A Dynamic Evaluation Method and System for the Construction of Sanitary Cities Based on Multi-Source Data Analysis

Abstract

This invention discloses a dynamic evaluation method and system for the construction of hygienic cities based on multi-source data analysis. The method includes: completing the division of urban administrative regions, constructing a scoring indicator database, collecting the data required for scoring, and periodically acquiring and storing the scores of the scoring indicators according to time nodes. It dynamically eliminates compliant monitoring points and adds new points to update the monitoring points, and calculates the comprehensive risk value of each administrative region by combining historical data including accumulated problems, ineffective rectification, and indicator deterioration. It assigns electronic tags to recurring problem points and increases the sampling frequency; it increases the weight and evaluation frequency of indicators with a score rate below 75% and prominent problem points; and it reduces the weight of indicators that have completed rectification. Based on the problem points identified in the evaluation, a closed-loop management module is constructed, and the weights are updated according to the verification results. Finally, a visualized heat map is constructed based on data analysis. This provides a quantitative basis for targeted governance.

Description

Technical Field

[0001] This invention belongs to the field of sanitary city assessment technology, and more specifically, relates to a dynamic assessment method and system for sanitary city construction based on multi-source data analysis. Background Technology

[0002] The current assessment of hygienic city construction suffers from significant lags in data collection and system design. Data acquisition relies excessively on manual inspections and periodic reporting, resulting in long information transmission chains and a substantial time lag between problem discovery and recording. Assessments are often based on outdated information, failing to reflect the immediate state of urban sanitation. Furthermore, the assessment system is severely rigid, with fixed indicator weights that cannot be adapted to the different governance priorities of different regions and stages. The differentiated problems between old and new urban areas are incorporated into a unified framework, leading to a disconnect between resource allocation and actual needs, and preventing targeted solutions to key issues.

[0003] Deficiencies in the monitoring network and rectification process further weaken the effectiveness of the assessment. The long-term fixed monitoring locations not only waste resources through repeated inspections in compliant areas but also leave regulatory gaps in new areas created by urban expansion. Newly built communities and temporary markets easily become sanitation blind spots, making it difficult for assessment results to cover the entire city. The rectification process is generally fragmented, with many problems remaining only at the discovery stage. The division of responsibility and rectification deadlines are unclear, and even when rectification is initiated, the lack of standardized verification mechanisms leads to the recurrence of similar problems, creating an ineffective cycle and severely wasting administrative resources.

[0004] The way assessment results are presented also restricts the efficiency of management decision-making. Traditional text reports and tabular data cannot intuitively show the spatial distribution and changing trends of health risks. Managers need to spend a lot of energy sorting and analyzing them, making it difficult to quickly identify key areas for governance and delaying the speed of decision-making response. These problems combine to create a serious disconnect between the assessment of hygienic city construction and actual governance needs, hindering the improvement of urban health management and becoming a key bottleneck restricting the quality and efficiency of hygienic city construction. Summary of the Invention

[0005] This invention aims to address the problems in current assessments of hygienic city construction, such as data lag, rigid indicators, one-sided monitoring, lack of rectification loops, and inefficient result presentation. It improves the timeliness, accuracy, and relevance of assessments by constructing a multi-source dynamic data collection mechanism, enabling iterative updates of monitoring points, establishing a comprehensive risk quantification model, designing dynamic adjustment rules for indicator weights, building a closed-loop management module for the entire problem process, and combining this with visual presentation. This provides a scientific and efficient dynamic assessment solution for hygienic city construction, contributing to the improvement of urban sanitation management.

[0006] To address the aforementioned deficiencies or improvement needs of existing technologies, as a first aspect of this invention, the present invention provides a dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis, comprising:

[0007] S1. Complete the division of the corresponding city's administrative regions and the construction of the scoring indicator database; complete the data collection required for the calculation of the scoring indicators; periodically obtain and store the scoring indicators based on the set time nodes;

[0008] S2. The monitoring points are updated iteratively by dynamically eliminating qualified points and periodically adding new points; at the same time, the comprehensive risk value of each administrative region is calculated by combining historical data, including accumulated problems, ineffective rectification, and deterioration of indicators.

[0009] S3. Set electronic tags for problem locations that repeatedly cause problems and increase their sampling frequency; increase the corresponding weight and evaluation frequency for indicators with a score rate of less than 75% and prominent problem locations; reduce the corresponding weight for indicators that have been rectified.

[0010] S4. Based on the problem points identified in the assessment, complete the construction of a closed-loop management module for "problem registration - rectification order assignment - process tracking - result verification"; and update the weight of the corresponding problem points according to the feedback from the result verification.

[0011] S5. Construct visualization charts based on the data analysis results.

[0012] Furthermore, the scoring indicators in S1 include seven primary indicator categories, including patriotic health organization management, health education and health promotion, urban environmental sanitation, ecological environment, sanitation of key places, food and drinking water safety, and disease prevention and control and medical and health services;

[0013] The Patriotic Health Campaign Organization Management includes secondary indicators such as working network, work status, integration of health into all policies, and public supervision; the Health Education and Health Promotion includes secondary indicators such as health literacy and tobacco control; the Urban Environment Sanitation includes secondary indicators such as landscaping, garbage and sewage, and the toilet revolution; the Ecological Environment includes secondary indicators such as major accidents, air, noise and water quality, and medical waste and sewage treatment; the Sanitation of Key Locations includes secondary indicators such as public place sanitation management, school sanitation, and occupational disease prevention and control; the Food and Drinking Water Safety includes secondary indicators such as the establishment of working mechanisms, food production and operation, and drinking water sanitation; and the Disease Prevention and Control and Medical and Health Services include secondary indicators such as infectious disease prevention and control, health services, medical and health care, and vector-borne disease monitoring and assessment.

[0014] Furthermore, the data collection required for calculating the scoring indicators in S1 is completed by connecting to data ports including urban management databases, IoT devices, and public feedback platforms.

[0015] Furthermore, the specific process of dynamically eliminating qualified locations in S2 is as follows:

[0016] When the points are continuous Wheel, among which When the preset target conditions are met, a weight reduction mechanism is triggered;

[0017] Let the initial weights be... , No. After the target is met, the weight is updated as follows:

[0018]

[0019] in, To achieve continuous compliance in each round, The attenuation coefficient is... This indicates the percentage of weight retained after each round of compliance.

[0020] when At that time, the weight is locked as It will no longer decrease. The minimum threshold coefficient, ;

[0021] After the weights are locked, if they are consecutive wheel, To maintain compliance, this location will be removed from the regular monitoring list and only randomly included in periodic spot checks.

[0022] Furthermore, the method for calculating the comprehensive risk value in S2 is as follows:

[0023]

[0024] in, These are respectively the problem accumulation index. Rectification failure coefficient Indicator deterioration rate In calculating the comprehensive risk value Weight of time;

[0025] Cumulative Problem Index:

[0026]

[0027] in, This represents the total number of locations within the administrative region. For the first The number of prominent issues at each location; For the first The number of general problems at each point;

[0028] For the rectification failure coefficient:

[0029]

[0030] in, This refers to the number of locations within the administrative region that have not experienced a recurrence after rectification. This represents the total number of rectification sites within the administrative region.

[0031] For the rate of degradation of the indicator:

[0032]

[0033] in, This refers to the number of secondary indicators within the administrative region that have a score rate below 75%. For the first The first-round scores for each indicator; For the first The latest scores for each indicator; To assess the number of months in the interval.

[0034] Furthermore, the weights in S2 are It is configured to calculate the comprehensive score of health construction in the administrative region. :

[0035]

[0036] in, The overall score for the health construction of the administrative region; No. The weights of each secondary indicator; For the first The actual score rate of each secondary indicator.

[0037] Furthermore, the specific process of reducing the corresponding weight in S2 is as follows:

[0038] Let the weight at time t after the indicator rectification is completed be... The calculation formula is as follows:

[0039]

[0040] in, This is a temporary high-weight designation during the rectification period; The initial base weights for the indicators; This refers to the timeframe for completing the rectification. For the weighted smoothing pullback cycle; This is the weighting adjustment factor. ; Current time .

[0041] Furthermore, the closed-loop management module in S3 includes: a problem registration module configured for standardized entry and classification storage of problems; a rectification dispatch module configured for automatically matching problem information with responsible parties and completing task allocation and notification; a process tracking module configured for real-time monitoring of rectification progress and timely early warning of overdue uncompleted tasks; and a result verification module configured for verifying rectification effectiveness, determining whether the problem has been resolved, and providing a basis for weight adjustment.

[0042] As a second aspect of the present invention, the present invention provides a dynamic evaluation system for the construction of hygienic cities based on multi-source data analysis, comprising:

[0043] The basic data construction unit is used to complete the division of the corresponding city's administrative regions and the construction of the scoring indicator database; to complete the data collection required for the calculation of scoring indicators; and to periodically obtain and store the scoring indicators based on the set time nodes.

[0044] The monitoring point iteration and risk control unit is used to iterate and update the monitoring points by dynamically eliminating qualified points and periodically adding new points; at the same time, it calculates the comprehensive risk value of each administrative region by combining historical data including problem accumulation, rectification failure and indicator deterioration.

[0045] The indicator weight dynamic adjustment unit is used to set electronic tags for problem points that repeatedly cause problems, thereby increasing their sampling frequency; for indicators with a score rate of less than 75% and prominent problem points, the corresponding weight is increased and the evaluation frequency is increased; for indicators that have completed rectification, the corresponding weight is reduced.

[0046] The problem closed-loop management unit is used to build a closed-loop management module based on the problem points identified in the assessment, which includes "problem registration - rectification order assignment - process tracking - result verification"; and to update the weight of the corresponding problem points based on the feedback from the result verification.

[0047] The data visualization unit is used to construct visual charts based on data analysis results.

[0048] As a third aspect of the invention, the invention provides a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor of any step of the dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis.

[0049] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects:

[0050] 1. The dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis of the present invention establishes an iterative mechanism for monitoring points, combining compliance elimination with the addition of new points to achieve dynamic updates of monitoring points. This mechanism gradually reduces the monitoring weight of a point based on its continuous compliance status until it is eliminated, while periodically adding new points according to regional coverage needs. This solves the problem of fixed monitoring points and easy lag in actual changes in sanitation conditions in traditional evaluations, ensuring that the monitoring network always maintains sensitivity to sanitation-deficient areas and provides accurate monitoring point data support for dynamic evaluation.

[0051] 2. The dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis of the present invention constructs a comprehensive risk value calculation model by integrating data on problem accumulation, rectification failure, and indicator deterioration. This model uses a weighted summation method to quantify the overall regional risk, where the problem accumulation index reflects the scale of problems at specific locations, the rectification failure coefficient reflects the quality of rectification, and the indicator deterioration rate warns of the deterioration trend of indicators. This solves the problem of single risk dimensions and difficulty in comprehensive judgment in traditional assessments, and provides a quantitative basis for targeted governance.

[0052] 3. The dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis of the present invention constructs a closed-loop management module for problems and a data visualization heatmap. The closed-loop management module realizes the tracking of the entire process from problem registration to verification, ensuring that problems are effectively handled, and the results are fed back for weight updates, forming a management closed loop; the visualization heatmap intuitively presents the data analysis results, making the hygienic status and risk distribution of each area clear at a glance, helping managers to quickly grasp key information and improve decision-making efficiency. Attached Figure Description

[0053] Figure 1 This is a flowchart of a dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis, according to an embodiment of the present invention.

[0054] Figure 2 This is a visual bar chart showing the percentage of prominent issues in the on-site assessments of Wuhan's two rounds of National Sanitary City construction, as described in this embodiment of the invention.

[0055] Figure 3 This is a visual bar chart showing the percentage of general problems in the on-site assessments of Wuhan's two rounds of National Sanitary City construction, as an embodiment of the present invention.

[0056] Figure 4 This is a visual bar chart showing the percentage of Wuhan City without problems in the on-site assessments of the two rounds of National Sanitary City construction, as an embodiment of the present invention.

[0057] Figure 5 This is a system unit diagram of an embodiment of the present invention. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0059] Example 1

[0060] Please refer to Figure 1 This embodiment 1 provides a dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis, including:

[0061] S1. Complete the division of the corresponding city's administrative regions and the construction of the scoring indicator database; complete the data collection required for the calculation of the scoring indicators; periodically obtain and store the scoring indicators based on the set time nodes;

[0062] S2. The monitoring points are updated iteratively by dynamically eliminating qualified points and periodically adding new points; at the same time, the comprehensive risk value of each administrative region is calculated by combining historical data, including accumulated problems, ineffective rectification, and deterioration of indicators.

[0063] S3. Set electronic tags for problem locations that repeatedly cause problems and increase their sampling frequency; increase the corresponding weight and evaluation frequency for indicators with a score rate of less than 75% and prominent problem locations; reduce the corresponding weight for indicators that have been rectified.

[0064] S4. Based on the problem points identified in the assessment, complete the construction of a closed-loop management module for "problem registration - rectification order assignment - process tracking - result verification"; and update the weight of the corresponding problem points according to the feedback from the result verification.

[0065] S5. Construct visualization charts based on the data analysis results.

[0066] This embodiment 1 further elaborates on the above steps.

[0067] (1) Basic data construction

[0068] First, the city's administrative districts are divided to clarify the spatial scope of the assessment work, thus defining clear boundaries for subsequent statistical analysis of data from each region. Simultaneously, a scoring indicator database is constructed, with seven primary indicators forming its core framework. These indicators specifically cover patriotic health organization and management, health education and promotion, urban environmental sanitation, ecological environment, sanitation of key locations, food and drinking water safety, disease prevention and control, and medical and health services.

[0069] In a preferred embodiment, each primary indicator is further subdivided into multiple secondary indicators, forming a hierarchical indicator system: the Patriotic Health Campaign Organization Management includes secondary indicators such as work network, work status, integration of health into all policies, and public supervision; the Health Education and Health Promotion includes secondary indicators such as health literacy and tobacco control; the Urban Appearance and Environmental Sanitation includes secondary indicators such as landscaping, garbage and sewage, and the toilet revolution; the Ecological Environment includes secondary indicators such as major accidents, air, noise and water quality, and medical waste and sewage treatment; the Sanitation of Key Locations includes secondary indicators such as public place sanitation management, school sanitation, and occupational disease prevention and control; the Food and Drinking Water Safety includes secondary indicators such as the establishment of working mechanisms, food production and operation, and drinking water sanitation; and the Disease Prevention and Control and Medical and Health Services include secondary indicators such as infectious disease prevention and control, health services, medical and health care, and vector-borne disease monitoring and assessment.

[0070] The data collection process is achieved by connecting to multiple data sources, including basic government information provided by the city management database, real-time monitoring data transmitted by IoT devices, and clues about livelihood issues collected by the public feedback platform, ensuring the comprehensiveness and timeliness of the data required for the calculation of scoring indicators.

[0071] In a preferred embodiment, for the primary indicator of patriotic health organization management, government meeting minutes, work network personnel lists, etc. are extracted from the urban management database to correspond to the secondary indicators of government attention and work network; public feedback is collected through the public feedback platform to collect citizens' opinions on health work and match them to the secondary indicator of public supervision.

[0072] For health education and health promotion, health literacy monitoring reports and tobacco control enforcement records are obtained from the urban management database, which correspond to the secondary indicators of health literacy and tobacco control, respectively.

[0073] Among the data related to urban appearance and environmental sanitation, the green coverage rate, garbage collection trajectory, and public toilet usage status transmitted in real time by IoT devices correspond to the secondary indicators of landscaping, garbage and sewage, and the toilet revolution; the environmental sanitation assessment results provided by the urban management database are also included in this indicator system.

[0074] The data for ecological and environmental indicators come from air, noise, and water quality data monitored by IoT devices, as well as records of major environmental accidents and medical waste disposal ledgers in the urban management database, which correspond to secondary indicators for air and noise quality, major accidents, medical waste, and sewage treatment, respectively.

[0075] Regarding hygiene in key locations, public place hygiene permits, school hygiene inspection reports, and occupational disease prevention and control statistics are extracted from the urban management database, corresponding to the secondary indicators of public place hygiene management, school hygiene, and occupational disease prevention and control.

[0076] Data on food and drinking water safety includes food safety work mechanism documents in the urban management database, sampling results of food production and operation units, and drinking water quality data monitored by IoT devices, which are matched with the secondary indicators of work mechanism construction, food production and operation, and drinking water hygiene, respectively.

[0077] Disease prevention and control and medical and health services obtain infectious disease incidence data, medical institution service statistics, and vector-borne disease monitoring reports through the urban management database, corresponding to the secondary indicators of infectious disease prevention and control, health services, medical and health care, and vector-borne disease monitoring and assessment.

[0078] Based on preset time nodes, the above multi-source data are compared with the standards of each secondary indicator to generate corresponding scoring results. These results, along with the original data, are structured and stored together to form a time-series data archive covering the entire indicator system, providing accurate and adaptable basic information for dynamic evaluation.

[0079] (2) Location iteration and risk control

[0080] This embodiment 1 improves the accuracy and adaptability of the assessment by dynamically adjusting monitoring points and quantifying regional risks. During iterative updates of monitoring points, a weight reduction mechanism is activated for points that have met the standards for three or more consecutive rounds. Their monitoring weight is gradually reduced by a fixed proportion, and if they meet the standards for two more consecutive rounds after reaching the minimum threshold, they are removed from regular monitoring and only retained for random checks. New monitoring points are periodically added. This mechanism reduces resource waste in areas that consistently meet the standards while also covering newly added risk areas, ensuring that the monitoring network always reflects the actual health situation.

[0081] In a preferred embodiment, the specific process of dynamically eliminating qualified locations is as follows:

[0082] When the points are continuous Wheel, among which When the preset target conditions are met, a weight reduction mechanism is triggered;

[0083] Let the initial weights be... , No. After the target is met, the weight is updated as follows:

[0084]

[0085] in, To achieve continuous compliance in each round, The attenuation coefficient is... This indicates the percentage of weight retained after each round of compliance.

[0086] when At that time, the weight is locked as It will no longer decrease. The minimum threshold coefficient, ;

[0087] After the weights are locked, if they are consecutive wheel, To maintain compliance, this location will be removed from the regular monitoring list and only randomly included in periodic spot checks.

[0088] Simultaneously, the comprehensive risk value for each administrative region is calculated by combining historical data on problem accumulation, rectification failure, and indicator deterioration. The comprehensive risk value is derived by weighted integration of three types of data: the problem accumulation index reflects the total number of problems in the region, the rectification failure coefficient reflects the quality of rectification, and the indicator deterioration rate warns of the deteriorating trend of indicators. This multi-dimensional risk quantification method breaks through the limitations of single-indicator assessment, comprehensively reflects the weaknesses in regional health management, provides a scientific basis for targeted resource allocation and governance measures, and promotes the transformation of health city construction assessment from passive response to proactive prevention.

[0089] In a preferred embodiment, the comprehensive risk value is calculated as follows:

[0090]

[0091] in, These are respectively the problem accumulation index. Rectification failure coefficient Indicator deterioration rate In calculating the comprehensive risk value Weight of time;

[0092] Cumulative Problem Index:

[0093]

[0094] in, This represents the total number of locations within the administrative region. For the first The number of prominent issues at each location; For the first The number of general problems at each point;

[0095] For the rectification failure coefficient:

[0096]

[0097] in, This refers to the number of locations within the administrative region that have not experienced a recurrence after rectification. This represents the total number of rectification sites within the administrative region.

[0098] For the rate of degradation of the indicator:

[0099]

[0100] in, This refers to the number of secondary indicators within the administrative region that have a score rate below 75%. For the first The first-round scores for each indicator; For the first The latest scores for each indicator; To assess the number of months in the interval.

[0101] (3) Dynamic adjustment of indicator weights

[0102] Furthermore, by establishing a differentiated management and control mechanism for monitoring points and indicators, precise allocation and dynamic adaptation of assessment resources can be achieved. For points where problems recur, electronic tags are used for precise marking, and the sampling frequency is increased based on this. This ensures continuous monitoring of these recurring areas, avoids the recurrence of problems due to excessively long monitoring intervals, and forms a normalized tracking mechanism for persistent problems.

[0103] At the indicator management level, tiered adjustments are implemented based on actual performance: For weak indicators with a score rate below 75% and frequently occurring prominent issues, a dual approach is adopted to strengthen governance: on the one hand, their weight in the comprehensive assessment is increased to enhance their impact on the regional health score; on the other hand, the assessment frequency is increased and the monitoring interval is shortened to quickly capture improvement and drive management resources to concentrate on these key shortcomings. For indicators that have been rectified, a gradual weight adjustment strategy is adopted. Starting from the rectification completion time, within a pre-set smoothing decline period, the temporary high weight during the rectification period is gradually transitioned to the initial basic weight. The adjustment range is controlled by a specific coefficient, which maintains sufficient attention in the early stage of rectification to consolidate the results while avoiding the misallocation of resources due to excessively high weight in the long term.

[0104] In a preferred embodiment, the weight is... It is configured to calculate the comprehensive score of health construction in the administrative region. :

[0105]

[0106] in, The overall score for the health construction of the administrative region; No. The weights of each secondary indicator; For the first The actual score rate of each secondary indicator.

[0107] In a preferred embodiment, the specific process of reducing its corresponding weight is as follows:

[0108] Let the weight at time t after the indicator rectification is completed be... The calculation formula is as follows:

[0109]

[0110] in, This is a temporary high-weight designation during the rectification period; The initial base weights for the indicators; This refers to the timeframe for completing the rectification. For the weighted smoothing pullback cycle; This is the weighting adjustment factor. ; Current time .

[0111] These dynamically adjusted indicator weights are directly applied to the calculation of the comprehensive score for health construction in administrative regions. By combining them with the actual score rates of each indicator, the assessment results can truly reflect the strengths and weaknesses of regional health management. This differentiated management mechanism ensures both the tackling of key and difficult issues and the optimization of resources in areas that have already been improved. It allows the assessment of health city construction to accurately identify governance priorities and efficiently follow up on rectification results, ultimately improving the responsiveness and governance effectiveness of the overall management system.

[0112] (4) Problem closed-loop management

[0113] Meanwhile, for the problem points identified in the assessment, a closed-loop management module of "problem registration - rectification assignment - process tracking - result verification" was constructed to achieve full-process control of the problem through the collaborative operation of each link.

[0114] The problem registration module is responsible for standardized entry of discovered problems, classifying and storing them according to preset categories to ensure that each problem has a clear record, providing standardized basic information for subsequent processing. The rectification task assignment module automatically matches the responsible party based on the registered problem information, completes task allocation, and simultaneously issues notifications, clearly defining rectification requirements and deadlines, allowing the responsible party to quickly understand and intervene. The process tracking module monitors the rectification progress in real time, issuing timely warnings for tasks that are not completed by the deadline to avoid delays and ensure the timeliness of the processing flow. The result verification module is responsible for verifying the rectification effect, determining whether the problem has been resolved through on-site inspections or data review. Its feedback results will serve as the basis for updating the weight of problem points: if verification passes, the weight of the corresponding point is adjusted according to the rules; if it fails, the weight is maintained or increased to strengthen monitoring.

[0115] This closed-loop management module achieves full-chain control from problem discovery to resolution through the connection of various sub-modules. It ensures that every problem can be tracked and handled, and through the linkage of result verification and weight updates, it allows the evaluation system to be dynamically adjusted according to the actual rectification situation, thereby improving the thoroughness of problem governance and the pertinence of evaluation.

[0116] (5) Data visualization

[0117] When constructing visualization charts based on data analysis results, it is necessary to integrate information such as indicator scores, comprehensive risk values, distribution of problem locations, and rectification effectiveness for each administrative region. Appropriate chart formats should be selected for different data types: bar charts should be used to compare the primary indicator scores of each administrative region, clearly presenting the advantages and gaps between regions; line charts should be used to show the changing trends of a single indicator over different periods, intuitively reflecting the sustainability of governance effects; heat maps should be used to indicate the spatial distribution of problem locations, using color depth to represent the density of problems; and pie charts should be used to present the proportion of different types of problems within a certain area, clarifying the main governance directions.

[0118] These charts can not only display data for specific dimensions individually, but also enable multi-chart interaction through a linked function. For example, clicking on a specific administrative region in a bar chart will simultaneously display a heatmap and pie chart showing the detailed distribution and type percentage of problems in that region. Key data labels, such as specific scores, number of problems, and rectification completion rate, can also be embedded in the charts to ensure information completeness.

[0119] By combining various charts, complex data analysis results are transformed into intuitive and easy-to-understand visual information, helping managers quickly grasp the overall situation, key issues, and changing patterns of sanitation in various regions. This provides clear data support for developing targeted governance strategies, improving decision-making efficiency and accuracy.

[0120] Please refer to Figures 2-4 In a specific implementation, the problems identified in the two rounds of on-site assessments for the construction of a National Sanitary City in Wuhan were analyzed and compared. Focusing on the data from the two rounds of assessments, the dynamics of regional health issues were presented through multi-dimensional comparisons. First, the data were categorized into three types: general problems, prominent problems, and no problems. These were then classified and analyzed according to the region (including Wuhan City and AP areas) and the two assessment cycles to clarify the relationship between the data dimensions.

[0121] In the visualization of prominent issues, blue and orange bars are used to distinguish between the two rounds of data. In Zone B, the proportion in the second round exceeds 9%, while it was only about 3% in the first round, highlighting the rebound of prominent issues; in Zones A and L, the proportion was high in the first round, but decreased significantly in the second round, clearly showing the fluctuations in the governance of prominent issues, providing a basis for identifying key areas for tackling.

[0122] For general issues, the percentage data for the first round (blue bars) and the second round (orange bars) were extracted and plotted as a bar chart with administrative region as the horizontal axis and percentage as the vertical axis. In Zone B, the percentage in the first round was nearly 90%, and it decreased slightly in the second round; in Zone I, the percentage in the first round exceeded 50%, and it dropped to about 10% in the second round. This visually presents the regional differences in the effectiveness of general issue governance and helps to identify areas with better and worse rectification results.

[0123] In the chart showing the percentage of areas without problems, the blue and orange bars correspond to data from two rounds. In Zones I and J, the percentages in the second round exceeded 80% and 70% respectively, while in the first round they were less than 50%, reflecting the expansion of areas without problems after rectification. In Zone B, the percentage was extremely low in the first round but improved in the second round, reflecting the progress of improvement in areas with weak foundations.

[0124] During the construction process, scattered data is transformed into a "barometer" of regional health issues through multi-dimensional comparisons, presenting the coverage effect of routine governance, key areas of supervision for prominent issues, and the long-term effectiveness of rectification measures. This provides visual support for resource allocation and policy adjustments, helps to implement precise policies, and improves the quality of hygienic city construction.

[0125] Example 2

[0126] Please refer to Figure 5 This embodiment 2 provides a dynamic evaluation system for the construction of hygienic cities based on multi-source data analysis, including:

[0127] The basic data construction unit is used to complete the division of the corresponding city's administrative regions and the construction of the scoring indicator database; to complete the data collection required for the calculation of scoring indicators; and to periodically obtain and store the scoring indicators based on the set time nodes.

[0128] The monitoring point iteration and risk control unit is used to iterate and update the monitoring points by dynamically eliminating qualified points and periodically adding new points; at the same time, it calculates the comprehensive risk value of each administrative region by combining historical data including problem accumulation, rectification failure and indicator deterioration.

[0129] The indicator weight dynamic adjustment unit is used to set electronic tags for problem points that repeatedly cause problems, thereby increasing their sampling frequency; for indicators with a score rate of less than 75% and prominent problem points, the corresponding weight is increased and the evaluation frequency is increased; for indicators that have completed rectification, the corresponding weight is reduced.

[0130] The problem closed-loop management unit is used to build a closed-loop management module based on the problem points identified in the assessment, which includes "problem registration - rectification order assignment - process tracking - result verification"; and to update the weight of the corresponding problem points based on the feedback from the result verification.

[0131] The data visualization unit is used to construct visual charts based on data analysis results.

[0132] Example 3

[0133] This embodiment 3 also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can implement any step of a dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis.

[0134] The computer-readable storage medium may include various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0135] For a description of the computer-readable storage medium provided in this application, please refer to the above method embodiments; further details will not be repeated here.

[0136] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis, characterized in that, include: S1. Complete the division of the corresponding city's administrative regions and the construction of the scoring indicator database; complete the data collection required for the calculation of the scoring indicators; periodically obtain and store the scoring indicators based on the set time nodes; S2. The monitoring points are updated iteratively by dynamically eliminating qualified points and periodically adding new points; at the same time, the comprehensive risk value of each administrative region is calculated by combining historical data, including accumulated problems, ineffective rectification, and deterioration of indicators. S3. Set electronic tags for problem locations that repeatedly cause problems and increase their sampling frequency; increase the corresponding weight and evaluation frequency for indicators with a score rate of less than 75% and prominent problem locations; reduce the corresponding weight for indicators that have been rectified. S4. Based on the problem points identified in the assessment, complete the construction of a closed-loop management module for "problem registration - rectification order assignment - process tracking - result verification"; and update the weight of the corresponding problem points according to the feedback from the result verification. S5. Construct visualization charts based on the data analysis results; The specific process for dynamically eliminating qualified locations in S2 is as follows: When the points are continuous Wheel, among which When the preset target conditions are met, a weight reduction mechanism is triggered; Let the initial weights be... , No. After the target is met, the weight is updated as follows: in, To achieve continuous compliance in each round, The attenuation coefficient is... This indicates the percentage of weight retained after each round of compliance. when At that time, the weight is locked as It will no longer decrease. The minimum threshold coefficient, ; After the weights are locked, if they are consecutive wheel, To maintain compliance, this location will be removed from the regular monitoring list and only randomly included in periodic spot checks. The method for calculating the comprehensive risk value in S2 is as follows: in, These are respectively the problem accumulation index. Rectification failure coefficient Indicator deterioration rate In calculating the comprehensive risk value Weight of time; Cumulative Problem Index: in, This represents the total number of locations within the administrative region. For the first The number of prominent issues at each location; For the first The number of general problems at each point; For the rectification failure coefficient: in, This refers to the number of locations within the administrative region that have not experienced a recurrence after rectification. This represents the total number of rectification sites within the administrative region. For the rate of degradation of the indicator: in, This refers to the number of secondary indicators within the administrative region that have a score rate below 75%. For the first The first-round scores for each indicator; For the first The latest scores for each indicator; To assess the number of months in the interval; The weight in S3 is It is configured to calculate the comprehensive score of health construction in the administrative region. : in, The overall score for the health construction of the administrative region; No. The weights of each secondary indicator; For the first The actual score rate of each secondary indicator.

2. The dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis according to claim 1, characterized in that, The scoring indicators in S1 include seven primary indicator categories, namely, patriotic health organization management, health education and health promotion, urban environmental sanitation, ecological environment, sanitation of key places, food and drinking water safety, and disease prevention and control and medical and health services. The patriotic health campaign management includes secondary indicators such as work network, work status, integration of health into all policies, and public supervision; the health education and health promotion includes secondary indicators such as health literacy and tobacco control; the urban environment sanitation includes secondary indicators such as landscaping, garbage and sewage, and the toilet revolution; the ecological environment includes secondary indicators such as major accidents, air, noise and water quality, and medical waste and sewage treatment; the sanitation of key locations includes secondary indicators such as public place sanitation management, school sanitation, and occupational disease prevention and control; the food and drinking water safety includes secondary indicators such as the establishment of working mechanisms, food production and operation, and drinking water sanitation; and the disease prevention and control and medical and health services include secondary indicators such as infectious disease prevention and control, health services, medical and health services, and vector-borne disease monitoring and assessment.

3. The dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis according to claim 1, characterized in that, The data collection required for calculating the scoring indicators in S1 is completed by connecting to data ports including urban management databases, IoT devices, and public feedback platforms.

4. The dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis according to claim 1, characterized in that, The specific process of reducing the corresponding weight in S3 is as follows: Let the weight at time t after the indicator rectification is completed be... The calculation formula is as follows: in, This is a temporary high-weight designation during the rectification period; The initial base weights for the indicators; This refers to the timeframe for completing the rectification. For the weighted smoothing pullback cycle; This is the weighting adjustment factor. ; Current time .

5. The dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis according to claim 1, characterized in that, The closed-loop management module in S4 includes: a problem registration module configured for standardized entry and classification storage of problems; a rectification dispatch module configured for automatically matching problem information with responsible parties and completing task allocation and notification; a process tracking module configured for real-time monitoring of rectification progress and timely early warning of overdue unfinished tasks; and a result verification module configured for verifying rectification effectiveness, determining whether the problem has been resolved, and providing a basis for weight adjustment.

6. A dynamic evaluation system for the construction of hygienic cities based on multi-source data analysis, used to implement the dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis as described in claim 1, characterized in that, include: The basic data construction unit is used to complete the division of the corresponding city's administrative districts and the construction of the scoring indicator database; and to complete the data collection required for the calculation of the scoring indicators. The scoring indicators are periodically acquired, scored, and stored based on the set time nodes. The monitoring point iteration and risk control unit is used to iterate and update the monitoring points by dynamically eliminating qualified points and periodically adding new points; at the same time, it calculates the comprehensive risk value of each administrative region by combining historical data including problem accumulation, rectification failure and indicator deterioration. The indicator weight dynamic adjustment unit is used to set electronic tags for problem points that repeatedly cause problems, thereby increasing their sampling frequency; for indicators with a score rate of less than 75% and prominent problem points, the corresponding weight is increased and the evaluation frequency is increased; for indicators that have completed rectification, the corresponding weight is reduced. The problem closed-loop management unit is used to build a closed-loop management module based on the problem points identified in the assessment, which includes "problem registration - rectification order assignment - process tracking - result verification"; and to update the weight of the corresponding problem points based on the feedback from the result verification. The data visualization unit is used to construct visual charts based on data analysis results.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program is executed by a processor using the dynamic evaluation method for the construction of hygienic cities based on multi-source data analysis as described in any one of claims 1-5.

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