A pollution collaborative supervision method, server, medium and program product

Abstract

The present application provides a collaborative pollution supervision method, server, medium and program product, which relate to the field of pollution supervision. The method includes obtaining the air quality status data, pollution source monitoring data and pollution type and other pollution conditions of the park before a set period of time. These data are then marked on the map with different color labels. Then, the pollutant treatment capacity of the employees is determined based on their historical work data, and the anti-pollution work allocation suggestions are determined in combination with the pollution situation in the park. After the allocation suggestions are adopted, the progress of anti-pollution work in different sub-areas is obtained and dynamically marked on the map. Finally, when the client instruction is received, the client is controlled to display the map to show the pollution situation in the park and the progress of anti-pollution work. By implementing this method, managers can intuitively grasp the pollution situation in different areas of the park, making it easier to make decisions quickly and take targeted anti-pollution measures.

Description

Technical Field

[0001] The present application relates to the field of pollution control, and in particular to a collaborative pollution control method, server, medium and program product. Background Art

[0002] Effective monitoring and control of pollution in industrial parks is crucial to protecting the environment.

[0003] Existing pollution control and supervision technologies typically involve installing traditional environmental monitoring instruments at specific locations within a park. These instruments regularly collect air quality data and monitor obvious pollution sources. The resulting data undergoes simple processing and is stored in a database for management to access. Management then implements pollution control measures according to pre-defined plans, and after each treatment cycle, they dispatch personnel to inspect the park's pollution control progress.

[0004] However, current pollution control is carried out according to pre-made plans, which makes it difficult to allow managers to intuitively see the pollution control situation in the park while making dynamic adjustments based on the control situation. Summary of the Invention

[0005] The present application provides a collaborative pollution supervision method, server, medium and program product, which is used to realize the functions of real-time monitoring of the pollution situation in the park, dynamically adjusting the pollution prevention and control plan according to the pollution situation, timely grasping the progress of the control, intuitively displaying the pollution situation in the park, reasonably allocating the pollution prevention work according to the processing capabilities of the employees and displaying the progress of the work in real time, in the case that pollution control in the prior art is carried out according to a pre-established plan, lacks flexibility and has delayed feedback, unreasonable resource allocation, non-intuitive presentation of the pollution situation, and lacks specificity in the allocation of pollution prevention work.

[0006] In the first aspect, the present application provides a collaborative pollution supervision method, which is applied to the server of the supervision system, and the method includes: obtaining the pollution situation of the park before a set period of time, and the pollution situation includes air quality status data, pollution source monitoring data and pollution type; marking the air quality status data, the pollution source monitoring data and the pollution type on the map with different color labels; determining the multiple pollutant treatment capabilities corresponding to the employees based on the historical work data of multiple employees, and the pollutant treatment capabilities include the treatment efficiency of the target pollution type; determining the work allocation suggestions for pollution prevention work based on the pollutant treatment capabilities and the pollution situation of the park; after determining that the allocation suggestion is adopted, obtaining multiple pollution prevention work progress corresponding to different sub-areas in multiple parks; dynamically marking multiple pollution prevention work progress on the map; after receiving the pollution situation viewing instruction sent by the client, controlling the client to display the map, so that the client displays the pollution situation of the park and the pollution prevention work progress of the park on the map.

[0007] By implementing this technical solution, managers can intuitively understand the pollution situation in different areas of the park, making it easier to make decisions and implement targeted pollution prevention measures. Furthermore, work assignment recommendations are based on employees' pollutant handling capabilities, improving the efficiency and relevance of pollution prevention efforts.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the step of determining the work assignment recommendation for pollution prevention work based on the pollutant treatment capacity and the pollution situation of the park specifically includes: sorting the pollutant treatment capacity from high to low to obtain a capacity ranking result; judging the pollution type and pollution severity of different sub-areas based on the pollution situation of the park; matching the sub-area with complex pollution type and high pollution severity to employees with high pollution treatment capacity, and matching the sub-area with simple pollution type and low pollution severity to employees with low pollution treatment capacity, the employee with high pollution treatment capacity refers to the employee whose capacity ranking result is ranked before the preset ranking, and the employee with low pollution treatment capacity refers to the employee whose capacity ranking result is ranked after the preset ranking; determine the work assignment recommendation based on the matching result.

[0009] By adopting the above technical solution, complex and serious areas are assigned to high-capacity employees, and simple and minor areas are assigned to low-capacity employees, achieving a reasonable allocation of human resources. This ensures that each area receives the most appropriate treatment, avoids resource waste, and improves the overall anti-fouling effect.

[0010] In combination with some embodiments of the first aspect, in some embodiments, after the step of marking the air quality status data, the pollution source monitoring data and the pollution type on the map with different color labels, it also includes: obtaining the enterprise's historical electricity consumption data and historical pollution monitoring data, the historical electricity consumption data includes the enterprise's electricity consumption in each time period, and the historical pollution monitoring data includes the pollution concentration and pollution type in each time period of the park; based on the historical electricity consumption data and the historical pollution monitoring data, determining the correlation between the enterprise's electricity consumption and the pollution situation in the park; based on the preset pollution concentration threshold, determining the corresponding enterprise electricity consumption threshold; after collecting the enterprise's real-time electricity consumption data, judging whether the enterprise's real-time electricity consumption data exceeds the enterprise's electricity consumption threshold; if it exceeds, determining the enterprise's electricity consumption adjustment suggestion, and the enterprise's electricity consumption adjustment suggestion includes reducing electricity consumption for the time period that exceeds the enterprise's electricity consumption threshold.

[0011] By adopting the above technical solution, the enterprise electricity consumption threshold is determined according to the pollution concentration threshold, and adjustment suggestions are given when the real-time electricity consumption data exceeds the threshold. This can help managers encourage enterprises to use electricity rationally, reduce pollution emissions that may be caused by excessive electricity consumption, and control park pollution from the source.

[0012] In combination with some embodiments of the first aspect, in some embodiments, after the step of obtaining the pollution situation of the park before the set time, it also includes: obtaining the pollution source environmental file of the enterprise, which includes the basic information of the enterprise, the pollution source information of the enterprise, the type of pollutants and the treatment facility information; after receiving the enterprise pollution situation viewing instruction sent by the client, obtaining the corresponding basic information of the enterprise's pollutant discharge unit by querying the basic information of the enterprise, which includes the enterprise name, address, contact information and industry information, and the basic information of the pollutant discharge unit is used by management personnel to contact and manage the corresponding enterprise to carry out pollution control work; and the basic information of the pollutant discharge unit is fed back to the client for display.

[0013] By adopting the above technical solutions, it is helpful to timely understand the pollution situation of enterprises, urge enterprises to take control measures, and improve the efficiency and pertinence of pollution control in the park.

[0014] In combination with some embodiments of the first aspect, in some embodiments, after the step of obtaining the pollution source environmental file of the enterprise, it also includes: conducting a pollution risk assessment in combination with the pollution source environmental file to obtain a risk assessment level, which risk assessment level includes a high risk level, a medium risk level and a low risk level; marking the corresponding enterprises of different risk assessment levels with different level identifiers on the map; when an instruction to query the target risk assessment level is received, the corresponding risk enterprise is determined according to the risk assessment level, and the level identifier corresponding to the target risk assessment level is displayed on the map, so that the management personnel can view all enterprises corresponding to the target risk assessment level in the park through the level identifier.

[0015] By adopting the above technical solutions, managers can quickly identify risky enterprises, facilitate targeted supervision of high-risk enterprises, and reduce the overall pollution risk of the park.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after determining that the allocation suggestion is adopted, after the step of obtaining multiple anti-pollution work progress corresponding to different sub-areas in multiple parks, it also includes: obtaining the multiple anti-pollution work progress and the work efficiency data of the corresponding employees; based on the anti-pollution work progress and the work efficiency data, calculating the shortest time plan to achieve comprehensive anti-pollution in the park; recording the shortest time plan as the optimal anti-pollution action plan, and the optimal anti-pollution action plan includes the optimized anti-pollution work allocation and schedule arrangement corresponding to the employees.

[0017] By adopting the above technical solutions, future anti-pollution work can be more scientific and efficient, thereby achieving comprehensive anti-pollution of the park in the shortest time and reducing the impact of pollution on the park environment and production and life.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of obtaining the pollution situation of the park before a set period of time, it also includes: obtaining detailed information of multiple pollution monitoring sites in the park, the detailed information at least including location information, and marking the location information of each monitoring site on the map; when the client sends a request to query the monitoring data of the target monitoring site, searching for the detailed information of the target monitoring site and determining the corresponding location information on the map; sending the detailed information and location information of the target monitoring site to the client for display.

[0019] By adopting the above technical solution, detailed information of monitoring sites can be obtained and their locations can be marked on the map. When the client queries, the target site can be quickly identified and information can be fed back. Users can easily understand the situation of each monitoring site, providing more reference basis for a comprehensive understanding of the pollution situation in the park.

[0020] In a second aspect, the present application provides a server comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code comprising computer instructions, the one or more processors calling the computer instructions to cause the server to execute the method described in the first aspect and any possible implementation of the first aspect.

[0021] In a third aspect, the present application provides a computer-readable storage medium comprising instructions, which, when executed on a server, cause the server to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, the present application provides a computer program product, which, when executed on a server, enables the server to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0024] 1. By adopting the technical means of obtaining pollution data from various parks and marking them on the map with different colors, and determining work allocation suggestions based on the pollutant treatment capabilities of employees, the system effectively solves the problems of the existing technology in that the pollution situation in the park is not intuitive and the anti-pollution treatment work is difficult to change dynamically. It then achieves the technical effect of intuitively and accurately displaying the pollution situation in the park and reasonably allocating anti-pollution work according to the pollutant treatment capabilities of employees.

[0025] 2. By adopting the technical means of ranking employees' pollutant treatment capabilities and matching and allocating them according to the type and severity of pollution in the park, the problem of lack of targeted allocation of anti-pollution work and waste of resources in the existing technology is effectively solved, thereby achieving the full utilization of employees' advantages, improving the efficiency of anti-pollution work and the targeted technical effect.

[0026] 3. Due to the technical means of combining pollution source environmental archives to conduct pollution risk assessment and marking enterprise risk levels with different levels of identification on the map, it effectively solves the problems of difficult to intuitively judge the pollution risks of park enterprises and lack of targeted supervision in existing technologies, thereby achieving the technical effect of facilitating management personnel to carry out targeted supervision and reducing the overall pollution risk of the park. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart of the collaborative pollution supervision method in the embodiment of the present application;

[0028] Figure 2 This is another flow chart of the collaborative pollution supervision method in the embodiment of the present application;

[0029] Figure 3 This is a schematic diagram of the physical device structure of the server in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The terms used in the following examples of the present application are for the purpose of describing specific embodiments only and are not intended to limit the present application. As used in the specification and appended claims of the present application, the singular expressions "a," "an," "said," "above," "the," and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to and encompasses any or all possible combinations of one or more of the listed items.

[0031] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0032] For ease of understanding, the following describes the process of the method provided by this implementation. Figure 1 , which is a flow chart of the collaborative pollution supervision method in an embodiment of the present application.

[0033] S101. Obtaining the pollution status of the park before a set period of time, the pollution status including air quality status data, pollution source monitoring data and pollution type;

[0034] In the industrial park, the server connects to the pollution monitoring database to obtain the air quality monitoring data of each area of ​​the park within a set time period, the monitoring data of each enterprise's pollution source, and the pollution type obtained by monitoring. Among them, the data in the pollution monitoring database is obtained by detecting the air through various air quality monitoring stations in the park or sensors at preset locations. The air quality status data can include the concentration values ​​of pollutants such as PM2.5, PM10, sulfur dioxide, nitrogen dioxide, carbon monoxide, etc. The pollution source monitoring data corresponds to the monitoring data of multiple pollution emission outlets of each enterprise in the park. These data reflect the types and concentrations of pollutants in different enterprises at different times. The server needs to connect to the online monitoring system of each enterprise to pull the monitoring data of the pollution source within the set time period. The pollution type is a classification of various pollutants detected, which may include but is not limited to air pollution, water pollution, garbage pollution and other types.

[0035] S102, marking the air quality status data, the pollution source monitoring data, and the pollution type on a map with different color markings;

[0036] The server will identify the location of each air quality monitoring station on the map with a distinct icon. A ring of different colors will be drawn around the monitoring station, centered at the monitoring station. The ring color is determined by the air quality index (AQI) as measured by the monitoring data. For example, a green ring indicates an excellent AQI, a yellow ring indicates a good AQI, and so on. By examining the colored circles around the monitoring stations on the map, you can clearly determine the general air quality conditions in that area. The AQI is determined as follows: Monitoring stations measure the concentrations of major pollutants. Based on these concentrations, an individual air quality index (IAQI) is calculated for each pollutant. The IAQI reflects the level of pollution. The overall AQI is then calculated based on the health impact weights of each pollutant. These weights can be set by administrators based on specific circumstances. A higher weight indicates a more severe health impact. Air quality is categorized according to the AQI value, with 0-50 generally considered excellent and 51-100 considered good. These classifications are adjustable.

[0037] At the same time, the server marks the location of the corresponding enterprise of the pollution source on the map. For pollution sources whose monitoring data indicates excessive pollution emissions, the corresponding location on the map is marked with a foul odor symbol and the pollution type, such as air pollution or water pollution, is displayed. For pollution sources whose monitoring data indicates normal emissions, the corresponding location on the map is marked with a normal symbol or is not marked.

[0038] The server counts the number of each type of pollution detected and displays a bar chart showing the distribution of each type of pollution in the lower right corner of the map or at a preset location. Different colors in the bar chart represent different types of pollution, such as air pollution in red, water pollution in blue, and soil pollution in yellow. Hovering your mouse over different areas of the bar chart displays the specific pollution type and amount.

[0039] By observing the color changes around monitoring stations on the map, managers can intuitively understand the air quality status of different areas. The locations of odor symbols marked on the map clearly indicate which companies are exceeding pollution emission standards. The pollution type distribution map in the lower right corner quickly reflects the changes in the quantity of different pollution types.

[0040] S103. Determine the pollutant treatment capabilities corresponding to the employees based on their historical work data, where the pollutant treatment capabilities include treatment efficiencies for target pollution types.

[0041] The server connects to the employee work database and retrieves historical data on each employee's past pollution prevention work. The database contains pollution prevention data for multiple employees within the park. This historical data includes work location, pollution type and pollutant type handled, and changes in pollution concentration during the treatment process. The server then compiles statistics on the types of pollution each employee has performed in the past, as well as the average treatment efficiency for each pollution type. Treatment efficiency can be calculated by the rate at which the employee reduces the concentration of a particular pollution type in a specific area. For example, an employee's average treatment efficiency for a particular pollution type is a 2-unit reduction per hour. The server then creates a pollution treatment capacity matrix for each employee. The rows of the matrix correspond to different pollution types, and the columns represent different pollutant types. The matrix elements record the employee's average treatment efficiency for each pollutant type. For example, [[2, 3, 1], [3, 1, 4]] indicates that the employee's treatment efficiency for PM2.5 is 2, PM10 is 3, and VOCs is 1; and for water pollution, the employee's treatment efficiency for ammonia nitrogen is 3, heavy metals is 1, and petroleum is 4. Employees are ranked according to their treatment efficiency in the matrix, with those with higher efficiency ranking higher.

[0042] In this way, the system can clearly identify each employee's ability and efficiency in handling different types of pollution and pollutants, making it easier to make reasonable work allocations based on the pollution situation.

[0043] S104. Determine the allocation of anti-pollution work based on the pollutant treatment capacity and the pollution situation of the park;

[0044] The server determines the primary pollution type and severity for each area marked on the map. Severity is determined by color changes in the air quality and the density of the marked pollution source odor symbols. The server then divides the map into a grid, creating multiple sub-areas. For each sub-area, the server determines the pollution type and severity. Areas with complex pollution types and high pollution severity are assigned to employees with high capacity to handle that type of pollution. Conversely, areas with simple pollution types and low pollution severity are assigned to employees with low capacity. Capacity is determined by ranking employees' efficiency in handling specific pollution types. During matching, the various pollutants to be handled in each sub-area are compared to the employee pollution handling capacity matrix. Employees with the highest matching efficiency values ​​are identified as the best match. Finally, the server identifies the best matching employees for each sub-area and forms a recommended allocation of pollution prevention work, assigning the most suitable pollution prevention staff member to each area. This recommendation is fed back to the administrator via the client.

[0045] This matching method, on the one hand, can dispatch employees with higher treatment efficiency to key pollution areas and improve the treatment effect; on the other hand, it can also reasonably arrange employees according to their strengths, mobilize their enthusiasm and improve work efficiency.

[0046] S105. After determining that the allocation suggestion is adopted, obtaining multiple anti-pollution work progress corresponding to different sub-areas in the multiple parks;

[0047] After the manager confirms the anti-pollution work assignment suggestion generated in the previous step through the client, the server generates progress display areas on the map for the different campus sub-areas responsible for the multiple employees who adopted the suggestion. The server then sends control instructions to the newly deployed sensors in these sub-areas, increasing their measurement frequency, for example, to report the latest data every 5 minutes, to quickly obtain pollution concentration data within the area. The server also configures a pollution concentration data receiving module to receive the latest processed pollution concentration data from the sensors in the area.

[0048] At the same time, the server generates a progress bar for each sub-area. For example, a rectangular box is displayed in a fixed position in the upper left corner of the sub-area on the map as the progress bar container. The rectangular border is filled with different colors to represent the progress. The server determines the difference between the latest concentration data at each moment and the original concentration data before treatment from sensors or monitoring stations set up at preset locations within the park. The difference is divided by the original concentration to obtain the current treatment progress percentage. For example, if the original concentration is 80, and after two hours of treatment, the current concentration drops to 50, the calculated progress is (80-50) / 80 = 37.5%. The progress bar fill percentage is updated immediately after each latest concentration data is obtained.

[0049] Furthermore, anti-pollution personnel can manually submit progress data to the server via a mobile app. The server then integrates data from regional sensors and manual feedback, calibrating multiple data sources to ensure the most accurate progress possible.

[0050] S106, dynamically marking the progress of multiple anti-pollution work on the map;

[0051] The server can already obtain and display the progress of anti-pollution work in each sub-area in real time. To more intuitively show the correspondence between progress and area, the server needs to further mark each area on the map.

[0052] Specifically, the server will set a different area identifier for each sub-area, such as 1, 2, 3, etc. These identifiers will be marked in the corresponding areas on the map, for example, identifier 1 is displayed in the center of sub-area 1.

[0053] The server then generates a progress list in the blank area at the map's border, displaying the identifiers of all sub-areas and their corresponding latest progress percentages. The list displays the progress of each area in order of their identifiers. For example: Area 1 45%, Area 2 65%, Area 3 35%. When the progress bar data is updated, the progress percentage in the list is also updated synchronously. This allows managers to intuitively see the latest progress corresponding to each area identifier in the list, linking it to the area's location on the map, providing a clearer understanding of the processing progress of each area. Dynamic progress markers make supervision more targeted and intuitive.

[0054] S107 . After receiving the pollution situation viewing instruction sent by the client, the client is controlled to display the map, so that the client displays the pollution situation of the park and the progress of the anti-pollution work on the map.

[0055] The server provides a map access interface through which clients can request to view the map. When a client sends a pollution status request to the server's map interface, the request carries parameters such as the client's location coordinates and the requested map area. Upon receiving the request, the server first checks the client's permissions to view the map data. Once the client has permission to view the map data, it then extracts the data for the requested portion of the map based on the parameters in the request.

[0056] The server then renders the map image into a single piece of map data for transmission. This map image visualization combines current park pollution data and pollution prevention progress data. Specifically, it displays the corresponding area's air quality color, identifies the location of the enterprise corresponding to the pollution source, annotates each sub-area with a regional identifier, and draws a progress bar. Once rendering is complete, the server returns the rendered map image data to the client requesting it in the form of a response.

[0057] After receiving the response, the client parses and displays the map image returned by the server through its own graphical interface, thus enabling the client to view the map. Users can see the real-time dynamic status of the park's pollution and anti-pollution progress through intuitive color, symbols, and progress bars on the map.

[0058] In the embodiment of the present application, due to the technical means of obtaining various pollution data of the park and marking them on the map with different colors, managers can intuitively grasp the pollution conditions in different areas of the park and grasp the progress of regional pollution prevention in real time, solving the problem of dynamic adjustment of pollution prevention work and delayed feedback in the existing technology.

[0059] In some embodiments, the server will further collect work efficiency data of employees responsible for anti-pollution work in each area based on obtaining the anti-pollution work progress corresponding to different sub-areas in multiple parks.

[0060] Specifically, the server will associate the anti-pollution staff in each area and obtain their employee identification. The server will then query the employee efficiency database, which stores the historical work efficiency data of each employee. These work efficiency data can come from the records of employees completing anti-pollution tasks in the past. The server can obtain the employee work efficiency data for a recent period of time, or it can only count the efficiency data of the employee in handling a specified type of pollution. After obtaining the work efficiency data of employees corresponding to all anti-pollution work areas, the server can determine the work efficiency of anti-pollution work in different areas. In addition, if there is not enough historical data in the employee efficiency database, the work efficiency of different employees can be pre-classified by asking the management staff for their experience, such as Class A has the highest efficiency and Class C has the lowest efficiency, which can also be used for subsequent calculations. In some embodiments, employees can manually enter the time to complete the task and the amount of pollution handled, and the system will automatically calculate the work efficiency, so that more accurate first-hand data can be obtained. After the server obtains the remaining progress percentage of the anti-pollution work in each area and the work efficiency of the corresponding employees, it can calculate the shortest time plan to achieve comprehensive anti-pollution in the park.

[0061] Specifically, the server converts the remaining workload for each area's pollution prevention task into the time required to complete it based on the corresponding employee's work efficiency. For example, if Area A has 30% of its pollution prevention task remaining, the VOCs treatment efficiency of the pollution prevention employee in that area is 100 units per hour, and the total VOC volume in that area is 1000 units, then the estimated remaining time for Area A is (1000 * 30%) / 100 = 3 hours. The server can convert this into the estimated remaining time for each area.

[0062] The server then sorts the estimated times for each area, arranging them by longest time, to create a completion time sequence. The last time in this sequence represents the total time required to complete pollution prevention in all areas of the park. This total time is the shortest possible time for comprehensive pollution prevention. The server records the calculated shortest possible time plan for achieving comprehensive pollution prevention in the park as the optimal pollution prevention action plan and saves it in the plan database. This optimal plan includes: 1) the original allocation of pollution prevention work; 2) the shortest time data calculated based on the progress of pollution prevention work and employee work efficiency; and 3) optimization suggestions for arranging pollution prevention work to minimize the time. This allows managers to directly call on this plan for subsequent pollution prevention work, avoiding the need to recalculate each time and improving work efficiency.

[0063] In some embodiments, the server is connected to the enterprise archive database of the environmental protection department to query and obtain the stored enterprise pollution source environmental archive data. As part of the archival management of the pollution status of the enterprise, the pollution source environmental archive will record the basic information of the enterprise, pollution source information, pollutant types and treatment facility information. Basic information includes the name, address, contact information, industry, etc. of the enterprise. Pollution source information includes the specific discharge of waste gas, wastewater and solid waste. When the management personnel need to understand the pollution situation of a certain enterprise, they can send a viewing instruction to the server through the client. The instruction contains the identification information of the enterprise to be queried. After receiving the instruction, the server will query and feedback the basic information of the enterprise in the pollution source environmental archive, and obtain its name, address, contact information and industry information. This information can help environmental management personnel quickly determine the identity and contact information of the enterprise, and facilitate the contact and management of subsequent pollution control work, so it is extracted and uniformly classified as the basic information of the pollutant discharge unit.

[0064] In some embodiments, the server first collects environmental data on pollution sources from enterprises. This data can be sourced from the environmental monitoring department's archive database. The server then constructs a pollution risk assessment model that integrates multiple factors to assign a score to the enterprise and calculate a risk index. Assessment factors may include: pollution source intensity, pollutant emission volume and the multiples exceeding the standard, pollutant toxicity (hazard coefficient of different pollutants), population density in the area where the enterprise is located, environmental sensitivity, and the effectiveness of the enterprise's remediation facilities in reducing emissions. The enterprise's risk index is calculated based on a scoring rule, and index thresholds are set to categorize risk levels. The model can be designed by environmental management experts or trained through machine learning. The server inputs the enterprise's environmental data on pollution sources and, through the risk assessment model, calculates the enterprise's risk index. Based on the index value, the enterprise is assigned a high, medium, or low risk level. After receiving the pollution risk assessment results for each enterprise, the server marks them on a map. High-risk enterprises are marked in red, medium-risk enterprises in yellow, and low-risk enterprises in green. When the map image data is generated, the enterprise locations are rendered on the map with corresponding markers in different colors and risk levels. When a client queries for enterprises with a specific risk level, it sends a risk level query command to the server. Upon receiving this command, the server retrieves the enterprises that meet the target risk level from the enterprise risk assessment results and generates a map showing the enterprises at that risk level. For example, when querying for high-risk enterprises, only the high-risk red markers are displayed on the returned map, filtering out the markers for enterprises at other risk levels. This allows managers to quickly locate enterprises at the target risk level and take risk prevention measures. The different colors and risk levels on the map provide a visual representation of the pollution risk status of different enterprises within the park, helping managers prioritize and supervise high-risk enterprises.

[0065] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , which is another flow chart of the collaborative pollution supervision method in the embodiment of the present application.

[0066] S201. Obtain historical electricity consumption data and historical pollution monitoring data of the enterprise, wherein the historical electricity consumption data includes the electricity consumption of the enterprise at each time period, and the historical pollution monitoring data includes the pollution concentration and pollution type at each time period in the park;

[0067] The server will connect to the power company's electricity consumption database to obtain the electricity consumption data of each enterprise in the park in the past year or other set time. These historical electricity consumption data can include detailed electricity consumption of enterprises in different periods and months. At the same time, the server is also connected to the pollution monitoring database of the environmental monitoring department to obtain the pollution concentration data and pollution types detected by each air quality monitoring station in the park during the same period in the past. The monitoring station will regularly detect the concentration of pollutants such as PM2.5, PM10, SO2, NO2, VOC, etc. in the air and enter them into the database. The server can determine the representative monitoring stations around the enterprise based on the coordinates of the monitoring stations and obtain their historical monitoring data as the pollution status of the enterprise area.

[0068] The server then conducts comparative data analysis, calculating the correlation between a company's electricity consumption at different times and regional pollution concentrations. This helps determine whether peak electricity consumption periods lead to significantly increased regional pollution and analyzes changes in pollution levels in response to different electricity consumption patterns.

[0069] By comparing enterprise electricity consumption data with regional pollution monitoring data, we can analyze the intrinsic connection between enterprise electricity consumption and regional pollution, and provide a basis for the subsequent formulation of electricity consumption thresholds.

[0070] S202: Determine a corresponding enterprise electricity consumption threshold based on a preset pollution concentration threshold;

[0071] Determine the concentration limits of major pollutants based on national or regional air quality standards. For example, the daily average limit for PM2.5 is 35μg / m3, which can serve as the regional PM2.5 concentration threshold.

[0072] The server then combines the relationship between the enterprise's electricity consumption and regional pollution concentration obtained in the previous step to determine the enterprise's electricity consumption threshold corresponding to different pollutant concentration thresholds. For example, by analyzing historical data, it is determined that when an enterprise's daily electricity consumption exceeds 2.5 million kilowatts, and monitoring data shows that the regional daily average PM2.5 value exceeds 35μg / m3, 2.5 million kilowatts can be used as the enterprise's electricity consumption threshold. Alternatively, the enterprise's electricity consumption threshold can be set by management personnel based on actual conditions, which is not limited here.

[0073] S203: After collecting the enterprise's real-time electricity consumption data, determine whether the enterprise's real-time electricity consumption data exceeds the enterprise's electricity consumption threshold;

[0074] The server will obtain the company's real-time electricity consumption data during the current period from the power company's real-time monitoring system. Then, the server will compare the obtained company's real-time electricity consumption with the set electricity consumption threshold to determine whether the real-time electricity consumption exceeds the threshold. The server will continue to obtain the company's real-time electricity consumption on a regular basis and determine whether it exceeds the threshold to monitor whether the company's electricity consumption is normal.

[0075] If the enterprise electricity consumption threshold is exceeded, step S204 is executed;

[0076] If the enterprise's electricity consumption threshold is not exceeded, step S205 is executed;

[0077] S204: Determine a power consumption adjustment suggestion for the enterprise, where the power consumption adjustment suggestion includes reducing power consumption during periods exceeding the enterprise's power consumption threshold;

[0078] When it is determined that the enterprise's electricity consumption exceeds the threshold during certain periods, the server will generate power adjustment suggestions to reduce the electricity consumption during these periods.

[0079] The server can give corresponding recommendations for reducing electricity consumption based on the average magnitude of the over-threshold during the company's historical over-threshold periods. For example, if the average over-threshold amount from 8 to 10 p.m. in the past was 300,000 kilowatts, then the generated electricity adjustment recommendation could be to reduce electricity consumption by 300,000 kilowatts during that period. It is also possible to determine which links can adjust electricity consumption by querying the company's production process. For example, it is recommended to shut down some high-power equipment during non-main production periods in the evening, appropriately lower the air-conditioning temperature, etc., to reduce electricity consumption. Specific electricity adjustment measures can also be set based on the experience of managers. The server is only responsible for automatically generating electricity adjustment recommendations and sending them to the company when an over-threshold is detected.

[0080] In addition, if the threshold-exceeding situation persists during a certain period, restrictions on electricity consumption during that period can be added in advance to forcibly limit the company's maximum electricity consumption during that period, thereby fundamentally solving the threshold-exceeding problem.

[0081] S205. Record the good electricity usage of the enterprise.

[0082] While continuously monitoring corporate electricity usage, the server also records good performance records, providing management with a comprehensive understanding. For companies with good performance, the server stores their data in a database of good examples for other companies to reference. Reports can also be generated to generate recommendations for electricity and environmental incentives, which can be sent to management.

[0083] In the embodiment of the present application, since a technical means is adopted to obtain the historical electricity consumption data and historical pollution monitoring data of the enterprise and to compare and analyze the intrinsic relationship between the enterprise electricity consumption and regional pollution, it effectively provides a basis for the subsequent formulation of the enterprise electricity consumption threshold, and solves the problem that the setting of electricity consumption thresholds in the existing technology lacks scientificity and pertinence.

[0084] The following describes the server in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , is a schematic diagram of a physical device structure of a server in an embodiment of the present application.

[0085] It should be noted that Figure 3 The structure of the server shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0086] like Figure 3 As shown, the server includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes, such as the methods described in the above embodiments, based on programs stored in a read-only memory (ROM) 302 or programs loaded from a storage unit 308 into a random access memory (RAM) 303. RAM 303 also stores various programs and data required for system operation. CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to bus 304.

[0087] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, push button switches, and the like; an output section 307 including a liquid crystal display (LCD), an audio output device, indicator lights, and the like; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. Removable media 311, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 310 as needed, so that computer programs read from the removable media can be installed in the storage section 308 as needed.

[0088] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 309 and / or installed from removable media 311. When executed by the central processing unit (CPU) 301, the computer program performs the various functions defined in the present invention.

[0089] It should be noted that specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0090] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings.

[0091] Specifically, the server of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the collaborative pollution supervision method provided in the above embodiment is implemented.

[0092] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the server described in the above embodiments, or may exist independently and not incorporated into the server. The storage medium carries one or more computer programs, which, when executed by a processor of the server, enable the server to implement the collaborative pollution monitoring method provided in the above embodiments.

[0093] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0094] As used in the above embodiments, the term “when” may be interpreted to mean “if” or “after” or “in response to determining that” or “in response to detecting that”, depending on the context. Similarly, the phrases “upon determining that” or “if (stated condition or event) is detected” may be interpreted to mean “if determining that” or “in response to determining that” or “upon detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

[0095] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A collaborative pollution monitoring method, applied to a server of a monitoring system, characterized in that: The method comprises: Obtaining the pollution status of the park before a set period of time, including air quality status data, pollution source monitoring data and pollution type; Marking the air quality status data, the pollution source monitoring data and the pollution types on a map with different color markings; Determining the pollutant treatment capabilities of multiple employees based on their historical work data, including the treatment efficiency for a target pollution type, which is calculated by the employee's rate of decrease in the concentration of the target pollution type in the area; Determine work allocation recommendations for pollution prevention work based on the pollutant treatment capacity and the pollution situation in the park; After determining that the allocation suggestion is adopted, obtaining a plurality of anti-pollution work progress corresponding to different sub-areas in the plurality of parks; Dynamically marking the progress of multiple anti-pollution tasks on the map; After receiving the pollution situation viewing instruction sent by the client, the client is controlled to display the map, so that the client displays the park pollution situation and the anti-pollution work progress of the park on the map.

2. The method according to claim 1, characterized in that The step of determining a work allocation recommendation for pollution prevention work based on the pollutant treatment capacity and the pollution situation of the park specifically includes: Ranking the pollutant treatment capabilities from high to low to obtain a capability ranking result; Determine the pollution type and severity of different sub-areas based on the pollution situation of the park; According to the pollution type and the pollution severity, the sub-areas with complex pollution types and high pollution severity are matched to employees with high pollution handling capabilities, and the sub-areas with simple pollution types and low pollution severity are matched to employees with low pollution handling capabilities. The employees with high pollution handling capabilities refer to employees whose capabilities are ranked before the preset ranking, and the employees with low pollution handling capabilities refer to employees whose capabilities are ranked after the preset ranking. The work assignment suggestion is determined according to the matching result.

3. The method according to claim 1, characterized in that After the step of marking the air quality status data, the pollution source monitoring data, and the pollution type on the map with different color markings, the method further includes: Obtaining historical electricity consumption data and historical pollution monitoring data of the enterprise, wherein the historical electricity consumption data includes the electricity consumption of the enterprise in each time period, and the historical pollution monitoring data includes the pollution concentration and pollution type in each time period of the park; Determining a correlation between the enterprise's electricity consumption and the pollution situation in the park based on the historical electricity consumption data and the historical pollution monitoring data; Determine the corresponding enterprise electricity consumption threshold based on the preset pollution concentration threshold; After collecting the enterprise's real-time electricity consumption data, determining whether the enterprise's real-time electricity consumption data exceeds the enterprise's electricity consumption threshold; If it exceeds, then a power consumption adjustment suggestion for the enterprise is determined, and the power consumption adjustment suggestion for the enterprise includes reducing the power consumption for the period exceeding the power consumption threshold of the enterprise.

4. The method according to claim 1, wherein After obtaining the pollution status of the park before the set time, the following steps are also included: Obtaining the enterprise's pollution source environmental files, which include basic information about the enterprise, information about the enterprise's pollution sources, types of pollutants, and information about treatment facilities; After receiving the enterprise pollution status check instruction sent by the client, the basic information of the pollutant discharge unit of the corresponding enterprise is obtained by querying the basic information of the enterprise. The basic information of the pollutant discharge unit includes the enterprise name, address, contact information and industry information. The basic information of the pollutant discharge unit is used by management personnel to contact and manage the corresponding enterprise to carry out pollution control work; The basic information of the pollutant discharge unit is fed back to the client for display.

5. The method according to claim 4, characterized in that After obtaining the enterprise's pollution source environmental files, it also includes: Conducting a pollution risk assessment in conjunction with the pollution source environmental archive to obtain a risk assessment level, wherein the risk assessment level includes a high risk level, a medium risk level, and a low risk level; Use different level labels on the map to mark the corresponding enterprises of different risk assessment levels; When an instruction to query the target risk assessment level is received, the corresponding risk enterprise is determined according to the risk assessment level, and the level identifier corresponding to the target risk assessment level is displayed on the map, so that the management personnel can view all enterprises corresponding to the target risk assessment level in the park through the level identifier.

6. The method according to claim 1, characterized in that After determining that the allocation suggestion is adopted, after the step of obtaining multiple anti-pollution work progress corresponding to different sub-areas in multiple parks, the method further includes: Obtaining the progress of the plurality of anti-pollution tasks and the work efficiency data of the corresponding employees; Calculate the shortest time plan for achieving comprehensive pollution prevention in the park based on the pollution prevention work progress and work efficiency data; The shortest time plan is recorded as an optimal anti-pollution action plan, and the optimal anti-pollution action plan includes the optimized anti-pollution work allocation and schedule arrangement corresponding to the employees.

7. The method according to claim 1, characterized in that After obtaining the pollution status of the park before the set time, the following steps are also included: Obtain detailed information of multiple pollution monitoring sites within the park, the detailed information including at least location information, Marking the location information of each monitoring site on a map; When a client sends a request to query monitoring data of a target monitoring site, searching for detailed information of the target monitoring site and determining the corresponding location information on the map; The detailed information and the location information of the target monitoring site are sent to the client for display.

8. A server, characterized in that: The server includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the server to execute the method according to any one of claims 1 to 7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a server, the server is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a server, the server is caused to perform the method according to any one of claims 1 to 7.

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