A high-standard farmland project management and operation system

Abstract

The present invention relates to the field of agricultural management technology, specifically a high-standard farmland project management and operation system, which includes a project visualization display module, an electronic document management module, a full-process project monitoring module, and a progress and quality management module. In the present invention, by integrating detailed geographical and historical farming data and using time series analysis, the visualization and traceability of the investment dynamics of farmland plots are significantly improved, and the digital management of farmland documents is realized. The incremental calculation and stream data processing framework ensures the real-time update and accuracy of information, improves the degree of data processing automation, and at the same time, the realization of full-process project monitoring enables each key node to be effectively recorded, greatly enhancing the transparency and efficiency of agricultural project management, ensuring quality control at all stages from project establishment to acceptance, helping to discover problems in a timely manner and quickly adjust countermeasures, and greatly reducing the uncertainty and risk in agricultural production.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural management, and in particular to a high-standard farmland project management and operation system. Background Art

[0002] The field of agricultural management technology covers a range of technologies and methods used to optimize agricultural production and resource utilization, including crop planting, harvesting, irrigation, fertilizer management, and pest and disease control. Modern agricultural management technology uses information technology and data analysis tools, such as geographic information systems (GIS), remote sensing technology, and precision agriculture applications to increase crop yields and quality while reducing environmental impacts. Through detailed data collection and analysis, agricultural practitioners can manage land and resources more accurately and achieve refinement and automation of crop planting.

[0003] The high-standard farmland project management and operation system refers to a comprehensive solution used to improve the management efficiency and output results of farmland. It provides real-time agricultural project operation information to agricultural practitioners by integrating advanced monitoring technology, data analysis and resource management tools. Its main purpose is to maximize resource utilization and increase crop yields by optimizing crop planting plans, irrigation systems and fertilizer use. The goal is to reduce waste, improve crop quality and quantity through scientific and technological means, and at the same time protect the environment, bringing the possibility of sustainable development to agricultural production.

[0004] Although existing technologies cover a wide range of agricultural management activities, they generally lack the ability to process real-time data and monitor comprehensive projects. Existing information technology is mostly used for static data analysis in agricultural management, rather than dynamic, real-time decision support, which makes it impossible for agricultural practitioners to respond immediately to sudden environmental changes or operational errors. In addition, existing methods often have delays in document management and data updates, and lack effective real-time data synchronization and processing mechanisms, which affects the efficiency and responsiveness of project management. These technologies limit the ability to efficiently manage resources and optimize crop output, resulting in resource waste and unstable yields. It can be seen that existing technologies need to be improved in ensuring data real-time, enhancing project monitoring capabilities, and improving management automation. These deficiencies may lead to low production efficiency and increased environmental burden. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a high-standard farmland project management and operation system.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: A high-standard farmland project management and operation system comprises:

[0007] The project visualization display module is based on the development history of existing farmland plots, collects the geographical coordinates and historical farming data of farmland plots, draws spatial distribution maps of plots, uses time series analysis to display the investment dynamics of all farmland plots, and generates a dynamic map of plot development;

[0008] The electronic document management module combines the dynamic map of the plot development, scans and digitizes all physical documents associated with the farmland plot, builds metadata indexes to quickly retrieve document content, combines incremental computing and stream data processing frameworks to capture and process data changes in real time, and outputs an electronic archive;

[0009] The full-process project monitoring module uses the electronic archive to track and record all activities of the high-standard farmland project from project establishment to acceptance, update the status of the high-standard farmland project in real time, record key decision points, record the implementation timeline of the farmland project, and form a full-process monitoring record of the project;

[0010] The progress and quality management module analyzes the time deviation and quality indicators of the high-standard farmland project construction phase based on the full monitoring records of the project, adjusts the high-standard farmland project schedule to match the actual progress, reviews the quality assurance measures and compliance of key construction phases, and generates real-time project progress and quality assessment records.

[0011] As a further solution of the present invention, the steps of drawing the spatial distribution map are:

[0012] Based on the development history of existing farmland plots, obtain the geographic coordinates of the farmland plots and apply the formula,

[0013]

[0014] Perform coordinate conversion, match the visualization format, and obtain the adjusted farmland geographic coordinate data, where: represents the original geographic coordinates, is the conversion factor used to convert geographic coordinates to the drawing scale, is the systematic deviation, representing the systematic fixed error, is a random noise parameter, representing the standard deviation of the coordinate data, is the scale parameter for data standardization, representing the random error in data collection;

[0015] Based on the development history of existing farmland plots, access the historical cultivation data of farmland plots and use the formula,

[0016]

[0017] Perform data cleaning, filter abnormal data, and obtain the cleaned farmland cultivation history data, among which, represents the original farming data, and are the mean and standard deviation of the tillage data, is the threshold value;

[0018] The adjusted farmland geographic coordinate data and the cleaned farmland cultivation history data are integrated, and the formula is applied:

[0019]

[0020] The spatial distribution map is drawn by GIS software, where: represents the intensity value of the target farmland plot, Represents the adjusted farmland geographic coordinate data, Represents the cleaned historical data of farmland cultivation. Represents the natural exponential function.

[0021] As a further solution of the present invention, the steps for obtaining the dynamic map of land development are:

[0022] Based on the spatial distribution map, the historical investment records of each farmland plot are extracted and the formula is applied.

[0023]

[0024] Get farmland plot investment data ,in, The plot is in The development data of farmland plots at the moment is used to increase the influence of the square adjustment data. is a regression analysis parameter used to measure the direct impact of land development data on investment. is a constant term, representing the basic investment level

[0025] According to the farmland plot investment data , combined with time series analysis, trend forecasting and periodicity analysis, applying formulas,

[0026]

[0027] Processing nonlinear effects, we get the time series analysis results, where Represents the predicted investment dynamics, and is a parameter determined by time series analysis, is a tuning parameter used to enhance the effect of the difference. is the first-order difference value of the farmland plot investment data;

[0028] The time series analysis results are integrated with the spatial distribution map, and Tableau graphic dynamic display software is used to generate a dynamic map of land plot development.

[0029] As a further solution of the present invention, the steps of constructing the metadata index are:

[0030] Combined with the plot development dynamic map, a scanner is used to scan all physical documents associated with the farmland plot project, and each document is identified by the formula

[0031]

[0032] Convert to digital form and obtain digital documents ,in, For the The pixel data of the page, is the noise disturbance parameter, which reflects the random error in the scanning process and increases the random noise to simulate the scanning uncertainty. is the number of document pages;

[0033] Performing image recognition and text extraction on the digitized documents, calculating the text clarity of each document,

[0034]

[0035] Output the farmland project document content, including: Represents the average recognition accuracy of the document, Indicates The recognition accuracy of characters, is the expected mean recognition accuracy, is the total number of characters;

[0036] Classify and index the contents of the farmland project documents, using the formula,

[0037]

[0038] Get the metadata index, where Represents the metadata index, is the weight factor, It is The tag set for the class document, is a tuning parameter used to balance the impact of labels. Indicates the total number of document categories.

[0039] As a further solution of the present invention, the output step of the electronic archive library is:

[0040] Retrieve documents based on the metadata index, apply the formula,

[0041]

[0042] Indicates the relevance of the search results. The frequency of occurrence of keywords,

[0043] According to the search results, combined with the incremental calculation framework, the document data is updated in real time, using the formula,

[0044]

[0045] Output updated document data, where: The number of data records affected by the update operation, is the update frequency, is the data change amount, For the previous document data, To change the sensitivity parameter;

[0046] The updated document data is stored in the database, and the formula is used.

[0047]

[0048] Output electronic archive, where To accumulate the amount of data processed and stored, is the data integrity coefficient, For the Update data, is the data distortion rate.

[0049] As a further solution of the present invention, the steps for forming the project full-process monitoring record are:

[0050] According to the electronic archive, the project-related activity data is extracted and the formula is used.

[0051]

[0052] Output farmland project activity data, where: Represents active record data, is the frequency of the activity, indicating the number of times the activity occurs. is the activity priority, is the uncertainty coefficient of the activity, which is used to adjust the sensitivity of the activity record;

[0053] Based on the farmland project activity data, update the project status in real time and record each key decision point, using formulas,

[0054]

[0055] Get the farmland project status update record, where: It is a new state. It's the old state. is the state change, is the decision sensitivity parameter, which affects the sensitivity of state update;

[0056] According to the farmland project activity data, the project time changes are analyzed and the formula is used.

[0057]

[0058] Get the farmland project time data record, where: It is The timestamp of the activity, is the project start time, is the activity interval, is the adjustment factor for the activity, affecting the calculation of the time interval;

[0059] The farmland project status update record and farmland project time data record are recorded using the formula:

[0060]

[0061] Merge and generate the whole process monitoring record of the project, including: is the total data of monitoring records, and They are activity record data, status update data, and quality control data. It is the decay coefficient of each data, which is used to adjust the influence of old data.

[0062] As a further solution of the present invention, the steps of analyzing the time deviation and the quality index are:

[0063] According to the full monitoring records of the project, the construction phase time data and the quality score of the construction phase are collected and integrated, and the formula is used.

[0064]

[0065] Generate a time deviation dataset where Indicates The time deviation of an activity, Indicates the actual completion time. Indicates the planned completion time. represents the error term, which is used to adjust the bias sensitivity;

[0066] According to the time deviation data set, the causes and trends of the time deviation are analyzed, and the formula is used.

[0067]

[0068] Output mean time deviation ,in, Indicates activity importance adjustment parameters to enhance the distinction of importance of difference activity deviations,

[0069] According to the quality score of the construction stage, the quality control data is analyzed and the formula is used.

[0070]

[0071] Output average quality index ,in, It is Quality rating of each construction phase, is the quality adjustment coefficient,

[0072] As a further solution of the present invention, the steps for obtaining the real-time progress and quality assessment records of the project are:

[0073] Based on the average time deviation , adjust the timetable of the high-standard farmland project and adopt a formula,

[0074]

[0075] Output an adjusted schedule where, Indicates the adjusted planned time. Indicates the current planned time. represents the time adjustment factor, represents the smoothing adjustment parameter;

[0076] According to the average quality index , review the quality assurance measures of high-standard farmland projects, using the formula,

[0077]

[0078] Output quality review results, including: Based on the average quality index Adjusted compliance score, Represents the compliance adjustment factor, which is used to adjust the flexibility of the compliance score. represents the compliance weight factor;

[0079] Combining the adjusted schedule and quality review results, applying the formula,

[0080]

[0081] Output real-time project progress and quality assessment records, including: It is a comprehensive score of high-standard farmland projects that integrates time and quality. Represents the total number of activities, indicating the number of activities referenced in the analysis.

[0082] Compared with the prior art, the advantages and positive effects of the present invention are:

[0083] In the present invention, by integrating detailed geographical and historical farming data and applying time series analysis, the visualization and traceability of investment dynamics of farmland plots are significantly improved, the digital management of farmland documents is realized, and the incremental computing and streaming data processing framework are adopted to ensure the real-time updating and accuracy of information, improve the degree of automation of data processing, and enhance the instant response capability. At the same time, the implementation of full-process project monitoring enables each key node to be effectively recorded, greatly enhancing the transparency and efficiency of agricultural project management, ensuring quality control at all stages from project establishment to acceptance, helping to discover problems in a timely manner and quickly adjust countermeasures, greatly reducing the uncertainty and risk in agricultural production. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 is a system flow chart of the present invention;

[0085] Figure 2 A flow chart for drawing a spatial distribution map of the present invention;

[0086] Figure 3 A flowchart for obtaining a dynamic map of land plot development according to the present invention;

[0087] Figure 4 A flowchart for constructing a metadata index of the present invention;

[0088] Figure 5 It is an output flow chart of the electronic archive of the present invention;

[0089] Figure 6 A flow chart for forming the monitoring record of the entire project of the present invention;

[0090] Figure 7 It is a flow chart of the analysis of time deviation and quality index of the present invention;

[0091] Figure 8 The present invention is a flowchart for obtaining real-time progress and quality assessment records of the project. DETAILED DESCRIPTION

[0092] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0093] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. Example

[0094] See also Figure 1 , a high-standard farmland project management and operation system includes:

[0095] The project visualization display module is based on the development history of existing farmland plots, collects the geographical coordinates and historical farming data of farmland plots, draws spatial distribution maps of plots, uses time series analysis to display the investment dynamics of all farmland plots, and generates a dynamic map of plot development;

[0096] The electronic document management module combines the dynamic map of land development, scans and digitizes all physical documents associated with farmland plots, builds metadata indexes to quickly retrieve document content, combines incremental computing and stream data processing frameworks to capture and process data changes in real time, and outputs electronic archives;

[0097] The full-process project monitoring module uses an electronic archive to track and record all activities of the high-standard farmland project from project establishment to acceptance, update the status of the high-standard farmland project in real time, record key decision points, record the implementation timeline of the farmland project, and form a full-process monitoring record of the project;

[0098] The progress and quality management module analyzes the time deviation and quality indicators of the high-standard farmland project construction phase based on the full project monitoring records, adjusts the high-standard farmland project schedule to match the actual progress, reviews the quality assurance measures and compliance of key construction phases, and generates real-time project progress and quality assessment records.

[0099] The dynamic map of land development includes farmland plot location information, historical change records and investment trend analysis results. The electronic archive includes document index, data update log and change tracking records. The full project monitoring records include activity logs, decision records and quality review documents. The real-time project progress and quality assessment records include progress comparison results, quality inspection results and a list of adjustment measures.

[0100] See also Figure 2 , the steps for drawing the spatial distribution map are:

[0101] Based on the development history of existing farmland plots, obtain the geographic coordinates of the farmland plots and apply the formula,

[0102]

[0103] Perform coordinate conversion, match the visualization format, and obtain the adjusted farmland geographic coordinate data, where: represents the original geographic coordinates, is the conversion factor used to convert geographic coordinates to the drawing scale, is the systematic deviation, representing the systematic fixed error, is a random noise parameter, representing the standard deviation of the coordinate data, is the scale parameter for data standardization, representing the random error in data collection;

[0104] Based on the development history of existing farmland plots, access the historical cultivation data of farmland plots and use the formula,

[0105]

[0106] Perform data cleaning, filter abnormal data, and obtain the cleaned farmland cultivation history data, among which, represents the original farming data, and are the mean and standard deviation of the tillage data, is the threshold value;

[0107] Integrate the adjusted farmland geographic coordinate data and the cleaned farmland cultivation history data, and apply the formula:

[0108]

[0109] The spatial distribution map is drawn by GIS software, where: represents the intensity value of the target farmland plot, Represents the adjusted farmland geographic coordinate data, Represents the cleaned historical data of farmland cultivation. Represents the natural exponential function.

[0110] Assume the following data:

[0111] : Assume the value is 100 (unit: longitude and latitude);

[0112] : Assuming the value is 1.5, it is used to convert geographic coordinates to a scale suitable for drawing;

[0113] : Assumed to be 5, representing a systematic fixed error;

[0114] : Assumed to be 10, it represents the standard deviation of the coordinate data;

[0115] : Assumed to be 3, representing the random error in data collection;

[0116] First calculate the multiplication:

[0117]

[0118] Adding systematic bias:

[0119]

[0120] Evaluate the terms in the denominator:

[0121]

[0122] Complete the division operation:

[0123]

[0124] Final Result , this value is the converted geographic coordinate suitable for drawing. In the spatial distribution map, the coordinates of each point are converted into such values ​​that can be directly used for graphical display, maintaining the relative position and scale of the original data while adjusting to the scale accepted by the visualization software.

[0125] Assumptions:

[0126] : Original farming history data, assuming the value is 200 (unit: jin / mu);

[0127] : The average value of the tillage data, assumed to be 180;

[0128] : The standard deviation of the tillage data is assumed to be 20;

[0129] : Threshold, set to 1, used to filter data;

[0130] Calculate the deviation:

[0131]

[0132] Normalize:

[0133]

[0134] calculate :

[0135]

[0136] Determine whether it is greater than :

[0137]

[0138] Therefore this data point is valid.

[0139] Outliers and inconsistent data were screened out, and only historical farming data that met the threshold requirements were retained to ensure data quality and consistency, making them suitable for further analysis.

[0140] Assumptions ,calculate .

[0141] Calculate the denominator:

[0142]

[0143] This evaluates the entire expression:

[0144]

[0145] Final calculation:

[0146]

[0147] The final result , indicating the intensity or importance of the target plot in the plot, which may be used for color coding or size variation to highlight the importance of specific attributes such as farming intensity or geographical location.

[0148] See also Figure 3 , the steps to obtain the dynamic map of land development are:

[0149] Based on the spatial distribution map, the historical investment records of each farmland plot are extracted and the formula is applied.

[0150]

[0151] Get farmland plot investment data ,in, The plot is in The development data of farmland plots at the moment is used to increase the influence of the square adjustment data. is a regression analysis parameter used to measure the direct impact of land development data on investment. is a constant term, representing the basic investment level

[0152] According to the farmland plot investment data , combined with time series analysis, trend forecasting and periodicity analysis, applying formulas,

[0153]

[0154] Processing nonlinear effects, we get the time series analysis results, where Represents the predicted investment dynamics, and is a parameter determined by time series analysis, is a tuning parameter used to enhance the effect of the difference. is the first-order difference value of the farmland plot investment data;

[0155] Integrate the time series analysis results with the spatial distribution map, and use Tableau graphic dynamic display software to generate a dynamic map of land development.

[0156] Assumptions:

[0157] : The assumed value is 0.8, which is used to measure the direct impact of land development data on investment;

[0158] :The plot is in The development data at the moment is assumed to be 50 (unit: RMB 10,000);

[0159] : Assumed to be 10, representing the basic investment level;

[0160] : The square of the development data, used for adjustment influence;

[0161] Compute the product:

[0162]

[0163] Add the constant term:

[0164]

[0165] Evaluate the terms in the denominator:

[0166]

[0167] Complete the division operation:

[0168]

[0169] Final Result Represents the level of investment adjusted for development data. Its value is close to 1, indicating that despite the increase in development activity, its impact on total investment remains at a relatively stable level after square adjustment.

[0170] Assumptions:

[0171] and : Parameters determined by time series analysis, with assumed values ​​of 0.5 and 0.3 respectively;

[0172] : From the above calculation, ;

[0173] : The first-order difference of the investment data, assumed to be 5 (the change from the previous moment);

[0174] : The assumed value is 0.2, which is used to strengthen the influence of the difference;

[0175] calculate:

[0176]

[0177]

[0178] Evaluate the terms in the denominator:

[0179]

[0180] Complete the division operation:

[0181]

[0182] Final Result Represents the adjusted forecast investment dynamics. This low value reflects the limitation of the impact of investment growth on total investment under given parameter settings.

[0183] See also Figure 4 , the steps to build the metadata index are:

[0184] Combined with the plot development dynamic map, a scanner is used to scan all physical documents associated with the farmland plot project. Each document is identified by the formula

[0185]

[0186] Convert to digital form and obtain digital documents ,in, For the The pixel data of the page, is the noise disturbance parameter, which reflects the random error in the scanning process and increases the random noise to simulate the scanning uncertainty. is the number of document pages;

[0187] Perform image recognition and text extraction on digitized documents and calculate the text clarity of each document.

[0188]

[0189] Output the farmland project document content, including: Represents the average recognition accuracy of the document, Indicates The recognition accuracy of characters, is the expected mean recognition accuracy, is the total number of characters;

[0190] Classify and index the contents of farmland project documents, using formulas,

[0191]

[0192] Get the metadata index, where Represents the metadata index, is the weight factor, It is The tag set for the class document, is a tuning parameter used to balance the impact of labels. Indicates the total number of document categories.

[0193] Assumptions:

[0194] : No. The average value of the pixel data of the page, assuming it is 2000 pixels;

[0195] Assuming 100, it represents the noise level, reflecting the random errors in the scanning process;

[0196] : The total number of pages in the document, assuming it is 50 pages;

[0197] Calculate the sum of the square of the pixel data and the noise of each page. For each page, calculate:

[0198]

[0199] Sum and average the results for all pages:

[0200]

[0201] Average results:

[0202]

[0203] Represents the average digitized value of each document page after taking into account the scanning error. This result shows that the scanning system is able to digitize documents with high accuracy and the error effect is very small.

[0204] Assumptions:

[0205] : No. The recognition accuracy of characters is assumed to be 0.95;

[0206] : Expected mean recognition accuracy, assumed to be 0.9;

[0207] : Total number of characters, assuming the document has 1000 characters in total;

[0208] Compute the absolute value of the accuracy difference for each character:

[0209]

[0210] Sum and average:

[0211]

[0212] It represents the average deviation of each character from the expected recognition accuracy. A small deviation value indicates that most characters are close to perfect recognition.

[0213] Assumptions:

[0214] : Weight factor, assuming that for all The values ​​are all 1;

[0215] : No. The label set of the class document, assuming that the number of labels for each class is 10;

[0216] : Adjustment parameter to balance the influence of labels, assumed to be 0.5;

[0217] : The total number of document categories, assumed to be 5;

[0218] Calculate the weighted value of the influence of each class label:

[0219]

[0220] Sum:

[0221]

[0222] Represents the total value of the metadata index, which indicates that the document content has been effectively classified and indexed, and the impact of each category has been considered evenly.

[0223] See also Figure 5, the output steps of the electronic archive are:

[0224] Retrieve documents based on metadata index, apply formula,

[0225]

[0226] Indicates the relevance of the search results. The frequency of occurrence of keywords,

[0227] According to the search results, combined with the incremental calculation framework, the document data is updated in real time, using the formula,

[0228]

[0229] Output updated document data, where: The number of data records affected by the update operation, is the update frequency, is the data change amount, For the previous document data, To change the sensitivity parameter;

[0230] Store the updated document data into the database, using the formula:

[0231]

[0232] Output electronic archive, where To accumulate the amount of data processed and stored, is the data integrity coefficient, For the Update data, is the data distortion rate.

[0233] Assumptions:

[0234] : Document relevance scoring, for keywords , assuming it is 0.8;

[0235] : The first The frequency of occurrence of a keyword, assuming there are 3 mentions in the query;

[0236] Keyword rarity index, which affects the keyword weight, is assumed to be 2;

[0237] The total number of keywords included in the query, assuming it is 5 keywords;

[0238] Calculate the weighted relevance of each keyword, for each keyword j:

[0239]

[0240] Weighted Relevance Score:

[0241]

[0242] Sum relevance scores:

[0243]

[0244] Calculate the total frequency of occurrence:

[0245]

[0246] Complete the division operation:

[0247]

[0248] Represents the relevance ratio of the overall search results, indicating the degree of match between the search results and the query. A lower value may indicate the need to optimize the search keywords or improve the relevance score of the keywords.

[0249] Assumptions:

[0250] : Update frequency, assuming it is once an hour, set to 1;

[0251] : Data change amount, assuming that this change involves 10 records;

[0252] : Previous document data, assuming there are 200 records previously;

[0253] : Change the sensitivity parameter, which affects the update impact, assuming it is 0.5;

[0254] Calculate update impact:

[0255]

[0256] App update frequency:

[0257]

[0258] Represents the number of data records affected by the update operation, reflecting the real-time change of data under the update frequency. This result is used for further processing and storage in the electronic archive.

[0259] Assumptions:

[0260] : Data integrity coefficient, for each update, assumed to be 0.95;

[0261] :The data updated each time is 4000 by the above calculation;

[0262] : Data distortion rate, assumed to be 0.1;

[0263] : Number of updates, assuming 10 updates;

[0264] Calculate the effective amount of data for each update, for each update i:

[0265]

[0266] Apply the integrity factor and sum:

[0267] Weighted data volume:

[0268]

[0269] Total data volume:

[0270]

[0271] It represents the cumulative amount of data processed and stored in the electronic archive after considering data integrity and distortion. The results show that the archive effectively integrates real-time updated data while maintaining high data integrity.

[0272] See also Figure 6 The steps for forming the project monitoring record are as follows:

[0273] According to the electronic archive, extract project-related activity data and use the formula:

[0274]

[0275] Output farmland project activity data, where: Represents active record data, is the frequency of the activity, indicating the number of times the activity occurs. is the activity priority, is the uncertainty coefficient of the activity, which is used to adjust the sensitivity of the activity record;

[0276] Based on the farmland project activity data, the project status is updated in real time and each key decision point is recorded. Using formulas,

[0277]

[0278] Get the farmland project status update record, where: It is a new state. It's the old state. is the state change, is the decision sensitivity parameter, which affects the sensitivity of state update;

[0279] According to the farmland project activity data, the project time changes were analyzed and the formula was used.

[0280]

[0281] Get the farmland project time data record, where: It is The timestamp of the activity, is the project start time, is the activity interval, is the adjustment factor for the activity, affecting the calculation of the time interval;

[0282] The farmland project status update record and farmland project time data record are recorded using the formula:

[0283]

[0284] Merge and generate the whole process monitoring record of the project, including: is the total data of monitoring records, and They are activity record data, status update data, and quality control data. It is the decay coefficient of each data, which is used to adjust the influence of old data.

[0285] Assume that for a high-standard farmland project:

[0286] (meaning the activity occurs 4 times a week);

[0287] (Activity priority is 3, which is higher);

[0288] (The uncertainty coefficient of the activity is 0.5, indicating that there is a certain amount of variation);

[0289] calculate :

[0290]

[0291] calculate :

[0292]

[0293] calculate :

[0294]

[0295] calculate :

[0296]

[0297] Comprehensive calculation :

[0298]

[0299] Indicates that after considering frequency, priority and uncertainty, the comprehensive weight of this activity is , which means that the activity has a greater impact on the monitoring of high-standard farmland projects and should receive more attention.

[0300] Assumptions:

[0301] (Project original status score);

[0302] (The status has improved);

[0303] (The decision-making sensitivity parameter is small, and the impact of state changes on the project is relatively stable);

[0304] calculate :

[0305]

[0306] calculate :

[0307]

[0308] calculate :

[0309]

[0310] calculate :

[0311]

[0312] The new status score of 22.62 reflects a modest improvement in the status of the high-standard farmland project and enhances the project's overall performance.

[0313] Assumptions:

[0314] (The project starts on day 0);

[0315] (There is a 7-day interval between each activity);

[0316] (The activity interval adjustment factor is 0.2);

[0317] calculate :

[0318]

[0319] calculate :

[0320]

[0321] calculate :

[0322]

[0323] Assume there are 3 activities, then,

[0324]

[0325] It indicates that the third activity occurs around the 18th day of the project, which helps to plan and monitor the timeline of the high-standard farmland project more accurately.

[0326] Assumptions:

[0327] (a high-quality event);

[0328] (The quality attenuation factor is small);

[0329] (Total 10 activities);

[0330] calculate :

[0331]

[0332] calculate :

[0333]

[0334] calculate :

[0335]

[0336] Indicates that the comprehensive monitoring record value of the entire project is , high values ​​reflect the good performance and close monitoring of high-standard farmland projects in multiple dimensions (activity frequency, status, and quality).

[0337] See also Figure 7 , the analysis steps of time deviation and quality indicators are:

[0338] According to the monitoring records of the whole project, the construction phase time data and the quality score of the construction phase are collected and integrated, and the formula is used.

[0339]

[0340] Generate a time deviation dataset where Indicates The time deviation of an activity, Indicates the actual completion time. Indicates the planned completion time. ;

[0341] According to the time deviation data set, the causes and trends of time deviation are analyzed, and the formula is used.

[0342]

[0343] Output mean time deviation ,in, Indicates activity importance adjustment parameters to enhance the distinction of importance of difference activity deviations,

[0344] According to the quality scores of the construction stage, the quality control data is analyzed and the formula is used.

[0345]

[0346] Output average quality index ,in, It is Quality rating of each construction phase, is the quality adjustment coefficient,

[0347] Assume that in a high-standard farmland project,

[0348] : Actual completion time, assuming that an activity is actually completed on the 10th day;

[0349] : Planned completion time, assuming that the activity is planned to be completed on the 8th day;

[0350]

[0351] Compute the square of the time difference:

[0352]

[0353] Add the error adjustment term:

[0354]

[0355] Compute the root of the time deviation:

[0356]

[0357] This means that after taking into account the error adjustment, the time deviation of this activity is 2.45 days. This means that the actual completion time is 2.45 days later than planned, indicating that there may be efficiency problems or the plan is too tight.

[0358] Assumptions:

[0359] : The time deviation of a single activity is 2.45 according to the above calculation;

[0360] : Activity importance adjustment parameter. Assume that the parameter of important activities is 0.1 and that of less important activities is 0.05. If there are 3 activities, the parameters are ;

[0361] : Total number of activities, assumed to be 3;

[0362] Calculate the weighted deviation:

[0363] Activity 1:

[0364] Activity 2:

[0365] Activity 3:

[0366] Sum:

[0367]

[0368] Calculate the average:

[0369]

[0370] It indicates that the average time deviation is 2.262 days, which is the result after considering the importance of the activities. It reflects that the project is generally delayed and the reasons need to be further investigated and measures should be taken.

[0371] Assumptions:

[0372] : The quality score of each construction stage. Assume that the quality scores of the three stages are ;

[0373] : Quality adjustment parameters, reflecting the quality volatility of each stage, assuming that the parameters are ;

[0374]

[0375] Calculate the weighted mass:

[0376] Phase 1:

[0377] Phase 2:

[0378] Phase 3:

[0379] Sum:

[0380]

[0381] Calculate the average:

[0382]

[0383] This means that after considering the quality adjustment parameters, the average quality score is 66.86. This score may indicate that there are some quality issues that require further investigation and improvement measures.

[0384] See also Figure 8 , the steps to obtain the real-time progress and quality assessment records of the project are:

[0385] Based on mean time deviation , adjust the timetable of the high-standard farmland project and adopt a formula,

[0386]

[0387] Output an adjusted schedule where, Indicates the adjusted planned time. Indicates the current planned time. represents the time adjustment factor, represents the smoothing adjustment parameter;

[0388] According to the average quality index , review the quality assurance measures of high-standard farmland projects, using the formula,

[0389]

[0390] Output quality review results, including: Based on the average quality index Adjusted compliance score, Represents the compliance adjustment factor, which is used to adjust the flexibility of the compliance score. represents the compliance weight factor;

[0391] Combining the adjusted schedule with the quality review results, applying the formula,

[0392]

[0393] Output real-time project progress and quality assessment records, including: It is a comprehensive score of high-standard farmland projects that integrates time and quality. .

[0394] Assume that in a high-standard farmland project,

[0395] : The current planned time, assuming that the current planned completion date of a key activity is the 15th day;

[0396] : The average time deviation obtained by the above calculation is 2.262 days;

[0397] : Time adjustment coefficient, assumed to be 0.5, is used to adjust the impact of deviation on the schedule;

[0398] : Smoothing adjustment parameter, assumed to be 1, used to reduce the impact of extreme deviations;

[0399] Compute the sum of squared deviations and a smoothing term:

[0400]

[0401] Calculate the root:

[0402]

[0403] Calculate the new planned time:

[0404]

[0405] The adjusted planned time is around the 16th day of the project. This adjustment helps the project schedule better synchronize with the actual progress and reduces the risk of project delays.

[0406] Assumptions:

[0407] : The average quality index obtained by the above calculation is 66.86;

[0408] : Compliance weight factor, assumed to be 1.2, emphasizes the importance of quality;

[0409] : Compliance adjustment coefficient, assumed to be 0.1, used to adjust the flexibility of compliance scoring;

[0410] Calculate the adjusted compliance denominator:

[0411]

[0412] Calculate the compliance score:

[0413]

[0414] Represents the adjusted compliance score, which reflects the overall compliance level of the project quality measures, indicating that the quality assurance in the implementation of the project meets the expected standards.

[0415] Assumptions:

[0416] : The adjusted planned schedule is 16.24 calculated from the above;

[0417] : The compliance score of each activity. Suppose there are 3 activities, and their compliance scores are ;

[0418]

[0419] Calculate the product of the time and quality score for each activity:

[0420] Activity 1:

[0421] Activity 2:

[0422] Activity 3:

[0423] Compute the sum of these products:

[0424]

[0425] Calculate the average:

[0426]

[0427] It represents the comprehensive value of the real-time progress and quality assessment records of the high-standard farmland project obtained by integrating the adjusted time and quality scores of each activity. The score value provides a quantitative indicator for the management of the high-standard farmland project, helping managers evaluate the overall execution quality of the project and the efficiency of time management.

[0428] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A high-standard farmland project management and operation system, characterized in that: The system comprises: The project visualization display module is based on the development history of existing farmland plots, collects the geographical coordinates and historical farming data of farmland plots, draws the spatial distribution map of the plots, uses time series analysis to display the investment dynamics of all farmland plots, and generates a plot development dynamic map; The electronic document management module combines the dynamic map of the plot development, scans and digitizes all physical documents associated with the farmland plot, builds metadata indexes to quickly retrieve document content, combines incremental computing and stream data processing frameworks to capture and process data changes in real time, and outputs an electronic archive; The full-process project monitoring module uses the electronic archive to track and record all activities of the high-standard farmland project from project establishment to acceptance, update the status of the high-standard farmland project in real time, record key decision points, record the implementation timeline of the farmland project, and form a full-process monitoring record of the project; The progress and quality management module analyzes the time deviation and quality indicators of the high-standard farmland project construction phase according to the full monitoring records of the project, adjusts the high-standard farmland project schedule to match the actual progress, reviews the quality assurance measures and compliance of the key construction phases, and generates real-time project progress and quality assessment records; The steps for constructing the metadata index are: Combined with the plot development dynamic map, a scanner is used to scan all physical documents associated with the farmland plot project, and each document is identified by the formula Convert to digital form and obtain digital documents ,in, For the The pixel data of the page, is the noise disturbance parameter, which reflects the random error in the scanning process and increases the random noise to simulate the scanning uncertainty. is the number of document pages; Performing image recognition and text extraction on the digitized documents, calculating the text clarity of each document, Output the farmland project document content, including: Represents the average recognition accuracy of the document, Indicates The recognition accuracy of characters, is the expected mean recognition accuracy, is the total number of characters; Classify and index the contents of the farmland project documents, using the formula, Get the metadata index, where Represents the metadata index, is the weight factor, It is The tag set for the class document, is a tuning parameter used to balance the impact of labels. Indicates the total number of document categories; The output steps of the electronic archive are: Retrieve documents based on the metadata index, apply the formula, Output the search results, where Indicates the relevance of the search results. Score document relevance, For the search query The frequency of occurrence of keywords, is the keyword rarity index; According to the search results, combined with the incremental calculation framework, the document data is updated in real time, using the formula, Output updated document data, where: The number of data records affected by the update operation, is the update frequency, is the data change amount, For the previous document data, To change the sensitivity parameter; The updated document data is stored in the database, and the formula is used. Output electronic archive, where To accumulate the amount of data processed and stored, is the data integrity coefficient, For the Update data, is the data distortion rate.

2. The high-standard farmland project management and operation system according to claim 1 is characterized by: The steps of drawing the spatial distribution map are: Based on the development history of existing farmland plots, obtain the geographic coordinates of the farmland plots and apply the formula, Perform coordinate conversion, match the visualization format, and obtain the adjusted farmland geographic coordinate data, where: represents the original geographic coordinates, is the conversion factor used to convert geographic coordinates to the drawing scale, is the systematic deviation, representing the systematic fixed error, is a random noise parameter, representing the standard deviation of the coordinate data, is the scale parameter for data standardization, representing the random error in data collection; Based on the development history of existing farmland plots, access the historical cultivation data of farmland plots and use the formula, Perform data cleaning, filter abnormal data, and obtain the cleaned farmland cultivation history data, among which, represents the original farming data, and are the mean and standard deviation of the tillage data, is the threshold value; The adjusted farmland geographic coordinate data and the cleaned farmland cultivation history data are integrated, and the formula is applied: The spatial distribution map is drawn by GIS software, where: represents the intensity value of the target farmland plot, Represents the adjusted farmland geographic coordinate data, Represents the cleaned historical data of farmland cultivation. Represents the natural exponential function.

3. The high-standard farmland project management and operation system according to claim 2 is characterized in that: The steps for obtaining the plot development dynamic map are as follows: Based on the spatial distribution map, the historical investment records of each farmland plot are extracted and the formula is applied. Get farmland plot investment data ,in, The plot is in The development data of farmland plots at the moment is used to increase the influence of the square adjustment data. is a regression analysis parameter used to measure the direct impact of land development data on investment. is a constant term, representing the basic investment level; According to the farmland plot investment data , combined with time series analysis, trend forecasting and periodicity analysis, applying formulas, Processing nonlinear effects, we get the time series analysis results, where Represents the predicted investment dynamics, and is a parameter determined by time series analysis, is a tuning parameter used to enhance the effect of the difference. is the first-order difference value of the farmland plot investment data; The time series analysis results are integrated with the spatial distribution map, and Tableau graphic dynamic display software is used to generate a dynamic map of land plot development.

4. The high-standard farmland project management and operation system according to claim 1 is characterized in that: The steps for forming the project's full-process monitoring record are as follows: According to the electronic archive, the project-related activity data is extracted and the formula is used. Output farmland project activity data, where: Represents active record data, is the frequency of the activity, indicating the number of times the activity occurs. is the activity priority, is the uncertainty coefficient of the activity, which is used to adjust the sensitivity of the activity record; Based on the farmland project activity data, update the project status in real time and record each key decision point, using formulas, Get the farmland project status update record, where: It is a new state. It's the old state. is the state change, is the decision sensitivity parameter, which affects the sensitivity of state update; According to the farmland project activity data, the project time changes are analyzed and the formula is used. Get the farmland project time data record, where: It is The timestamp of the activity, is the project start time, is the activity interval, is the adjustment factor for the activity, affecting the calculation of the time interval; The farmland project status update record and farmland project time data record are recorded using the formula: Merge and generate the whole process monitoring record of the project, including: is the total data of monitoring records, and They are activity record data, status update data, and quality control data. It is the decay coefficient of each data, which is used to adjust the influence of old data.

5. The high-standard farmland project management and operation system according to claim 1 is characterized in that: The analysis steps of the time deviation and quality index are as follows: According to the full monitoring records of the project, the construction phase time data and the quality score of the construction phase are collected and integrated, and the formula is used. Generate a time deviation dataset where Indicates The time deviation of an activity, Indicates the actual completion time. Indicates the planned completion time. ; According to the time deviation data set, the causes and trends of the time deviation are analyzed, and the formula is used. Output mean time deviation ,in, Indicates activity importance adjustment parameters to enhance the distinction of importance of difference activity deviations, Total number of representative activities; According to the quality score of the construction stage, the quality control data is analyzed and the formula is used. Output average quality index ,in, It is Quality rating of each construction phase, is the quality adjustment coefficient, 6. The high-standard farmland project management and operation system according to claim 5 is characterized by: The steps for obtaining the real-time progress and quality assessment records of the project are as follows: Based on the average time deviation , adjust the timetable of high-standard farmland projects, adopt a formula, Output an adjusted schedule where, Indicates the adjusted planned time. Indicates the current planned time. represents the time adjustment factor, represents the smoothing adjustment parameter; According to the average quality index , review the quality assurance measures of high-standard farmland projects, using the formula, Output quality review results, including: Based on the average quality index Adjusted compliance score, Represents the compliance adjustment factor, which is used to adjust the flexibility of the compliance score. represents the compliance weight factor; Combining the adjusted schedule and quality review results, applying the formula, Output real-time project progress and quality assessment records, including: It is a comprehensive score of high-standard farmland projects that integrates time and quality. Represents the total number of activities, indicating the number of activities referenced in the analysis.

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