Garbage classification community governance supervision method, device and equipment and storage medium
Through garbage classification assessment and evaluation and dynamic tracking and prediction models, combined with multi-dimensional analysis and reward mechanism, the participation and accuracy problems in garbage classification community management are solved, and more efficient community governance is achieved.
Patent Information
- Application Number
- CN202411566729.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-05
- Publication Date
- 2024-12-13
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Inadequate participation of residents, low classification accuracy and lack of effective incentive mechanisms in waste classification community management have led to increased resource waste and management costs.
The garbage classification assessment and evaluation plan is adopted, and a dynamic tracking and prediction statistical model is created by collecting key data, comprehensive evaluation and multi-dimensional stereoscopic analysis are carried out, reward mechanisms are formulated, and management measures are optimized through cross-regional collaboration mechanisms.
It has improved management efficiency, reduced operating costs, encouraged residents and community organizations to actively participate, improved overall participation rate, and achieved more efficient and scientific community governance of garbage classification.
Smart Images
Figure CN119130264A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of garbage classification technology, and more specifically to a method, device, equipment and storage medium for community management and supervision of garbage classification. Background Art
[0002] In modern urban management, garbage classification has become an important measure to improve environmental quality and resource recycling. In the current practice of garbage classification, community management of garbage classification faces the following major problems: First, insufficient participation of residents: many community residents do not have a deep understanding of garbage classification, resulting in low enthusiasm for participation, affecting the overall classification effect. Second, low classification accuracy: even if some residents are willing to participate, due to the lack of effective guidance and incentives, the classification accuracy is still not high, resulting in waste of resources and increased management costs. Third, lack of effective incentive mechanism: the existing incentives are single and unattractive, and fail to stimulate residents' enthusiasm and initiative for long-term participation. Summary of the invention
[0003] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a method, device, equipment and storage medium for community management and supervision of garbage classification.
[0004] To achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for community governance and supervision of garbage classification, comprising: Set up a waste classification assessment and evaluation plan; Collect key data on waste classification related to assessment and evaluation, including community organization participation data, facility maintenance data, and activity participation data; Create dynamic tracking and prediction statistical models based on key data of garbage classification; Dynamic tracking and intelligent prediction are carried out based on dynamic tracking and prediction statistical models; Conduct a comprehensive evaluation of the effectiveness of the waste sorting community based on dynamic tracking and intelligent prediction results; Generate analysis reports based on comprehensive evaluation results of effectiveness; Conduct multi-dimensional analysis and horizontal and vertical analysis based on the analysis report; Formulate a reward mechanism based on the results of multi-dimensional analysis and horizontal and vertical analysis; Based on the feedback from the reward mechanism, a cross-regional collaboration mechanism for garbage sorting communities will be formulated.
[0005] Furthermore, the setting of the garbage classification assessment and evaluation plan includes: Identify key evaluation dimensions; Set evaluation indicators and scoring criteria; Set the initial weights of each dimension; Dynamically adjust weights based on feedback; Set the statistical period for each dimension.
[0006] Furthermore, the comprehensive evaluation of the effectiveness of the garbage classification community based on dynamic tracking and intelligent prediction results includes: Establish a step-by-step review mechanism, including community review, street review, district review and city review; Establishing a review and supplement mechanism; The comprehensive community portrait score is calculated based on the audit results at all levels to obtain a comprehensive evaluation of the effectiveness of garbage classification in the community.
[0007] Furthermore, the step-by-step review mechanism is established, and the step-by-step review includes community review, street review, district review and city review, including: Conducting preliminary audits at the community level to collect and organize waste sorting data, including sorting accuracy, equipment integrity, and resident participation; Review the audit results of each community at the street level and make suggestions for phased improvements; The district-level departments review the aggregated data at the street level, conduct further analysis and evaluation, and provide scores and feedback on the garbage sorting work of each street; The municipal department will ultimately review the district-level data, conduct a comprehensive analysis of the overall effectiveness of the city’s waste sorting efforts, and formulate and adjust policies.
[0008] Furthermore, the community comprehensive portrait score is calculated based on the audit results at all levels to obtain a comprehensive evaluation result of the effectiveness of garbage classification in the community, including: Calculate daily operations assessment scores; Calculate district-level assessment scores; Calculate city-level assessment scores; The community comprehensive portrait score is calculated based on the set score weights combined with the calculated daily operation evaluation score, district-level evaluation score, and city-level evaluation score.
[0009] Furthermore, the multi-dimensional analysis and horizontal and vertical analysis based on the analysis report includes: Compare data from different regions to identify data differences in regional dimensions; Compare data from the same region at different times to identify data differences over time; Combine the data difference information in the regional dimension and the data difference information in the time dimension to obtain comprehensive analysis results.
[0010] Furthermore, the reward mechanism is formulated according to the analysis results of the multi-dimensional stereoscopic analysis and the horizontal and vertical analysis, including: Setting incentive forms, including point rewards, honorary titles, and community selection; Formulate points scoring rules; Establish selection rules and selection cycle.
[0011] In a second aspect, the present invention also provides a garbage classification community governance and supervision device, including: A setting unit, used to set a garbage classification assessment plan; A data collection unit, used to collect key data on waste classification related to assessment and evaluation, including community organization participation data, facility maintenance data, and activity participation data; A model creation unit, used to create a dynamic tracking and prediction statistical model based on key data of garbage classification; A model tracking and prediction unit, used for dynamic tracking and intelligent prediction based on a dynamic tracking and prediction statistical model; Comprehensive evaluation unit, used to conduct a comprehensive evaluation of the effectiveness of the garbage sorting community based on dynamic tracking and intelligent prediction results; An analysis report generating unit, used for generating an analysis report according to the comprehensive evaluation result of the effectiveness; The overall analysis unit is used to conduct multi-dimensional analysis and horizontal and vertical analysis based on the analysis report; A reward mechanism formulation unit, used to formulate a reward mechanism based on the analysis results of multi-dimensional stereoscopic analysis and horizontal and vertical analysis; The collaboration mechanism formulation unit is used to formulate a cross-regional collaboration mechanism for the garbage classification community based on feedback from the reward mechanism.
[0012] In the third aspect, the present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the garbage classification community governance and supervision method as described above is implemented.
[0013] In a fourth aspect, the present invention also provides a computer-readable storage medium, which stores a computer program, and the computer program includes program instructions. When the program instructions are executed by a processor, the processor executes the garbage classification community governance and supervision method as described above.
[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: a method for community governance and supervision of garbage classification, comprising setting up a garbage classification assessment plan; collecting key data on garbage classification related to the assessment, wherein the key data on garbage classification includes community organization participation data, facility maintenance data and activity participation data; creating a dynamic tracking and prediction statistical model based on the key data on garbage classification; performing dynamic tracking and intelligent prediction based on the dynamic tracking and prediction statistical model; conducting a comprehensive evaluation of the effectiveness of the garbage classification community based on the dynamic tracking and intelligent prediction results; generating an analysis report based on the comprehensive evaluation results of the effectiveness; conducting multi-dimensional stereoscopic analysis and horizontal and vertical analysis based on the analysis report; formulating a reward mechanism based on the analysis results of the multi-dimensional stereoscopic analysis and horizontal and vertical analysis; and formulating a cross-regional collaboration mechanism for garbage classification communities based on feedback from the reward mechanism. The present invention enables managers to respond and adjust measures quickly through dynamic tracking and intelligent prediction functions, thereby improving management efficiency and reducing operating costs; by generating analytical reports and multi-dimensional analysis, it provides detailed data support and horizontal and vertical analysis results to help formulate scientific management decisions and reward mechanisms; by setting up a comprehensive garbage classification assessment and evaluation plan and reward mechanism, it encourages more residents and community organizations to actively participate and improve the overall participation rate. Overall, it achieves more efficient and scientific garbage classification community governance.
[0015] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the following preferred embodiments are specifically cited and described in detail as follows. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.
[0017] Figure 1 A flowchart of a method for community management and supervision of garbage classification provided by a specific embodiment of the present invention; Figure 2 A schematic block diagram of a garbage classification community governance and supervision device provided in a specific embodiment of the present invention; Figure 3 A schematic block diagram of a computer device provided for a specific embodiment of the present invention. DETAILED DESCRIPTION
[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0019] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.
[0020] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.
[0021] It should be further understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
[0022] like Figure 1 As shown, an embodiment of the present invention provides a method for community governance and supervision of garbage classification, which includes the following steps: S10-S90.
[0023] S10. Set up a garbage classification assessment and evaluation plan.
[0024] In one embodiment, step S10 specifically includes the following steps: S101 - S105 .
[0025] S101. Determine key evaluation dimensions.
[0026] In this embodiment, the evaluation dimensions are determined from the aspects of community organization leadership, facility maintenance, and activity participation.
[0027] Community organization leadership: Evaluate the guiding and organizing role of community organizations in garbage sorting, including the participation rate of organization members, number of activities carried out, etc.
[0028] Facility maintenance: Evaluate the maintenance of garbage sorting hardware facilities, such as the integrity rate of classified garbage bins, cleaning frequency, etc.
[0029] Activity participation: Assess community residents’ participation in waste sorting activities, including participation rate, number and quality of activities.
[0030] S102. Set evaluation indicators and scoring criteria.
[0031] In this embodiment, in terms of community organization leadership, specifically, the participation rate of community organization members is determined: the proportion of community organization members who participate in garbage sorting activities to the total number of members is determined. The number of activities carried out is determined: the number of garbage sorting related activities organized by the community organization each month. Scoring criteria: Scoring is performed based on the participation rate and the number of activities, such as 80-100% participation gets full marks, 60-80% gets medium marks, and less than 60% gets low marks.
[0032] For facility maintenance, specifically, determine the integrity rate of classified trash bins: the proportion of intact trash bins to the total number. Determine the cleaning frequency: the frequency of cleaning each trash bin. Determine the scoring criteria: score based on integrity rate and cleaning frequency, such as full marks for integrity rates above 95%, medium marks for 90-95%, and low marks for below 90%.
[0033] Regarding activity participation, specifically, determine the activity participation rate: the proportion of residents participating in the activity to the total number of residents. Determine the activity quality: survey residents' satisfaction with the activity. Determine the scoring criteria: score based on participation rate and satisfaction, such as 80-100% participation for full marks, 60-80% for medium marks, and below 60% for low marks.
[0034] S103: Set the initial weight of each dimension.
[0035] In this embodiment, the weight of community organization accounts for 30%, the weight of facility maintenance accounts for 40%, and the weight of activity participation accounts for 30%.
[0036] S104. Dynamically adjust weights according to feedback.
[0037] In this embodiment, the weight adjustment rule is: adjust the weight every quarter based on the evaluation results and community feedback. For example, if facility maintenance is found to be unusually important, the weight of "facility maintenance" can be increased. Automatic adjustment algorithm: Use machine learning algorithms, such as regression analysis or decision trees and random forest algorithms, to automatically adjust the weight based on historical data and current performance. The specific algorithm can be based on multi-factor analysis, considering the relevance and influence of each dimension.
[0038] S105. Set the statistical period of each dimension.
[0039] In this embodiment, the statistical period is divided into short-term statistics, medium-term statistics and long-term statistics.
[0040] For short-term statistics, specifically: Statistical period: weekly; Statistics: Facility maintenance, participation in short-term activities, and short-term performance feedback; Statistical purpose: Quickly identify problems and make short-term adjustments.
[0041] For mid-term statistics, specifically: Statistical period: monthly; Statistical content: community organization leadership effectiveness, facility maintenance stability, and mid-term activity participation; Statistical purpose: To evaluate interim results and conduct monthly adjustments and optimizations.
[0042] For long-term statistics, specifically: Statistical period: quarterly; Statistical content: overall effectiveness evaluation, long-term trend analysis, and comprehensive feedback; Statistical purpose: To evaluate overall performance and trends, and to conduct long-term planning and strategic adjustments.
[0043] S20. Collect key data on garbage classification related to assessment and evaluation. The key data on garbage classification includes community organization participation data, facility maintenance data and activity participation data.
[0044] In this embodiment, sensors, IoT devices and other technical means are used to collect data such as the amount of garbage put in, the overflow of garbage bins, the number of community organization activities, the number of participants, the duration of volunteer service, etc. in real time. Then a structured database is established to classify and store the collected data to ensure the safe storage and convenient query of the data. In addition, duplicate records and erroneous data are removed to ensure the accuracy of the data, and data cleaning algorithms are used to automatically process data anomalies. The data cleaning algorithm here can specifically be a deduplication algorithm or an outlier detection algorithm.
[0045] S30. Create a dynamic tracking and prediction statistical model based on key data of garbage classification.
[0046] In this embodiment, the collected garbage classification key data is fused. Specifically, based on key fields such as timestamp and geographic location, multi-source data is fused to form a unified data set. Data fusion can integrate data from different sources and provide a basis for multi-dimensional analysis. ETL tools (such as Apache NiFi, Talend) can be used for data fusion. Then, the fused historical data is used to train the machine learning model. Algorithms such as regression analysis, neural networks, and XGBoost can be used, and Scikit-learn, TensorFlow, or PyTorch can be used for model training.
[0047] S40, performing dynamic tracking and intelligent prediction according to a dynamic tracking and prediction statistical model.
[0048] In this embodiment, a trained dynamic tracking and prediction statistical model is used to predict future trends in waste sorting, and automatically generate improvement suggestions to guide community waste sorting work.
[0049] S50. Conduct a comprehensive evaluation of the effectiveness of the garbage sorting community based on dynamic tracking and intelligent prediction results.
[0050] In one embodiment, step S50 specifically includes the following steps: S501 - S503 .
[0051] S501. Create a step-by-step review mechanism, which includes community review, street review, district review and city review.
[0052] In one embodiment, step S501 specifically includes the following steps: S5011 - S5014 .
[0053] S5011. Conduct preliminary audits at the community level to collect and organize waste classification data, including classification accuracy, equipment integrity, and resident participation; S5012, review the audit results of each community at the street level and put forward suggestions for phased improvements; S5013. District-level departments review the aggregated data at the street level, conduct further analysis and evaluation, and provide scores and feedback on the garbage sorting work of each street; S5014. The municipal department shall finally review the district-level data, comprehensively analyze the overall effectiveness of the city's garbage sorting work, and formulate and adjust policies; S502. Establish an audit supplement mechanism.
[0054] In this embodiment, for the community and street level: the problems found in the community audit are reviewed and supplemented at the street level to ensure comprehensive coverage of the problems. For the street and district level: the weak points of the street audit are focused on and analyzed in depth to improve the comprehensiveness of the assessment. For the district and municipal level: the comprehensive problems of the district audit are formulated by the municipal department to ensure overall improvement.
[0055] S503. Calculate the comprehensive community portrait score based on the audit results at all levels to obtain a comprehensive evaluation result of the effectiveness of garbage classification in the community.
[0056] In one embodiment, step S503 specifically includes the following steps: S5031 - S5034 .
[0057] S5031. Calculate the daily operation evaluation score.
[0058] S5032. Calculate district-level assessment scores; S5033. Calculate the city-level assessment score; S5034. Calculate the community comprehensive portrait score based on the set score weights combined with the calculated daily operation evaluation score, district-level evaluation score, and city-level evaluation score.
[0059] In this embodiment, for steps S5031-S5034, for the daily operation evaluation score, the community collects garbage classification related data regularly (such as daily or weekly), and scores according to set indicators (classification accuracy, equipment integrity rate, activity participation, etc.), and the daily operation evaluation score is calculated by weighted average of the scores of each indicator.
[0060] For district-level assessment scores, data from each community is aggregated at the street level to produce a comprehensive score, and a centralized assessment is conducted monthly or quarterly to calculate the district-level assessment scores.
[0061] For the city-level assessment scores, the city-level department aggregates the data from each district, makes an overall score, and conducts a comprehensive assessment through data analysis and field visits to calculate the city-level assessment scores.
[0062] Set the weight ratios for daily operations assessment score (A%), district-level assessment score (B%), and city-level assessment score (C%).
[0063] Comprehensive score = A% * daily operation assessment score + B% * district-level assessment score + C% * city-level assessment score. For example: weight ratio: daily operation assessment score (A%): 40%; district-level assessment score (B%): 30%; city-level assessment score (C%): 30%.
[0064] S60. Generate an analysis report based on the comprehensive evaluation results of the effectiveness.
[0065] In this embodiment, based on the constructed evaluation data model, analysis reports of various dimensions can be generated, and the report content can be presented intuitively by combining charts and text descriptions. In addition, the rectification effect is evaluated regularly and the analysis report is updated. A continuous improvement cycle is formed to promote the continuous improvement of garbage classification work.
[0066] It should be noted that the evaluation data model can be constructed based on the key indicators of community waste classification. The evaluation data model is a tool for quantifying and evaluating the effectiveness of waste classification and is composed of multiple indicators.
[0067] S70. Conduct multi-dimensional analysis and horizontal and vertical analysis based on the analysis report.
[0068] It can realize multi-dimensional analysis of garbage classification work, accurately locate problems and provide specific improvement suggestions, thereby promoting continuous improvement of the overall work.
[0069] In one embodiment, step S70 specifically includes the following steps: S701 - S703 .
[0070] S701, comparing data from different regions to identify data difference information in regional dimensions; S702, comparing data from different periods in the same region to identify data difference information in the time dimension; S703: Combine the data difference information in the regional dimension and the data difference information in the time dimension to obtain a comprehensive analysis result.
[0071] In this embodiment, for steps S701-S703, evaluation data of each region is collected, including classification accuracy, equipment integrity rate, resident participation, etc. Statistics such as the mean value and standard deviation of each dimension are calculated to evaluate the overall level. Data from different regions are compared to identify indicator differences, and visualization tools (such as heat maps) are used to display regional differences and identify key areas of focus.
[0072] Accurately lock the weak points Specifically, comparative analysis and positioning: in vertical analysis, compare data from different periods in the same region to identify trend changes; in horizontal analysis, compare data from different regions in the same period to find differences. In-depth cause analysis: for weak links, collect relevant background and management information; analyze internal and external factors to find the root cause of the problem. Provide improvement suggestions: formulate improvement measures for weak links. Optimize resource allocation and improve work efficiency and effectiveness.
[0073] Horizontal and vertical integration Combine the time dimension (vertical) and the regional dimension (horizontal) for comprehensive analysis. Use dynamic visualization tools (such as dynamic charts) to show the changing trends and regional differences. Based on the analysis and combined results, reveal the development laws of garbage sorting, discover hidden problems, and propose comprehensive solutions.
[0074] S80. Establish a reward mechanism based on the results of multi-dimensional analysis and horizontal and vertical analysis.
[0075] In one embodiment, step S80 specifically includes the following steps: S801 - S803 .
[0076] S801. Set incentive forms, including point rewards, honorary titles and community selection; S802, formulate points rules; S803. Establish selection rules and selection cycle.
[0077] In this embodiment, for steps S801-S803, in determining the form of incentives, for point rewards: design a point system, residents can get points by correctly sorting garbage, and the points can be exchanged for physical rewards or services. For honorary titles: set honorary titles such as "Excellent Resident in Garbage Sorting" and "Environmental Protection Pioneer", and regularly select and issue certificates.
[0078] Regarding community selection: regularly select “excellent communities for garbage classification” and give collective commendations.
[0079] In formulating the points rules, for points acquisition: clarify the rules for points acquisition, such as how many points are obtained for each correct garbage sorting. For points redemption: design a points redemption mechanism, including the types and quantities of redeemable rewards, such as daily necessities, community service coupons, etc.
[0080] In establishing the selection mechanism, for the selection criteria: formulate the selection criteria for excellent communities and individuals in garbage classification, including classification accuracy, participation frequency, etc. For the selection cycle: determine the selection cycle, such as once a quarter or half a year.
[0081] In publicity and promotion, for publicity channels: publicize the incentive mechanism through community bulletin boards, WeChat groups, leaflets, etc. For mobilization activities: organize community mobilization meetings, explain incentive measures, and encourage residents to actively participate.
[0082] In regular selection and commendation, for data collection and evaluation: regularly collect residents' garbage classification data, record points and participation, analyze data, and evaluate the classification performance of each resident and community. For the selection process: conduct preliminary screening based on points and selection criteria, determine the candidate list, invite community representatives and residents to participate in the review, and finally determine the outstanding residents and communities. For commendation and rewards: organize a commendation ceremony, issue certificates and awards to outstanding residents and communities. According to the points redemption rules, issue the redeemed physical or service rewards. In feedback and improvement, for resident feedback: collect residents' feedback on the incentive mechanism, and understand their satisfaction and suggestions. For mechanism improvement: adjust and optimize the incentive mechanism based on feedback.
[0083] S90. Develop a cross-regional collaboration mechanism for waste sorting communities based on feedback from the reward mechanism.
[0084] In this embodiment, by formulating cross-community and cross-regional collaboration plans, promoting experience exchange and resource sharing, regularly organizing cross-regional garbage sorting work exchange meetings, and sharing successful cases and experiences. In addition, collecting and organizing successful cases from different communities, promoting and sharing them through online and offline channels, and encouraging communities to learn from each other and draw on successful experiences to continuously optimize garbage sorting work.
[0085] The present invention enables managers to respond and adjust measures quickly through dynamic tracking and intelligent prediction functions, thereby improving management efficiency and reducing operating costs; by generating analytical reports and multi-dimensional analysis, it provides detailed data support and horizontal and vertical analysis results to help formulate scientific management decisions and reward mechanisms; by setting up a comprehensive garbage classification assessment and evaluation plan and reward mechanism, it encourages more residents and community organizations to actively participate and improve the overall participation rate. Overall, it achieves more efficient and scientific garbage classification community governance.
[0086] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.
[0087] The embodiment of the present invention also provides a garbage classification community governance supervision device, which is used to execute the steps in any embodiment of the above-mentioned garbage classification community governance supervision method. Figure 2 , Figure 2 A schematic block diagram of a garbage classification community governance supervision device 100 provided in an embodiment of the present application is shown. The garbage classification community governance supervision device 100 specifically includes: The setting unit 110 is used to set the garbage classification assessment and evaluation plan; the data collection unit 120 is used to collect key data of garbage classification related to the assessment and evaluation, and the key data of garbage classification includes community organization participation data, facility maintenance data and activity participation data; the model creation unit 130 is used to create a dynamic tracking and prediction statistical model based on the garbage classification key data; the model tracking and prediction unit 140 is used to perform dynamic tracking and intelligent prediction based on the dynamic tracking and prediction statistical model; the comprehensive evaluation unit 150 is used to conduct a comprehensive evaluation of the effectiveness of the garbage classification community based on the dynamic tracking and intelligent prediction results; the analysis report generation unit 160 is used to generate an analysis report based on the comprehensive evaluation results of the effectiveness; the overall analysis unit 170 is used to perform multi-dimensional stereoscopic analysis and horizontal and vertical analysis based on the analysis report; the reward mechanism formulation unit 180 is used to formulate a reward mechanism based on the analysis results of the multi-dimensional stereoscopic analysis and horizontal and vertical analysis; the collaboration mechanism formulation unit 190 is used to formulate a cross-regional collaboration mechanism for garbage classification communities based on the feedback of the reward mechanism.
[0088] In one embodiment, the setting unit 110 is specifically configured to: Determine key evaluation dimensions; set evaluation indicators and scoring criteria; set initial weights for each dimension; dynamically adjust weights based on feedback; set statistical periods for each dimension.
[0089] In one embodiment, the comprehensive evaluation unit 150 is specifically used for: Create a step-by-step review mechanism, which includes community review, street review, district review and city review; establish a review supplement mechanism; calculate the community comprehensive portrait score based on the review situation at all levels to obtain a comprehensive evaluation result of the effectiveness of garbage classification in the community.
[0090] In one embodiment, the comprehensive evaluation unit 150 is further specifically configured to: A preliminary review is conducted at the community level to collect and organize garbage classification data, which includes classification accuracy, equipment integrity rate and resident participation; the review results of each community are reviewed at the street level, and phased improvement suggestions are put forward; the district-level departments review the summary data at the street level, conduct further analysis and evaluation, and score and provide feedback on the garbage classification work of each street; the municipal department finally reviews the district-level data, comprehensively analyzes the overall effectiveness of the city's garbage classification work, and formulates and adjusts policies.
[0091] In one embodiment, the comprehensive evaluation unit 150 is further specifically configured to: Calculate the daily operation evaluation score; calculate the district-level evaluation score; calculate the city-level evaluation score; calculate the community comprehensive portrait score based on the set score weights and the calculated daily operation evaluation score, district-level evaluation score and city-level evaluation score.
[0092] In one embodiment, the overall analysis unit 170 is specifically used for: Compare data from different regions to identify data difference information in the regional dimension; compare data from different periods in the same region to identify data difference information in the time dimension; combine data difference information in the regional dimension and data difference information in the time dimension to obtain comprehensive analysis results.
[0093] In one embodiment, the reward mechanism formulation unit 180 is specifically used to: Set incentive forms, including point rewards, honorary titles and community selection; formulate point rules; establish selection rules and selection cycles.
[0094] It should be noted that technical personnel in the relevant field can clearly understand that the specific implementation process of the above-mentioned garbage classification community governance supervision device 100 and each unit can refer to the corresponding description in the aforementioned method embodiment, and for the convenience and conciseness of the description, it will not be repeated here.
[0095] The above-mentioned garbage classification community governance supervision device can be implemented in the form of a computer program, which can be used in Figure 3 Runs on the computer device shown.
[0096] See also Figure 3 , Figure 3700 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device 700 may be a server, wherein the server may be an independent server or a server cluster composed of multiple servers.
[0097] like Figure 3 As shown, the computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the garbage classification community governance and supervision method as described above are implemented.
[0098] The computer device 700 may be a terminal or a server. The computer device 700 includes a processor 720 , a memory, and a network interface 750 connected via a system bus 710 , wherein the memory may include a non-volatile storage medium 730 and an internal memory 740 .
[0099] The non-volatile storage medium 730 can store an operating system 731 and a computer program 732. When the computer program 732 is executed, the processor 720 can execute the garbage classification community governance supervision method.
[0100] The processor 720 is used to provide computing and control capabilities and support the operation of the entire computer device 700.
[0101] The internal memory 740 provides an environment for the operation of the computer program 732 in the non-volatile storage medium 730. When the computer program 732 is executed by the processor 720, the processor 720 can execute the garbage classification community governance and supervision method.
[0102] The network interface 750 is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will appreciate that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the present application scheme, and does not constitute a limitation on the computer device 700 to which the present application scheme is applied. The specific computer device 700 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. The processor 720 is used to run the program code stored in the memory to implement the garbage classification community governance supervision method.
[0103] Those skilled in the art will understand that Figure 3 The embodiments of the computer device shown in the figure do not constitute a limitation on the specific composition of the computer device. In other embodiments, the computer device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. For example, in some embodiments, the computer device may only include a memory and a processor. In such embodiments, the structure and function of the memory and the processor are the same as those of the embodiment of the present invention. Figure 3The embodiments shown are consistent and will not be described again here.
[0104] It should be understood that in the embodiment of the present application, the processor 720 may be a central processing unit (CPU), and the processor 720 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.
[0105] In another embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium may be a non-volatile computer-readable storage medium. The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the garbage classification community governance and supervision method disclosed in the embodiment of the present invention is implemented.
[0106] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the above-described equipment, devices and units can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. Those of ordinary skill in the art can appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.
[0107] In the several embodiments provided by the present invention, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. Units with the same function may also be combined into one unit. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices or units, or may be electrical, mechanical or other forms of connection.
[0108] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.
[0109] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.
[0110] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), disk or optical disk and other media that can store program codes.
[0111] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.
Claims
1. The method for community governance and supervision of garbage classification is characterized by: include: Set up a waste classification assessment and evaluation plan; Collect key data on waste classification related to assessment and evaluation, including community organization participation data, facility maintenance data, and activity participation data; Create dynamic tracking and prediction statistical models based on key data of garbage classification; Dynamic tracking and intelligent prediction are carried out based on dynamic tracking and prediction statistical models; Conduct a comprehensive evaluation of the effectiveness of the waste sorting community based on dynamic tracking and intelligent prediction results; Generate analysis reports based on comprehensive evaluation results of effectiveness; Conduct multi-dimensional analysis and horizontal and vertical analysis based on the analysis report; Formulate a reward mechanism based on the results of multi-dimensional analysis and horizontal and vertical analysis; Based on the feedback from the reward mechanism, a cross-regional collaboration mechanism for garbage sorting communities will be formulated.
2. The method for community management and supervision of garbage classification according to claim 1 is characterized in that: The setting of the garbage classification assessment and evaluation plan includes: Identify key evaluation dimensions; Set evaluation indicators and scoring criteria; Set the initial weights of each dimension; Dynamically adjust weights based on feedback; Set the statistical period for each dimension.
3. The method for community management and supervision of garbage classification according to claim 1 is characterized in that: The comprehensive evaluation of the effectiveness of the garbage classification community based on dynamic tracking and intelligent prediction results includes: Establish a step-by-step review mechanism, including community review, street review, district review and city review; Establishing a review and supplement mechanism; The comprehensive community portrait score is calculated based on the audit results at all levels to obtain a comprehensive evaluation of the effectiveness of garbage classification in the community.
4. The method for community management and supervision of garbage classification according to claim 3 is characterized in that: The step-by-step review mechanism is established, and the step-by-step review includes community review, street review, district review, and city review, including: Conducting preliminary audits at the community level to collect and organize waste sorting data, including sorting accuracy, equipment integrity, and resident participation; Review the audit results of each community at the street level and make suggestions for phased improvements; The district-level departments review the aggregated data at the street level, conduct further analysis and evaluation, and provide scores and feedback on the garbage sorting work of each street; The municipal department will ultimately review the district-level data, conduct a comprehensive analysis of the overall effectiveness of the city’s waste sorting efforts, and formulate and adjust policies.
5. The method for community management and supervision of garbage classification according to claim 3 is characterized in that: The community comprehensive portrait score is calculated based on the audit results at all levels to obtain a comprehensive evaluation result of the effectiveness of garbage sorting in the community, including: Calculate daily operations assessment scores; Calculate district-level assessment scores; Calculate city-level assessment scores; The community comprehensive portrait score is calculated based on the set score weights combined with the calculated daily operation evaluation score, district-level evaluation score, and city-level evaluation score.
6. The method for community management and supervision of garbage classification according to claim 1 is characterized in that: The multi-dimensional analysis and horizontal and vertical analysis based on the analysis report include: Compare data from different regions to identify data differences in regional dimensions; Compare data from the same region at different times to identify data differences over time; Combine the data difference information in the regional dimension and the data difference information in the time dimension to obtain comprehensive analysis results.
7. The method for community management and supervision of garbage classification according to claim 1 is characterized in that: The reward mechanism is formulated based on the analysis results of multi-dimensional stereoscopic analysis and horizontal and vertical analysis, including: Setting incentive forms, including point rewards, honorary titles, and community selection; Formulate points scoring rules; Establish selection rules and selection cycle.
8. The garbage classification community management and supervision device is characterized by: include: A setting unit, used to set a garbage classification assessment plan; A data collection unit, used to collect key data on waste classification related to assessment and evaluation, including community organization participation data, facility maintenance data, and activity participation data; A model creation unit, used to create a dynamic tracking and prediction statistical model based on key data of garbage classification; A model tracking and prediction unit, used for dynamic tracking and intelligent prediction based on a dynamic tracking and prediction statistical model; Comprehensive evaluation unit, used to conduct a comprehensive evaluation of the effectiveness of the garbage sorting community based on dynamic tracking and intelligent prediction results; An analysis report generating unit, used for generating an analysis report according to the comprehensive evaluation result of the effectiveness; The overall analysis unit is used to conduct multi-dimensional analysis and horizontal and vertical analysis based on the analysis report; A reward mechanism formulation unit, used to formulate a reward mechanism based on the analysis results of multi-dimensional stereoscopic analysis and horizontal and vertical analysis; The collaboration mechanism formulation unit is used to formulate a cross-regional collaboration mechanism for the garbage classification community based on feedback from the reward mechanism.
9. A computer device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the garbage classification community governance and supervision method as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, which includes program instructions. When the program instructions are executed by the processor, the processor executes the garbage classification community governance and supervision method as described in any one of claims 1 to 7.