator corresponding to the reliable supervision indicator is set to 0;

[0059] Otherwise, a supervision abnormality instruction is generated and the corresponding supervision indicator is marked as an abnormal supervision indicator. According to the abnormal supervision indicator, all the second abnormality identification identifiers obtained by traversal are traversed and matched with the preset supervision data item weight table to obtain the supervision implementation weights corresponding to different second abnormality identification identifiers;

[0060] It should be explained that the supervision data item weight table is pre-set with a number of different sample second identification identifiers and their corresponding supervision implementation weights. The supervision implementation weights are used to digitize and differentiate the supervision implementation impacts corresponding to the sample second identification identifiers. The specific values ​​of different supervision implementation weights can be determined by professional and technical personnel in this field based on work experience and work requirements, or can be determined based on the total number of abnormalities that have occurred in the corresponding history;

[0061] In the embodiment of the present invention, by performing data analysis on the total number of supervision implementation identifications to determine the corresponding marks, reliable analysis data support can be provided for the subsequent processing and analysis of all second abnormal identification identifications;

[0062] All the second abnormal identification marks obtained by the supervision index processing and their corresponding supervision implementation weights are calculated through the formula Calculate and obtain the corresponding indicator supervision abnormality BY; where JQj is the supervision implementation weight corresponding to different second abnormal identification identifiers; j is the different second abnormal identification identifiers associated with the abnormal supervision indicator, j=1, 2, 3, ..., m; m is a positive integer, which is the total number of all second abnormal identification identifiers; N is the total number of all second identification identifiers associated with the abnormal supervision indicator; B is the indicator supervision abnormality classification value, which can be determined according to the median value of the indicator supervision abnormality corresponding to all historical second abnormal identification identifiers;

[0063] It should be noted that the indicator supervision abnormality is used to perform data calculation on the abnormal supervision data corresponding to all the second abnormal identification marks obtained by abnormal supervision indicator processing to digitally represent its abnormal supervision status;

[0064] Conduct data analysis on the abnormality of indicator supervision to determine the abnormal supervision status corresponding to the abnormal supervision indicator;

[0065] If the indicator supervision abnormality is -1, an abnormal supervision low impact instruction is generated and prompted;

[0066] If the indicator supervision abnormality is -2, an abnormal supervision high impact instruction is generated and prompted;

[0067] The supervision abnormality degrees of different indicators corresponding to all supervision indicators are sorted and combined to obtain a reliable processing sequence for local supervision;

[0068] In the embodiment of the present invention, the local supervision reliability data processing and analysis corresponding to different supervision indicators are implemented according to the supervision implementation supervision table obtained in the previous processing, and the supervision abnormality corresponding to different supervision indicators is obtained. While realizing the digital representation of the abnormal supervision status corresponding to the individual supervision indicator, it can also provide reliable supervision data support for the overall supervision reliability analysis corresponding to all supervision indicators supervised by the subsequent supervision party, thereby improving the local supervision reliability analysis effect of the green building supervision itself.

[0069] The green building supervision overall work evaluation module is used to perform overall supervision reliability analysis on all supervision indicators supervised by the supervisor according to the local supervision reliability processing sequence, and dynamically manage the supervision of the supervisor according to the overall supervision reliability analysis results; including:

[0070] When the overall supervision reliability analysis is performed on all supervision indicators supervised by the supervision party, the local supervision reliability processing sequence is traversed, and the total number of first anomalies N1 with a value of -1 and the total number of second anomalies N2 with a value of -2 are counted respectively;

[0071] If the total number of the first anomaly and the total number of the second anomaly are both 0, the overall reliability status of the supervision is generated and the existing supervision is maintained for the supervision party;

[0072] If the total number of first anomalies and / or the total number of second anomalies is not 0, the first overall supervision formula Calculate and obtain the first supervision overall abnormality ZY1 corresponding to the supervision party; where ZY1 and ZY2 are the index supervision abnormality coefficients with a value of -1 and -2, respectively. The index supervision abnormality coefficient is

[0073] and, through the second overall regulatory formula Calculate and obtain the second supervision overall abnormality ZY2 corresponding to the supervision party; where a1 and a2 are different calculation weight coefficients, and 0<a1<a2, the specific value is not limited, and can be customized according to the actual application requirements of the actual application scenario; NZ is the total number of all supervision indicators;

[0074] It should be noted that the first overall abnormality of supervision and the second overall abnormality of supervision are used to calculate the overall supervision reliability data of abnormal supervision data corresponding to all abnormal supervision indicators supervised by the supervisor from different aspects, so as to digitally represent the corresponding overall abnormal state of supervision;

[0075] The first supervision overall abnormality and the second supervision overall abnormality obtained by calculation are calculated by formula Calculate and obtain the supervision overall abnormal state identification BZ corresponding to the supervision party; where max(*) is a function that takes the maximum value of two values; A is the overall abnormal classification value of supervision, which can be determined according to the actual application requirements of the actual application scenario, or according to the median value of all the overall abnormal degrees of supervision corresponding to all historical supervision parties;

[0076] It should be noted that the overall abnormal state identification of supervision is used to digitally represent the overall abnormal state of supervision corresponding to all abnormal supervision indicators supervised by the supervisor;

[0077] Conduct data analysis on the overall abnormal status identification of supervision and adaptively manage the supervision of the supervision party dynamically;

[0078] If the overall abnormal state indicator of the supervision is 0, a slight overall abnormal state of the supervision is generated and prompted, and at the same time, the first management plan is implemented for the supervision of the supervision party;

[0079] If the overall abnormal status indicator of the supervision is 0, the overall severe abnormal status of the supervision is generated and prompted, and the second management plan is implemented for the supervision of the supervision party;

[0080] Specifically, the first management plan may be to implement targeted local supervision rectification management for all abnormal supervision indicators supervised by the supervision party;

[0081] The second management plan can be specific in that it can implement comprehensive overall supervision rectification management on all supervision indicators supervised by the supervision party.

[0082] In the embodiment of the present invention, the overall supervision reliability data calculation is implemented for all supervision indicators supervised by the supervisor according to the local supervision reliability processing sequence obtained in the previous processing, and the overall supervision abnormal state identification corresponding to the supervisor is obtained. By performing data analysis on the overall supervision abnormal state identification and adaptively managing the supervision of the supervisor, the overall supervision reliability analysis effect and management effect of green building supervision are improved.

[0083] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0084] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0085] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0086] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0087] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A green building supervision project intelligent management system, characterized in that: It includes a green building supervision local work supervision module, which is used to count all supervision data items and supervision results corresponding to different supervision indicators in the green building construction process supervised by the supervision party and digitally process and combine them to obtain the supervision implementation supervision table and upload it to the supervision project management platform; the supervision implementation supervision table is obtained by sorting and combining the indicator implementation supervision processing sub-tables corresponding to different supervision indicators; The green building supervision local work evaluation module is used to implement the local supervision reliability analysis corresponding to different supervision indicators according to the supervision implementation supervision table, and sort and combine the local supervision reliability analysis results corresponding to different supervision indicators to obtain the local supervision reliability processing sequence and upload it to the supervision project management platform; the local supervision reliability processing sequence is obtained by sorting and combining the supervision abnormality degrees of different indicators corresponding to different supervision indicators; The green building supervision overall work evaluation module is used to implement overall supervision reliability analysis on all supervision indicators supervised by the supervisor according to the local supervision reliability processing sequence, and dynamically manage the supervision of the supervisor according to the overall supervision reliability analysis results.

2. According to claim 1, a green building supervision project intelligent management system is characterized in that: Obtain all supervision indicators that the supervision party supervises during the green building construction process and mark them as first identification marks respectively, and sequentially obtain all supervision data items corresponding to different supervision indicators and mark them as second identification marks respectively; And, obtaining the supervision results corresponding to different supervision data items and marking them as verification marks respectively; Sort and combine all second identification identifiers associated with the first identification identifier and the corresponding verification identifiers to obtain an indicator implementation supervision sub-table corresponding to the corresponding supervision indicator; When the indicator implementation supervision sub-table of different supervision indicators is digitally processed, the verification identifiers associated with different second identification identifiers in the indicator implementation monitoring table are analyzed by the supervision implementation reliable identification function, and the corresponding supervision implementation identifier BSi is output; i is a different verification identifier, i=1, 2, 3, ..., n; n is a positive integer; The supervision implementation flag contains a value of 0 or 1, indicating whether the supervision implementation of the corresponding supervision data item is reliable or unreliable; The supervision implementation identifications obtained by processing all verification identifications in the indicator implementation supervision table are associated and updated with their corresponding verification identifications to obtain the indicator implementation supervision processing sub-table; The indicator implementation supervision processing sub-tables corresponding to all supervision indicators are sorted and combined to obtain the supervision implementation supervision table.

3. According to claim 2, a green building supervision project intelligent management system is characterized in that: The expression of the reliable identification function for supervision implementation is: Wherein, JGi is the different verification marks in the indicator implementation monitoring table; JG0i is the standard supervision result corresponding to the different verification marks in the indicator implementation monitoring table.

4. According to claim 2, a green building supervision project intelligent management system is characterized in that: Obtain the indicator implementation supervision processing subtable corresponding to different supervision indicators in the supervision implementation supervision table. When performing local supervision reliability analysis corresponding to different supervision indicators, traverse the indicator implementation supervision processing subtables of different supervision indicators respectively, obtain the second identification identifier belonging to different supervision implementation identifiers with a value of 1, and mark them as the second abnormal identification identifier; Analyze the total number of supervision implementation marks with a value of 1 corresponding to the supervision index; If the total number of supervision implementation identifiers with a value of 1 is 0, a normal supervision instruction is generated and the corresponding supervision indicator is marked as a reliable supervision indicator, and the supervision abnormality of the indicator corresponding to the reliable supervision indicator is set to 0; Otherwise, a supervision exception instruction is generated and the corresponding supervision indicator is marked as an abnormal supervision indicator. According to the abnormal supervision indicator, all the second abnormal identification identifiers obtained by traversal are traversed and matched with the preset supervision data item weight table to obtain the supervision implementation weights corresponding to different second abnormal identification identifiers.

5. The green building supervision project intelligent management system according to claim 4 is characterized in that: All the second abnormal identification marks obtained by the supervision index processing and their corresponding supervision implementation weights are calculated through the formula Calculate and obtain the corresponding indicator supervision abnormality BY; Where JQj is the supervision implementation weight corresponding to different second abnormality identification marks; j is a different second abnormality identification mark associated with the abnormal supervision indicator, j=1, 2, 3, ..., m; m is a positive integer, which is the total number of all second abnormal identification identifiers; N is the total number of all second identification identifiers associated with the abnormal supervision index; B is the index supervision abnormal classification value; Conduct data analysis on the indicator supervision abnormality to determine the abnormal supervision status corresponding to the abnormal supervision indicator.

6. The green building supervision project intelligent management system according to claim 5 is characterized in that: If the indicator supervision abnormality is -1, an abnormal supervision low impact instruction is generated and prompted; If the indicator supervision abnormality is -2, an abnormal supervision high impact instruction is generated and prompted; The supervision anomaly degrees of different indicators corresponding to all supervision indicators are sorted and combined to obtain a reliable processing sequence for local supervision.

7. The green building supervision project intelligent management system according to claim 6 is characterized in that: When the overall supervision reliability analysis is performed on all supervision indicators supervised by the supervision party, the local supervision reliability processing sequence is traversed, and the total number of first anomalies N1 with a value of -1 and the total number of second anomalies N2 with a value of -2 are counted respectively; If the total number of the first anomaly and the total number of the second anomaly are both 0, the overall reliability status of the supervision is generated and the existing supervision is maintained for the supervision party; If the total number of first anomalies and / or the total number of second anomalies is not 0, the first overall supervision formula Calculate and obtain the first supervision overall abnormality ZY1 corresponding to the supervision party; where ZY1 and ZY2 are the index supervision abnormality coefficients with a value of -1 and -2, respectively. The index supervision abnormality coefficient is 8. The green building supervision project intelligent management system according to claim 7 is characterized in that: Through the second overall regulatory formula Calculate and obtain the second supervision overall abnormality ZY2 corresponding to the supervision party; where a1 and a2 are different calculation weight coefficients, and 0<a1<a2; NZ is the total number of all supervision indicators.

9. The green building supervision project intelligent management system according to claim 8, characterized in that: The first supervision overall abnormality and the second supervision overall abnormality obtained by calculation are calculated by formula Calculate and obtain the supervision overall abnormal state identification BZ corresponding to the supervision party; where max(*) is a function that takes the maximum value of two values; A is the overall abnormal classification value of supervision; Conduct data analysis on the overall abnormal status identification of supervision and adaptively manage the supervision of the supervision party dynamically.

10. The green building supervision project intelligent management system according to claim 9, characterized in that: If the overall abnormal state indicator of the supervision is 0, a slight overall abnormal state of the supervision is generated and prompted, and at the same time, the first management plan is implemented for the supervision of the supervision party; If the overall abnormal state of supervision is marked as 0, an overall severe abnormal state of supervision is generated and prompted, and at the same time, the second management plan is implemented for the supervision of the supervisor.

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