Cooperative pollution supervision method, server, medium and program product

Abstract

The invention provides a pollution collaborative supervision method, a server, a medium and a program product, and relates to the field of pollution supervision. The method comprises the following steps: acquiring air quality condition data, pollution source monitoring data, pollution types and other pollution conditions of a park before a set time length; and then marking the data on a map by different color identifiers. And then determining the pollutant treatment capability of the employees according to historical work data of the employees, and determining an anti-pollution work distribution suggestion in combination with the pollution condition of the park. And after the distribution suggestion is adopted, acquiring antifouling work schedules of different sub-regions and dynamically marking the antifouling work schedules on a map. And finally, when a client instruction is received, the client is controlled to display a map, and the pollution condition of the park and the antifouling work progress are displayed. By implementing the method, a manager can intuitively master pollution conditions of different areas of the park, so that decisions can be made quickly and targeted antifouling measures can be taken conveniently.

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] In the existing pollution prevention and control supervision technology scheme, some traditional environmental monitoring instruments are generally installed at specific locations in the park. These instruments will regularly collect air quality data and monitor some obvious pollution sources. The data obtained will be stored in the database after simple processing for managers to query. The managers will then carry out pollution prevention and control according to the pre-made plan, and arrange staff to check the pollution control situation in the park after the treatment cycle ends.

[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 are 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 capacity of the employees, and displaying the work progress in real time, in the case where pollution control in the prior art is carried out according to a pre-made plan, lacks flexibility and has delayed feedback, unreasonable resource allocation, unintuitive pollution situation presentation, 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 a server of a 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 in the past, and the pollutant treatment capabilities include the treatment efficiency of the target pollution type; determining the work allocation suggestions for anti-pollution work based on the pollutant treatment capabilities and the pollution situation of the park; after determining that the allocation suggestions are adopted, obtaining multiple anti-pollution work progress corresponding to different sub-areas in multiple parks; dynamically marking multiple anti-pollution 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 anti-pollution work progress of the park on the map.

[0007] By adopting the above technical solutions, managers can intuitively understand the pollution situation in different areas of the park, making it easier to make decisions and take targeted anti-pollution measures. At the same time, work allocation suggestions are determined based on the pollutant treatment capabilities of employees, which improves the efficiency and pertinence of anti-pollution work.

[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 in 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 in the park; matching the sub-area with complex pollution type and high pollution severity to an employee with high pollution treatment capacity, and matching the sub-area with simple pollution type and low pollution severity to an employee with low pollution treatment capacity, the employee with high pollution treatment capacity refers to an employee whose capacity ranking result is ranked before a preset ranking, and the employee with low pollution treatment capacity refers to an employee whose capacity ranking result is ranked after a 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 can receive the most suitable treatment, avoids waste of resources, 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 including the enterprise's electricity consumption in each time period, and the historical pollution monitoring data including the pollution concentration and pollution type in each time period of the park; determining the 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; determining the corresponding enterprise electricity consumption threshold based on a 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 exceeded, determining the enterprise's electricity consumption adjustment suggestion, the enterprise's electricity consumption adjustment suggestion includes reducing electricity consumption for time periods that exceed 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 a set period of time, it also includes: obtaining the pollution source environmental file of the enterprise, which includes basic information of the enterprise, enterprise pollution source information, types of pollutants and 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, and 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 for 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.

[0013] By adopting the above-mentioned 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 a 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, 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 the monitoring sites can be obtained and the locations can be marked on the map. When the client queries, the target site can be quickly determined and information can be fed back. Users can easily understand the situation of each monitoring site, providing more reference 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 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 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, causes 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 manner of the first aspect.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Due to the adoption of technical means to obtain various park pollution data and mark them on the map with different colors, and determine work allocation suggestions based on the pollutant treatment capabilities of employees, the problem of non-intuitive presentation of park pollution and difficulty in dynamic changes in pollution prevention and control work in the existing technology is effectively solved, thereby achieving the technical effect of intuitively and accurately displaying the park pollution situation and reasonably allocating pollution prevention work according to the pollutant treatment capabilities of employees.

[0024] 2. By ranking the pollutant treatment capabilities of employees and matching and allocating them according to the type and severity of pollution in the park, the technical means are adopted to effectively solve the problems of lack of specificity and waste of resources in the existing anti-pollution work allocation, thereby fully leveraging the advantages of employees, improving the efficiency of anti-pollution work and targeted technical effects.

[0025] 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, the problem of difficult intuitive judgment of pollution risks of park enterprises and lack of targeted supervision in the existing technology is effectively solved, thereby achieving the technical effect of facilitating management personnel to conduct targeted supervision and reducing the overall pollution risk of the park. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flow chart of the collaborative pollution supervision method in the embodiment of the present application; Figure 2 is another flow chart of the collaborative pollution supervision method in the embodiment of the present application; Figure 3 It is a schematic diagram of a physical device structure of a server in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more listed items.

[0028] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0029] For ease of understanding, the following is a description of the process of the method provided by this implementation. Figure 1 , which is a flow chart of the collaborative pollution supervision method in the embodiment of the present application.

[0030] S101, obtaining the pollution situation of the park before a set period of time, the pollution situation including air quality status data, pollution source monitoring data and pollution type; 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, the monitoring data of each enterprise's pollution source, and the pollution type obtained by monitoring. The data in the pollution monitoring database is obtained by detecting the air through sensors at various air quality monitoring stations or preset locations in the park. The air quality status data may include the concentration values ​​of pollutants such as PM2.5, PM10, sulfur dioxide, nitrogen dioxide, and carbon monoxide. The pollution source monitoring data corresponds to the data monitored by 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. 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.

[0031] S102, marking the air quality status data, the pollution source monitoring data and the pollution type on the map with different color labels; The server will mark the location of each air quality monitoring station with different icons on the map. With the location of the air quality monitoring station as the center, draw circles of different colors around it. The color of the circle is determined according to the air quality index reflected by the monitoring data. For example, a green circle is drawn within the range of excellent air quality index, a yellow circle is drawn within the range of good air quality index, and so on. By looking at the color circles around the monitoring station on the map, you can clearly judge the approximate air quality status of the area. The process of determining the air quality index is as follows: the concentration of each major pollutant is obtained through the monitoring of the air quality monitoring station, and the individual air quality index IAQI of each pollutant is calculated according to the concentration value. IAQI reflects the degree of pollution of the pollutant, and then the comprehensive air quality index AQI is calculated according to the health impact weight of each pollutant. The health impact weight can be set by the management personnel according to the actual situation. The larger the weight, the more serious the health impact. The corresponding level of air quality is divided according to the AQI value, generally 0-50 is classified as excellent, 51-100 is classified as good, etc. The classification standard can be adjusted.

[0032] At the same time, the server marks the location of the enterprise corresponding to the pollution source on the map. For pollution sources whose monitoring data show that the pollution exceeds the emission standard, the location corresponding to the pollution source on the map is marked with a foul odor symbol, and the type of pollution, such as air pollution, water pollution, etc., is displayed. For pollution sources whose monitoring data show that the emission is normal, the location corresponding to the pollution source on the map is marked with a normal symbol or not marked.

[0033] The server will count the number of each type of pollution detected, and use a bar chart in the lower right corner of the map or at a preset location to reflect the distribution of different pollution types. Different colors in the bar chart represent different types of pollution. For example, air pollution is represented by red, water pollution is represented by blue, and soil pollution is represented by yellow. When the mouse hovers over different areas on the bar chart, the specific pollution type and amount will be displayed.

[0034] In this way, managers can intuitively understand the air quality conditions in different areas by checking the color changes around the monitoring stations on the map. By looking at the location of the odor symbols marked on the map, it is possible to clearly identify companies that have excessive pollution emissions. The pollution type distribution map in the lower right corner quickly reflects the changes in the quantity of different pollution types.

[0035] S103, determining the pollutant treatment capabilities corresponding to the employees based on the historical work data of the employees, where the pollutant treatment capabilities include the treatment efficiency for the target pollution type; The server connects to the employee work database to obtain the historical data of each employee's past anti-pollution work. The employee work database contains the anti-pollution management data of multiple employees in the park. The historical data includes the work location, the type of pollution and pollutant to be processed, and the pollution concentration change data during the processing process. The server will count the types of pollution types that each employee has performed anti-pollution work in the past, as well as the average processing efficiency of each pollution type. The processing efficiency can be calculated by the employee's pollution concentration reduction rate for a certain type of pollution in a certain area. For example, the average efficiency of an employee in processing a certain type of pollution is a concentration reduction of 2 units per hour. Then, the server will establish a pollution processing capacity matrix for each employee. The rows of the matrix correspond to different pollution types, the columns represent different types of pollutants, and the matrix elements record the average efficiency of the employee in processing the pollution type corresponding to the pollutant type. For example, [[2, 3, 1], [3, 1, 4]] means that the employee's efficiency in processing PM2.5 of air pollution is 2, PM10 efficiency is 3, and VOCs efficiency is 1; the efficiency of ammonia nitrogen of water pollution is 3, heavy metal efficiency is 1, and petroleum efficiency is 4. Employees are sorted according to the processing efficiency in the matrix, and those with higher efficiency are ranked higher.

[0036] 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.

[0037] S104. Determine the work allocation suggestions for anti-pollution work based on the pollutant treatment capacity and the pollution situation of the park; The server determines the main pollution type and severity of different areas marked on the map. The severity can be determined based on the color change of air quality and the density of the marked pollution source odor symbols. Then, the server divides the area on the map into grids to obtain multiple sub-areas. For each sub-area, determine its pollution type and severity. Match areas with complex pollution types and high pollution severity to employees with high ability to handle the pollution type; conversely, match areas with simple pollution types and low pollution severity to employees with low processing capabilities. The level of processing capacity can be derived from the ranking of employees' processing efficiency for a certain type of pollution. When matching, compare the types of multiple pollutants that need to be handled in each sub-area with the employee pollution processing capacity matrix. Those with a high degree of matching efficiency values ​​are determined as the best matching employees. Finally, the server determines the best matching employees for different sub-areas and forms a distribution recommendation for anti-pollution work, with the best matching anti-pollution staff corresponding to each area. The recommendation is fed back to the manager through the client.

[0038] This matching method, on the one hand, can dispatch employees with higher treatment efficiency to key pollution areas to 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.

[0039] S105, after determining that the allocation suggestion is adopted, obtaining multiple anti-pollution work progress corresponding to different sub-areas in multiple parks; After the manager confirms the adoption of the anti-pollution work allocation suggestion generated in the previous step through the client, the server will generate progress display areas on the map for different park sub-areas that are responsible for multiple employees who adopt the suggestion. The server will send control instructions to the newly deployed sensors in these sub-areas to increase their measurement frequency, such as reporting the latest data every 5 minutes, so as to quickly obtain pollution concentration data in the area. The server will also be equipped with a pollution concentration data receiving module to receive the latest processed pollution concentration data fed back from the sensors in the area.

[0040] At the same time, the server will generate a progress bar for each sub-area. For example, a rectangular frame is displayed at a fixed position in the upper left corner of the sub-area on the map as a progress bar container, and different colors are filled in the rectangular frame 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 the sensors or monitoring stations set at preset positions in the park, and divides the difference by the original concentration to obtain the current treatment progress percentage. For example, if the original concentration is 80, and the current concentration drops to 50 after 2 hours of treatment, the calculated progress is (80-50) / 80=37.5%. The fill percentage of the progress bar is updated immediately after the latest concentration data is obtained.

[0041] In addition, anti-pollution personnel can also manually feedback processing progress data to the server through the mobile terminal app. The server will simultaneously integrate the data from regional sensors and the data from manual feedback, and calibrate multiple data sources to ensure that the progress is as accurate as possible.

[0042] S106, dynamically marking the progress of multiple anti-pollution works on the map; The server can already obtain and display the anti-fouling work progress of each sub-area in real time. In order to more intuitively display the correspondence between progress and area, the server also needs to further mark each area on the map.

[0043] 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.

[0044] Then, the server will generate a progress list in the blank space at the border of the map, showing the identifiers of all sub-areas and the corresponding latest progress percentage. The list will show the progress of each area in the order of the 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 will also be updated synchronously. In this way, the manager can intuitively see the latest progress corresponding to each area identifier in the list, and associate it with the area location of the identifier on the map, so as to more clearly grasp the processing progress of each area. Dynamic progress marking makes supervision more targeted and intuitive.

[0045] 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.

[0046] The server provides a map access interface, through which clients can request to view the map. When the client sends a pollution status viewing instruction to the server map interface, the instruction carries parameters such as the client's location coordinates and the map area requested to be viewed. After receiving the instruction, the server first determines the authority of the client that sent the instruction, and after confirming that it has the authority to view the map data, it further extracts the data of the map part requested by the client according to the parameters in the instruction.

[0047] The server then renders the map image into a map image data for transmission. The map image rendering will be visualized by integrating the current park pollution data and the anti-pollution work progress data. Specifically, it will display the air quality color of the corresponding area, mark the location of the enterprise corresponding to the pollution source, mark the area identifier in each sub-area, and draw a progress bar. After the rendering is completed, the server will feed back the rendered map image data to the client requesting to view it in the form of a response.

[0048] After receiving the response, the client will parse and display the map image returned by the server through its own graphical interface, thus realizing the client's viewing of the map. Users can see the real-time dynamic situation of the park's pollution and anti-pollution progress intuitively presented on the map by color, logo, progress bar, etc.

[0049] 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 color labels, managers can intuitively grasp the pollution conditions in different areas of the park and grasp the progress of regional pollution prevention in real time, thus solving the problem that the pollution prevention work in the prior art is difficult to dynamically adjust and the feedback is delayed.

[0050] 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 progress of anti-pollution work corresponding to different sub-areas in multiple parks.

[0051] 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 be derived from the records of employees completing anti-pollution tasks in the past. The server can obtain the employee work efficiency data in the recent period, or it can only count the efficiency data of the employee in handling the specified pollution type. After obtaining the work efficiency data of the corresponding employees in 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 automatically calculates 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.

[0052] Specifically, the server converts the remaining workload of each area's anti-pollution task into the completion time required according to the corresponding employee's work efficiency. For example, the anti-pollution task in area A is 30% remaining, the VOCs treatment efficiency of the anti-pollution employee in this area is 100 units per hour, and the total amount of VOCs in this area is 1000 units. Then the estimated remaining time for area A is (1000*30%) / 100=3 hours. The server can convert and calculate the estimated remaining time for each area.

[0053] Then, the server sorts the estimated time for each area and arranges them in order of the longest time to obtain a completion time sequence. The last time in the sequence represents the total time for all areas of the park to complete anti-pollution. This total time is the shortest time plan for comprehensive anti-pollution. The server records the calculated shortest time plan for achieving comprehensive anti-pollution in the park as the optimal anti-pollution action plan and saves it in the plan database. The optimal plan includes: 1) the original anti-pollution work distribution; 2) the shortest time data calculated based on the progress of anti-pollution work and employee work efficiency; 3) optimization suggestions for anti-pollution work arrangements for the shortest time. This allows managers to directly call the plan in subsequent anti-pollution work, avoiding the need to recalculate every time and improving work efficiency.

[0054] 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. The pollution source information includes the specific discharge of waste gas, wastewater and solid waste. When the manager needs to understand the pollution situation of a certain enterprise, the client can send a viewing instruction to the server, which 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.

[0055] In some embodiments, the server needs to first collect the environmental archive data of the pollution source of the enterprise. The archive can be derived from the archive database of the environmental monitoring department. The server constructs a pollution risk assessment model, which comprehensively scores the enterprise and calculates the risk index based on multiple factors. The assessment factors may include: pollution source intensity, pollutant emission size, excess multiples, pollutant toxicity: hazard coefficient of different pollutants, population distribution density in the area where the enterprise is located, environmental sensitivity, emission reduction effect of enterprise governance facilities, etc. The risk index of the enterprise is calculated according to the scoring rules, and the index threshold is set to divide the risk level. The model can be designed by environmental management industry experts or obtained through machine learning training. The server inputs the environmental archive data of the pollution source of the enterprise, and obtains the risk index of the enterprise after calculation by the risk assessment model. And determine which risk level the enterprise belongs to based on the index value. After obtaining the pollution risk assessment results of each enterprise, the server will mark them on the map. Among them, the location of high-risk enterprises uses red setting marks, medium-risk enterprises use yellow setting marks, and low-risk enterprises use green setting marks. When the map image data is generated, the location of the enterprise will be rendered on the map with different colors and risk level words. When the client chooses to query an enterprise of a certain risk level, it will send a command to query the risk level to the server. After receiving the command, the server will retrieve the enterprises that meet the target risk level from the enterprise risk assessment results, and generate a map with the target risk level enterprises marked for return. For example, when querying high-risk enterprises, only the red mark of high risk is marked on the returned map, and the marks of enterprises of other levels are filtered out. This allows managers to quickly locate enterprises of the target risk level and take risk prevention measures. In this way, the pollution risk status of different enterprises in the park can be intuitively reflected through the marks of different colors and risk levels on the map. It is beneficial for managers to focus on supervising high-risk enterprises.

[0056] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the collaborative pollution supervision method in the embodiment of the present application.

[0057] S201, obtaining the enterprise's historical electricity consumption data and historical pollution monitoring data, wherein the historical electricity consumption data includes the enterprise's electricity consumption in each period, and the historical pollution monitoring data includes the pollution concentration and pollution type in each period of the park; 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 various air quality monitoring stations 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.

[0058] The server will then conduct data comparison and analysis to calculate the correlation between the electricity consumption of enterprises at different times and the regional pollution concentration. It will determine whether the peak electricity consumption period causes a significant increase in regional pollution and analyze the pollution changes in the corresponding areas of different electricity consumption.

[0059] By comparing enterprise electricity consumption data with regional pollution monitoring data, we can analyze the intrinsic relationship between enterprise electricity consumption and regional pollution, and provide a basis for the subsequent formulation of electricity consumption thresholds.

[0060] S202, determining a corresponding enterprise electricity consumption threshold according to a preset pollution concentration threshold; According to the national or regional air quality standards, the concentration limits of major pollutants are determined. For example, the daily average limit of PM2.5 is 35μg / m3, which can be used as the threshold of regional PM2.5 concentration.

[0061] The server will then combine the relationship between the enterprise's electricity consumption and the 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 the enterprise's daily electricity consumption exceeds 2.5 million kilowatts, the monitoring data shows that the regional PM2.5 daily average exceeds 35μg / m3. Then 2.5 million kilowatts can be used as the enterprise's electricity consumption threshold. In addition, the enterprise's electricity consumption threshold can also be a threshold set by the management personnel based on actual conditions, which is not limited here.

[0062] S203, after collecting the real-time electricity consumption data of the enterprise, determining whether the real-time electricity consumption data of the enterprise exceeds the electricity consumption threshold of the enterprise; The server will obtain the company's real-time electricity consumption data in the current period from the power company's real-time monitoring system. Then, the server will compare the 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.

[0063] If the enterprise electricity consumption threshold is exceeded, step S204 is executed; If the enterprise power consumption threshold is not exceeded, step S205 is executed; S204, determining a power consumption adjustment suggestion for the enterprise, where the power consumption adjustment suggestion for the enterprise includes reducing power consumption during a period exceeding the power consumption threshold of the enterprise; When it is determined that the enterprise's electricity consumption exceeds the threshold during certain periods, the server will generate power regulation suggestions to reduce the electricity consumption during these periods.

[0064] The server can give corresponding suggestions for reducing electricity consumption based on the average threshold-exceeding magnitude during the company's historical threshold-exceeding periods. For example, historically, the average threshold-exceeding amount from 8 to 10 p.m. was 300,000 kilowatts, so the generated electricity adjustment suggestion can be to reduce electricity consumption by 300,000 kilowatts during this 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 suggestions and sending them to the company when an over-threshold is detected.

[0065] In addition, if the over-threshold situation persists during a certain period of time, 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 over-threshold problem.

[0066] S205. Record the good electricity usage situation of the enterprise.

[0067] While continuously monitoring the electricity consumption of enterprises, the server will also record the good electricity consumption of enterprises so that managers can fully understand the situation. For enterprises with good electricity consumption, the server will store their electricity consumption data in the good sample database for reference by other enterprises. It can also generate suggestions such as electricity fee rewards and environmental rewards in the form of reports and send them to the receiving end of the management department.

[0068] 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's electricity consumption and regional pollution, it effectively provides a basis for the subsequent formulation of the enterprise's electricity consumption threshold, and solves the problem that the setting of electricity consumption thresholds in the prior art lacks scientificity and pertinence.

[0069] 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.

[0070] It should be noted that Figure 3The structure of the server shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0071] like Figure 3 As shown, the server includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0072] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. 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. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0073] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0074] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a 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 may be used by or in combination with an instruction execution system, apparatus, or device.

[0075] 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 may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a 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 may also occur in an order different from that marked in the accompanying drawings.

[0076] 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.

[0077] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the server described in the above embodiment; or may exist independently without being assembled into the server. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the server, the server implements the collaborative pollution supervision method provided in the above embodiment.

[0078] 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned 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.

[0079] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0080] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A pollution collaborative supervision method, applied to a server of a supervision system, characterized in that: The method comprises: Obtain the pollution situation of the park before a set time, wherein 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 a map with different color labels; Determine the pollutant treatment capabilities corresponding to the employees based on the historical work data of the employees, wherein the pollutant treatment capabilities include the treatment efficiency for the target pollution types; Determine the work allocation suggestions for anti-pollution work based on the pollutant treatment capacity and the pollution situation of the park; After determining that the allocation suggestion is adopted, obtaining a plurality of anti-pollution work progress corresponding to different sub-areas in a plurality of parks; Dynamically marking the progress of a plurality of said anti-fouling works on said 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 pollution situation of the park and the progress of the anti-pollution work in the park on the map.

2. The method according to claim 1, characterized in that The step of determining the work allocation suggestion of the anti-pollution work according to the pollutant treatment capacity and the pollution situation of the park specifically includes: Sorting 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 ability ranking results are ranked before the preset ranking, and the employees with low pollution handling capabilities refer to employees whose ability ranking results 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 the enterprise's historical electricity consumption data and historical pollution monitoring data, wherein the historical electricity consumption data includes the enterprise's electricity consumption in each period, and the historical pollution monitoring data includes the pollution concentration and pollution type in each period of the park; Determine the 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; According to the preset pollution concentration threshold, determine the corresponding enterprise electricity consumption 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 suggestion for regulating the electricity consumption of the enterprise is determined, and the suggestion for regulating the electricity consumption of the enterprise includes reducing the electricity consumption during the period exceeding the enterprise electricity consumption threshold.

4. The method according to claim 1, characterized in that: After the step of obtaining the pollution status of the park before the set time, it also includes: Obtain the pollution source environmental file of the enterprise, which includes basic information of the enterprise, information on the pollution sources of the enterprise, types of pollutants and information on 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 name, address, contact information and industry information of the enterprise. The basic information of the pollutant discharge unit is used by the 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 environmental files of the pollution sources of the enterprise, it also includes: Conduct pollution risk assessment in combination with the environmental archives of the pollution source 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 to mark the corresponding enterprises with different risk assessment levels 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.

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-fouling tasks and the work efficiency data of the corresponding employees; Calculate the shortest time plan to achieve 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 the step of obtaining the pollution status of the park before the set time, it also includes: Obtain detailed information of multiple pollution monitoring sites in the park, wherein the detailed information at least includes location information, Marking the location information of each monitoring site on a map; When the client sends a request to query the 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 enable the server to execute the method described in any one of claims 1-7.

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 execute the method according to any one of claims 1 to 7.

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