A customized method for physical investigation based on a universal index library

Abstract

The present application relates to the technical field of information management of water and electricity engineering, and more particularly to a physical investigation customization method based on a general index library; comprising the following steps: S1, constructing an enterprise-level general index library; S2, comparing project data with the general index library to obtain corresponding codes, forming a project index snapshot, analyzing the project index snapshot, mapping and filling in a survey table template to form a survey table; S3, adding, modifying and disabling the survey table through the project layer; S4, collecting data by a mobile terminal of a field collection personnel, and processing the collected data through a built-in operation model of the mobile terminal; S5, comparing the operation processing result with the latest updated survey table, and filling the operation processing result into the corresponding table of the survey table; S6, publicly announcing and checking the survey table filled with data, data summarizing and outputting results; improving the standardization, accuracy and management efficiency of physical index investigation work.

Description

Technical Field

[0001] This invention relates to the field of information management technology for hydropower projects, and in particular to a customized method for physical surveys based on a general indicator library. Background Technology

[0002] Physical indicator surveys are generally conducted using paper-based questionnaires. Before the survey begins, a site survey is conducted to understand the physical indicators that may be involved within the land acquisition area for project construction. Based on the survey results and compensation standard documents issued by the local government, the survey forms are manually customized using Excel spreadsheets, and blank paper copies are printed in advance. During the site survey, investigators manually fill out the paper questionnaires. After the daily site survey is completed, the data from the paper questionnaires is manually entered into the system or compiled into an electronic spreadsheet. This method is commonly used for physical indicator surveys of hydropower project resettlement, but it has the following problems in practical application: The process of customizing the survey form is cumbersome: Customizing the survey form for each indicator of the project requires first investigating the actual situation of the indicators on site, and then summarizing and screening various compensation standard documents to retain only the indicators related to the current project construction land acquisition scope in the survey form. This process is cumbersome, time-consuming, and easily affected by human experience and oversights in details.

[0003] Difficulty in adjusting the content of the survey form: Since the survey form is based on preliminary investigation, it cannot fully cover all physical indicators of the current project. If any missing indicators are found during the on-site investigation, it is often impossible to adjust or modify them in time, and paper survey forms need to be added, which hinders the on-site investigation work.

[0004] The addition of new indicators is difficult to standardize: each survey team adopts a decentralized approach, lacking real-time information synchronization and a unified management mechanism. This often results in inconsistent naming conventions when different teams add the same indicators, affecting the standardized management and verification of subsequent data.

[0005] The data compilation workload is large: After the on-site survey is completed, the investigators need to enter the data from the paper survey forms into the spreadsheet or system one by one. The manual compilation workload is large and the data is prone to deviation due to personal omissions or input errors, which affects the data quality.

[0006] Inconsistent data versions: The number of physical indicator survey teams varies, ranging from one or two to dozens. Due to the difficulty in real-time communication between the teams, the survey data versions are not updated in a timely manner, and there are inconsistencies or even multiple versions of data from different teams, which increases the difficulty of data collection and review.

[0007] Therefore, there is an urgent need to provide a customized method for physical surveys based on a general indicator library, which can improve the standardization, accuracy, and management efficiency of physical indicator surveys compared to existing technologies. Summary of the Invention

[0008] This invention addresses the technical problems existing in the prior art and provides a customized method for physical surveys based on a general indicator library.

[0009] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for customizing physical surveys based on a universal indicator library includes the following steps: S1. Construct an enterprise-level general indicator library. The general indicator library adopts a hierarchical classification structure, including N-level categories, and each category has a corresponding code. S2. Compare the project data with the general indicator library to obtain the corresponding codes. Create a snapshot of all codes for the project indicators. Set up a survey form template. Parse the snapshot of the project indicators and map it into the survey form template to form the survey form for the project. S3. During the project survey process, the survey form can be modified through the project level, including adding, modifying, and disabling operations; S4. On-site data collection personnel collect data using mobile terminals and process the collected data using the built-in computing model of the mobile terminals. S5. Compare the calculation results with the latest updated questionnaire, and fill the calculation results into the corresponding table of the questionnaire. S6. Publicize and review the survey forms containing the entered data, summarize the data, and output the results.

[0010] Furthermore, S2 specifically includes the following steps: S21. Obtain project data, compare the project data with all categories in the general indicator library, identify the words corresponding to each level of categories in the general indicator library through a semantic analysis model, and integrate the category codes corresponding to the identified words with the comparison time to form a snapshot of project indicators. S22. Set up the survey form template and map the survey form template to the general indicator library; S23. Analyze the project indicator snapshot obtained in step S21, and fill the indicators in the project indicator snapshot into the survey form template; S24. Delete the blank cells in the survey form template that have not been filled in with indicators to form a survey form that is suitable for the project.

[0011] Furthermore, in step S22, the survey form template is based on an Excel spreadsheet. The leftmost column is set as the mapping position for the first-level category, and the first-level category, second-level category, ..., N-level category are mapped from left to right. Each table position is set with a positioning field, which consists of a column letter and a row number, thus forming the survey form template. The positioning field of each table in the survey form template forms a one-to-one mapping relationship with the code of each category in the general indicator library.

[0012] Furthermore, the parsing method for step S23 is as follows: the codes identified from the project are parsed and converted into location fields through a one-to-one mapping relationship with the location fields of the survey form template. Then, the project indicators are filled into the survey form template according to the converted location fields.

[0013] Furthermore, in step S3, when adding a new indicator to the survey form, at the project level, a semantic analysis model is used to compare the new indicator with a general indicator library, identify the indicators that match the new indicator, form the code corresponding to the matching indicator, and integrate the code with the comparison time to form a snapshot of the project indicator. Using the method in step S23, the positioning field of the new indicator in the original survey form template is found. Then, the position of the positioning field of the first-level category of the new indicator is added to the survey form formed in step S24. Finally, the new indicator is added to the survey form according to the found positioning field to form the survey form after adding the new indicator.

[0014] Furthermore, in step S3, when replacing an indicator in the survey form, the indicator to be modified is marked in the survey form. Then, at the project level, a semantic analysis model is used to compare the replacement indicator with a general indicator library, identify the indicator that matches the replacement indicator, form the code corresponding to the matching indicator, and integrate the code with the comparison time to form a project indicator snapshot of the replacement indicator. It is then determined whether the replacement indicator and the replaced indicator are similar indicators. If they are similar indicators, the position of the indicator to be replaced in the survey form is updated to the replacement indicator. Otherwise, the replacement indicator is added to the survey form using the method of adding an indicator.

[0015] Furthermore, in step S3, when replacing indicators in the survey form, the method for determining whether the replacement indicator and the replaced indicator are similar indicators is as follows: remove all indicators except the indicator to be replaced from the original item indicator snapshot to form the item indicator snapshot of the indicator to be replaced; calculate the similarity between the item indicator snapshot of the replacement indicator and the item indicator snapshot of the indicator to be replaced; set a similarity threshold; when the similarity is greater than the similarity threshold, it means that the replacement indicator and the indicator to be replaced are similar indicators; otherwise, it means that the replacement indicator and the indicator to be replaced are not similar indicators.

[0016] Furthermore, in step S3, when an indicator in the survey form is disabled, the indicator to be disabled in the survey form is identified at the project level, the identified indicator is used as the disabled indicator, and it is deleted from the survey form. In subsequent addition or modification operations, the disabled indicator cannot be operated accordingly.

[0017] Furthermore, in step S5, the calculation results of the mobile terminal in step S4 are entered into the latest updated survey form. The data type entered by the mobile terminal is semantically compared with each indicator in the general indicator library to find the indicator that matches the data. The indicator that matches the data is matched with the latest updated survey form. If there is a corresponding relationship in the latest updated survey form, the data is filled into the corresponding table. If there is no corresponding relationship, the survey form is updated using the method of adding indicators in step S3, and the data is entered into the updated survey form.

[0018] Furthermore, in step S1, the first-level category includes multiple lower-level categories, and the indicators of each level category are coded independently.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention is applicable to the survey of physical indicators for resettlement in various hydropower projects. Through customizable design, it meets the actual survey needs of various projects, and is more suitable for projects with complex on-site conditions and numerous indicators. By using technologies such as unified coding management, snapshot mechanism, message queue synchronization and mobile intelligent data collection, it comprehensively improves the standardization, digitization and automation of the survey of physical indicators for resettlement in hydropower projects, significantly reduces manual workload and data error rate, and ensures the consistency and accuracy of survey data throughout the entire process. Attached Figure Description

[0020] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0021] The technical solution of the present invention will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention. It should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description. They do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0022] like Figure 1As shown, this invention provides a method for customizing physical surveys based on a general indicator library, comprising the following steps: S1. Construct an enterprise-level general indicator library. The general indicator library adopts a hierarchical classification structure, including N levels of categories, ordered from 1 to N. Each level of category includes multiple sub-level categories. The indicators of each level of category are coded, and the code of each level of category is unique to ensure consistency and standardization when referencing the code in various projects.

[0023] The classification in the general indicator library uses a hybrid classification method that combines surface classification and line classification. The following example illustrates the specific classification process: The categories include population, housing, decoration, ancillary facilities, land, trees, rural small-scale special facilities, agricultural and sideline facilities, individual industrial and commercial households, and cultural, educational and health facilities. The first-level categories are numbered sequentially from smallest to largest, forming a unique code. For example, population is numbered 1, housing is numbered 2, and other first-level categories are numbered accordingly. Second-level categories are illustrated using trees as an example. Other first-level categories are classified with reference to the second-level categories of trees. The second-level categories of trees are classified according to their uses, including general trees, fruit trees, miscellaneous trees, landscaping trees, shrubs, timber trees, economic trees, and landscaping trees. Third-level categories are illustrated using landscaping trees as an example. The corresponding third-level categories are classified according to specific species, including rosewood and agarwood. Fourth-level categories are classified according to size, including diameter and height. Fifth-level categories are classified according to size range, including 3cm-6cm and 6cm-10cm.

[0024] S2. Based on the project-related physical indicators, obtain the corresponding codes from the general indicator library built in step S1, generate the corresponding code sequence for the project, and thus generate a project indicator snapshot. Then, parse the project indicator snapshot and map it into the survey form template. Specifically, this includes the following steps: S21. Obtain project data, compare the project data with the categories of the general indicator library, and use a semantic analysis model to identify words similar to the categories of the general indicator library from the project data. Then, replace the words identified in the project data with the codes of their corresponding categories. The codes of all replacements in the project form a code sequence. Combine the code sequence with the comparison time to form a snapshot of the project indicators.

[0025] S22. Set up the survey form template and its mapping to the general indicator library. The survey form template is based on an Excel spreadsheet. The leftmost column is set as the mapping position for the first-level category. From left to right, the first-level category, second-level category, ..., N-level category are mapped sequentially. Each table position has a positioning field, which consists of a column letter and a row number, thus forming the survey form template. The positioning field of each table in the survey form template forms a one-to-one mapping relationship with the code of each category in the general indicator library.

[0026] S23. Analyze the snapshot of project indicators formed in step S21. The specific analysis method is as follows: the codes identified from the project are converted into location fields through a one-to-one mapping relationship with the location fields of the survey form template. Then, the project indicators are filled into the survey form template according to the converted location fields.

[0027] S24. Remove blank cells from the survey form template after the item is filled in in step S23. Delete the blank cells in the survey form template that have not been filled in with indicators to form a survey form that matches the item.

[0028] In this step, the questionnaire's location fields are mapped one-to-one with the indicator codes, ensuring that the collected data remains consistent with the standard codes. The questionnaire supports multiple output formats, including Excel, PDF, and mobile spreadsheets, and can be distributed in paper form or directly assigned to the mobile devices of the field survey team, thus significantly improving the efficiency and adaptability of questionnaire generation.

[0029] Project leaders can log into the management system via the web. The web-based management system can automatically execute the steps in this process, generating a dynamic coding sequence. Based on the coding sequence, it generates a corresponding survey template, deletes blank cells to form the corresponding survey form, and creates a more adaptable survey form with higher generation efficiency.

[0030] S3. During the project survey process, the survey forms can be modified through the coding management center, including adding, modifying, and disabling operations, specifically: (1) When it is necessary to add indicators to the survey form, in the project layer, the semantic analysis model is used to compare the new indicators with the general indicator library, identify the indicators that match the new indicators, form the code corresponding to the matching indicators, and integrate the code with the comparison time to form a snapshot of the project indicators. Using the method in step S23, the positioning field of the new indicator in the original survey form template is found. Then, the position of the positioning field of the first-level category of the new indicator is added to the survey form formed in step S24. Then, the new indicator is added to the survey form according to the found positioning field to form the survey form after adding the new indicators.

[0031] (2) When it is necessary to modify the indicators in the survey form, mark the indicators to be modified in the survey form. Then, in the project layer, use the semantic analysis model to compare the replacement indicators with the general indicator library, identify the indicators that match the replacement indicators, match the codes corresponding to the indicators, and integrate the codes with the comparison time to form a snapshot of the project indicators of the replacement indicators. Remove all indicators except the indicators to be replaced from the original snapshot of the project indicators formed in step S21 to form a snapshot of the project indicators to be replaced. Calculate the similarity between the snapshot of the project indicators of the replacement indicators and the snapshot of the project indicators to be replaced, and set a similarity threshold. When the similarity is greater than the similarity threshold, it means that the replacement indicator and the indicators to be replaced are similar indicators. The position of the indicators to be replaced in the survey form can be updated to the replacement indicator. Otherwise, it means that the replacement indicator and the indicators to be replaced are not similar indicators. The indicators to be replaced need to be removed from the survey form. Then, the replacement indicator can be added to the survey form using the method of adding new indicators.

[0032] (3) When it is necessary to disable an indicator in the survey form, the indicator to be disabled in the survey form is identified and marked in the project layer. The marked indicator is used as the disabled indicator and deleted in the survey form. In subsequent addition and modification operations, the disabled indicator cannot be operated accordingly.

[0033] In this step, at the project level, the system can automatically add, delete, and disable indicators in the survey form, automatically generate the updated survey form, and push the latest version of the survey form to the mobile terminal. This ensures that the survey personnel and the field data collectors use the same survey form, achieving good consistency and implementing consistency control.

[0034] S4. On-site data collectors use mobile terminals to collect data. The mobile terminals have offline data collection capabilities to ensure that data collection can be carried out normally regardless of whether there is network coverage. On-site data collectors fill in the measured dimensions, quantities, coefficients and other parameters into the mobile terminals. The mobile terminals use built-in calculation models to process the parameters entered by the on-site data collectors to ensure the continuity of the survey work.

[0035] The following uses parameters from categories such as house area measurement, renovation area measurement, scattered trees, and land as examples to illustrate the specific calculation process of the mobile terminal's computing model: (1) Measurement of building area: Building area = floor height coefficient Bi * length L * width D; Among them, the floor height coefficient Bi is related to the building height h. When h ≥ 2.0m, Bi = 1.0; when 1.8m ≤ h < 2.0m, Bi = 0.8; when 1.5m ≤ h < 1.8m, Bi = 0.6; when 1.2m ≤ h < 1.5m, Bi = 0.4; when h < 1.2m, Bi = 0.

[0036] (2) Measurement of decoration area: Decoration area = length L * width D.

[0037] (3) Scattered trees and land: The sum of the number of scattered trees and land of the same type.

[0038] During data entry, the system can perform real-time data verification based on indicator coding rules. For example, when entering an ID number, it automatically verifies the format's legality and uniqueness. If investigators encounter unpreset indicators (tree species, economic crop categories, etc.) on-site, they can initiate a new indicator application while connected to the internet. This application is immediately uploaded to the management backend via a message queue. After initial review by the project manager, it is automatically submitted to the enterprise-level administrator for approval. Once the process is initiated, the relevant personnel will be notified immediately for approval. After the indicator update is complete, clicking "Synchronize Data" on the terminal will synchronize the latest content in real time and refresh the form fields. Investigators do not need to work on-site at the terminal; they can continue data entry after synchronization, ensuring the real-time nature and continuity of the survey process.

[0039] S5. Enter the calculation results of the mobile terminal in step S4 into the latest updated survey form. Perform semantic comparison between the data type entered by the mobile terminal and each indicator in the general indicator library to find the indicator that matches the data. Match the indicator that matches the data with the latest updated survey form. If there is a corresponding relationship in the latest updated survey form, fill the data into the corresponding table. If there is no corresponding relationship, update the survey form by adding an indicator in step S3 (1) and enter the data into the updated survey form.

[0040] S6. Publicize and review the final survey forms, summarize the data, and output the results.

[0041] During the public notice review process, the system automatically generates public notice documents based on industry standards and local policies, using built-in public notice and summary table templates. If the rights holder has objections to the public notice content, they can submit a review application. If the review application is successful, the survey data will be modified.

[0042] After the data has been publicized and verified, the system automatically generates summary results according to preset summary rules (such as summarizing by household head, summarizing by construction land acquisition scope, summarizing by administrative division, etc.). The results support multiple export formats (Excel, PDF) and are connected to external business systems such as cost management platform and resettlement planning system through data interface to achieve cross-system sharing and linkage.

[0043] The results data are generated entirely based on project indicator snapshots and unified coding, completely eliminating data information deviations caused by version inconsistencies and ensuring data consistency and standardization across projects.

[0044] This invention is applicable to the survey of physical indicators for resettlement in various hydropower projects. Through customizable design, it meets the actual survey needs of various projects, and is more suitable for projects with complex on-site conditions and numerous indicators. By using technologies such as unified coding management, snapshot mechanism, message queue synchronization and mobile intelligent data collection, it comprehensively improves the standardization, digitization and automation of the survey of physical indicators for resettlement in hydropower projects, significantly reduces manual workload and data error rate, and ensures the consistency and accuracy of survey data throughout the entire process.

[0045] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of the present invention do not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A method for customizing physical surveys based on a general indicator library, characterized in that, Includes the following steps: S1. Construct an enterprise-level general indicator library. The general indicator library adopts a hierarchical classification structure, including N-level categories, and each category has a corresponding code. S2. Compare the project data with the general indicator library to obtain the corresponding codes. Create a snapshot of all codes for the project indicators. Set up a survey form template. Parse the snapshot of the project indicators and map it into the survey form template to form the survey form for the project. S3. During the project survey process, the survey form can be modified through the project level, including adding, modifying, and disabling operations; S4. On-site data collection personnel collect data using mobile terminals and process the collected data using the built-in computing model of the mobile terminals. S5. Compare the calculation results with the latest updated questionnaire, and fill the calculation results into the corresponding table of the questionnaire. S6. Publicize and review the survey forms containing the entered data, summarize the data, and output the results.

2. The method for customizing physical surveys based on a general indicator library according to claim 1, characterized in that, S2 specifically includes the following steps: S21. Obtain project data, compare the project data with all categories in the general indicator library, identify the words corresponding to each level of categories in the general indicator library through a semantic analysis model, and integrate the category codes corresponding to the identified words with the comparison time to form a snapshot of project indicators. S22. Set up the survey form template and map the survey form template to the general indicator library; S23. Analyze the project indicator snapshot obtained in step S21, and fill the indicators in the project indicator snapshot into the survey form template; S24. Delete the blank cells in the survey form template that have not been filled in with indicators to form a survey form that is suitable for the project.

3. The method for customizing physical surveys based on a general indicator library according to claim 2, characterized in that, In step S22, the survey form template is based on an Excel spreadsheet. The leftmost column is set as the mapping position for the first-level category, and the first-level category, second-level category, ..., N-level category are mapped from left to right. Each table position is set with a positioning field, which consists of a column letter and a row number, thus forming the survey form template. The positioning field of each table in the survey form template forms a one-to-one mapping relationship with the code of each category in the general indicator library.

4. The method for customizing physical surveys based on a general indicator library according to claim 3, characterized in that, The specific parsing method for step S23 is as follows: the codes identified from the project are parsed and converted into location fields through a one-to-one mapping relationship with the location fields of the survey form template. Then, the project indicators are filled into the survey form template according to the converted location fields.

5. The method for customizing physical surveys based on a general indicator library according to claim 2, characterized in that, In step S3, when a new indicator is added to the survey form, at the project level, a semantic analysis model is used to compare the new indicator with a general indicator library to identify the indicator that matches the new indicator, form the code corresponding to the matching indicator, and integrate the code with the comparison time to form a project indicator snapshot. Using the method in step S23, the positioning field of the new indicator in the original survey form template is found. Then, the position of the positioning field of the first-level category of the new indicator is added to the survey form formed in step S24. Finally, the new indicator is added to the survey form according to the found positioning field to form the survey form after the new indicator is added.

6. The method for customizing physical surveys based on a general indicator library according to claim 5, characterized in that, In step S3, when replacing an indicator in the survey form, the indicator to be modified is marked in the survey form. Then, at the project level, a semantic analysis model is used to compare the replacement indicator with a general indicator library, identify the indicator that matches the replacement indicator, form the code corresponding to the matching indicator, and integrate the code with the comparison time to form a project indicator snapshot of the replacement indicator. It is then determined whether the replacement indicator and the replaced indicator are similar indicators. If they are similar indicators, the position of the indicator to be replaced in the survey form is updated to the replacement indicator. Otherwise, the replacement indicator is added to the survey form using the method of adding an indicator.

7. The method for customizing physical surveys based on a general indicator library according to claim 6, characterized in that, In step S3, when replacing indicators in the survey form, the method for determining whether the replacement indicator and the replaced indicator are similar indicators is as follows: remove all indicators except the indicator to be replaced from the original item indicator snapshot to form the item indicator snapshot of the indicator to be replaced. Calculate the similarity between the item indicator snapshot of the replacement indicator and the item indicator snapshot of the indicator to be replaced. Set a similarity threshold. When the similarity is greater than the similarity threshold, it means that the replacement indicator and the indicator to be replaced are similar indicators; otherwise, it means that the replacement indicator and the indicator to be replaced are not similar indicators.

8. The method for customizing physical surveys based on a general indicator library according to claim 2, characterized in that, In step S3, when an indicator in the survey form is disabled, the indicator to be disabled in the survey form is identified at the project level, the identified indicator is designated as the disabled indicator, and it is deleted from the survey form. Furthermore, in subsequent addition or modification operations, the disabled indicator cannot be modified accordingly.

9. The method for customizing physical surveys based on a general indicator library according to claim 1, characterized in that, In step S5, the calculation results from the mobile terminal in step S4 are entered into the latest updated survey form. The data type entered by the mobile terminal is semantically compared with each indicator in the general indicator library to find the indicator that matches the data. The indicator that matches the data is then matched with the latest updated survey form. If there is a corresponding relationship in the latest updated survey form, the data is filled into the corresponding table. If there is no corresponding relationship, the survey form is updated using the method of adding indicators in step S3, and the data is entered into the updated survey form.

10. A method for customizing physical surveys based on a general indicator library according to claim 1, characterized in that, In step S1, the first-level category includes multiple lower-level categories, and the indicators of each level category are coded independently.

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