Park environmental protection supervision method and system based on multi-data adaptive processing

Abstract

The invention discloses a park environmental protection supervision method and system based on multi-data adaptive processing, relates to the technical field of environmental protection, and solves the problems that when an existing park environmental protection supervision method is applied to a large comprehensive park, the pollution condition in the park is difficult to find in time due to various pollutant data types and large data volume, and the environmental protection efficiency is improved. And thus, the park management efficiency is reduced. Comprising the steps of obtaining input information of each enterprise in a to-be-supervised park; dividing the supervision area based on the input information to obtain a plurality of supervision sub-areas; generating a plurality of analysis priorities of the supervision sub-regions based on the input information of each enterprise in each supervision sub-region; sequentially acquiring monitoring data based on the analysis priorities, and analyzing based on the monitoring data to obtain monitoring data analysis results of the supervision sub-regions; performing early warning based on a monitoring data analysis result; the pollution condition of each supervision sub-region can be analyzed in time, early warning is carried out in time, and the park management efficiency is improved.

Description

Technical Field

[0001] This application belongs to the field of environmental protection technology, specifically a park environmental protection supervision method and system based on multi-data adaptive processing. Background Technology

[0002] Existing technology (invention patent with publication number CN116822913B) discloses a big data-based environmental protection service system for smart parks. This system includes a data acquisition module, a data processing module, an alarm module, and an environmental protection service module. The invention uses the data processing module to calculate the pollution levels of waste, water, noise, and air from the data acquisition module, based on the waste, water, noise, and air pollution levels. It then manages waste, water, noise, and air pollution based on these levels, enabling real-time monitoring of multiple aspects of environmental pollution. Upon detection of pollution, timely pollution management is implemented, and park staff are mobilized to provide environmental protection services.

[0003] The aforementioned smart park environmental protection service system collects data from various aspects of the park in real time by setting up a large number of different types of monitoring sensors, and then analyzes the collected data in real time to obtain the pollution situation at various locations in the park. However, due to the large amount of data collected in real time and the variety of data types, it is difficult to analyze this data simultaneously. This will cause data delays, lags, and congestion during the analysis process, resulting in reduced efficiency of park management. Therefore, a park environmental protection supervision method and system based on multi-data adaptive processing is needed. Summary of the Invention

[0004] This application provides a method and system for environmental protection supervision of industrial parks based on multi-data adaptive processing. It solves the technical problem that existing environmental protection supervision methods for industrial parks, when applied to large comprehensive industrial parks, are difficult to detect pollution in a timely manner due to the diverse types and large volume of pollutant data, which leads to reduced efficiency in park management.

[0005] To achieve the above objectives, this application adopts the following technical solution: Firstly, a method for environmental protection supervision of industrial parks based on adaptive multi-data processing is provided, including: The process involves: acquiring the input information of each enterprise in the park to be regulated; dividing the regulated area into several sub-regions based on the input information; generating several analysis priorities for each sub-region based on the input information of each enterprise in each sub-region; and defining the analysis priorities as the priorities of various pollution forms within each sub-region. Based on the analysis priority, the monitoring data of the regulatory sub-regions are obtained sequentially, and the monitoring data analysis results of the regulatory sub-regions are obtained based on the monitoring data analysis results; early warning is issued based on the monitoring data analysis results.

[0006] Based on the above technical solution, in the park environmental protection supervision method based on multi-data adaptive processing provided in this application, the following steps are taken: First, the input information of each enterprise in the park to be supervised is obtained. Then, the supervision area is divided into several supervision sub-areas based on the input information. Next, several analysis priorities for each supervision sub-area are generated based on the input information of each enterprise in each supervision sub-area. Then, monitoring data within the supervision sub-area is obtained sequentially according to the analysis priorities, and the monitoring data analysis results for the supervision sub-area are obtained based on the monitoring data analysis results. Finally, early warnings are issued based on the monitoring data analysis results. By dividing the monitoring data corresponding to each supervision sub-area and analyzing the monitoring data of each supervision sub-area in stages according to the analysis priorities, the pollution situation of each supervision sub-area can be analyzed in a timely manner, and early warnings can be issued promptly, thereby improving the efficiency of park management.

[0007] In conjunction with the first aspect above, in one possible implementation, the regulatory area is divided based on the enterprise's entered information to obtain several regulatory sub-regions, including: Extract the waste form and waste percentage of each production waste from the information entered by each enterprise; the waste form includes solid waste, liquid waste and gaseous waste; the waste percentage is the proportion of the corresponding waste form in the total waste; Extract the enterprise coordinates from the information entered by each enterprise; integrate the enterprise coordinates and the proportion of waste in each form of waste into the corresponding enterprise feature vector according to the set order; perform cluster analysis on the feature vectors of each enterprise to obtain several clusters; divide each enterprise in the same cluster into the same regulatory sub-region; and obtain the regulatory sub-regions corresponding to each cluster in turn.

[0008] In conjunction with the first aspect above, in one possible implementation, several analysis priorities are generated based on the information entered by each enterprise in each regulatory sub-region, including: Historical emission data is extracted from the information entered by each enterprise within the regulated sub-region. The historical emission data includes data such as the emission volume of various waste materials. The historical emission data is then input into a risk analysis model to obtain an emission risk score for the pollutants emitted in the regulated sub-region. The higher the emission risk score, the more serious the emission of pollutants in the region or the higher the risk. Extract the waste type and waste percentage from the information entered by each enterprise in the regulated sub-region; calculate the average waste percentage of the same waste type for each enterprise in the regulated sub-region; and sequentially obtain the average waste percentage of each waste type. The product of the emission risk score of the regulated sub-region and the average value of the waste form is used as the analysis priority for the corresponding waste form in the regulated sub-region.

[0009] In conjunction with the first aspect above, in one possible implementation, one training method for the risk analysis model includes: Acquire several historical emission data and their corresponding emission risk scores; integrate the historical emission data and their corresponding emission risk scores into several training data and test data. The AI ​​model is trained using training data and tested using validation data. The final result is a risk analysis model with historical emission data as input and emission risk score as output. The AI ​​model includes a BP neural network model and an RBF neural network model.

[0010] In conjunction with the first aspect above, in one possible implementation, monitoring data within the monitored sub-regions are acquired sequentially based on analysis priority, and the monitoring data analysis results are obtained based on the analysis of the monitoring data, including: S1: Obtain several analysis priorities for each regulatory sub-region, and construct a region priority sorting table and an analysis priority sorting table based on each of the analysis priorities; S2: Obtain the regulatory sub-region corresponding to analysis priority number 1 in the regional priority sorting table; obtain the monitoring data of the corresponding analysis priority in the regulatory sub-region; S3: Extract each monitoring item from the monitoring data, and determine in turn whether the monitoring value of each monitoring item is within the set warning range; if yes, record the main monitoring status of the monitoring item as qualified; otherwise, record the main monitoring status of the monitoring item as exceeding the standard. S4: Determine whether there is an out-of-standard status for the main monitoring status corresponding to each monitoring item; if yes, set the main monitoring result of the regulatory sub-area to out of standard and output the main monitoring result; proceed to S5; if no, set the main monitoring result of the regulatory sub-area to qualified and output the main monitoring result; proceed to S6; S5: Obtain the analysis priority ranking table of the regulatory sub-regions corresponding to the regulatory data, and obtain the monitoring data corresponding to the analysis priority in sequence according to the order of the analysis priority table; obtain the comprehensive monitoring result of the regulatory sub-region based on the analysis of each monitoring data; proceed to S8; S6: Obtain the analysis priority number M corresponding to the regulatory sub-region, and determine whether M is less than N, where N is the maximum number in the region priority ranking table; if yes, proceed to step S7; if no, proceed to supplementary analysis; the supplementary analysis is the data analysis of other monitoring data of each regulatory sub-region that has not generated comprehensive monitoring results. S7: Obtain the corresponding monitoring data in the regulatory sub-area corresponding to the analysis priority number M+1; Proceed to S3; S8: Output comprehensive monitoring results, which include main monitoring results and comprehensive monitoring results.

[0011] In conjunction with the first aspect above, in one possible implementation, the region priority sorting table is constructed in the following ways: Extract several analysis priorities from each regulatory sub-region, sort the largest analysis priorities in each regulatory sub-region in descending order, and use the ranking as the corresponding analysis priority and the corresponding regulatory sub-region number, thereby generating a regional priority ranking table.

[0012] In conjunction with the first aspect above, one possible implementation of the analysis priority ranking table includes: Extract several analysis priorities from the regulatory sub-regions, and sort each analysis priority in descending order to generate an analysis priority ranking table.

[0013] In conjunction with the first aspect above, in one possible implementation, the supplementary analysis includes the following steps: Obtain each regulatory sub-region whose main monitoring results are qualified, and the corresponding number of the regulatory sub-region in the region priority sorting table. Sort each regulatory sub-region according to the order of its corresponding number to obtain a supplementary analysis sorting table. Following the order of the supplementary analysis sorting table, the analysis priority sorting tables for each regulatory sub-region are obtained sequentially. Based on the sorting order of the analysis priorities, the monitoring data corresponding to each analysis priority is obtained. Based on the analysis of the monitoring data, the comprehensive monitoring results of the regulatory sub-region are obtained.

[0014] In conjunction with the first aspect above, in one possible implementation, the comprehensive monitoring result is obtained based on the analysis of various monitoring data, including: The monitoring items in each monitoring data are obtained sequentially to obtain several pollutant correlation maps; the pollutant correlation maps include the morphology of several related pollutants and the correlation between pollutants of each morphology. The monitoring items corresponding to each form of pollutant in the pollutant association map are obtained, and the monitoring values ​​of each monitoring item are summed to obtain the comprehensive monitoring value corresponding to the pollutant association map; specifically... If the comprehensive monitoring value is within the set comprehensive warning range, then the comprehensive monitoring results of the several monitoring items corresponding to the pollutant association map are set to exceed the standard; otherwise, the comprehensive monitoring results of the several monitoring items corresponding to the pollutant association map are set to qualified.

[0015] In conjunction with the first aspect above, in one possible implementation, the early warning based on monitoring data analysis results includes: Extract the main monitoring results and comprehensive monitoring results from the monitoring data analysis results corresponding to the regulatory sub-region; when the main monitoring result exceeds the standard, issue an early warning for the regulatory sub-region; when the comprehensive monitoring result exceeds the standard, issue an early warning for the regulatory sub-region; the early warning includes a display warning, that is, highlighting the monitoring items corresponding to the main monitoring results and comprehensive monitoring results on the corresponding display device, such as changing the background color of the display to red or yellow.

[0016] Secondly, this application provides a park environmental protection monitoring device based on multi-data adaptive processing, comprising: a processor and a storage medium; the storage medium includes instructions, and the processor is used to execute the instructions to implement the method described in the first aspect and any possible implementation thereof. This park environmental protection monitoring device based on multi-data adaptive processing can be an electronic device or a chip within an electronic device.

[0017] Thirdly, this application provides a park environmental protection monitoring system based on multi-data adaptive processing, comprising: an interaction module, a data acquisition module, a data analysis module, and an early warning module; wherein, Data acquisition module: acquires monitoring data of each regulatory sub-area through several data acquisition devices connected to it, including hazardous waste monitoring data, water quality monitoring data and air monitoring data; The data analysis module includes an analysis and sorting unit, a main processing unit, and a secondary processing unit; Analysis and sorting unit: This unit acquires the input information of each enterprise in the park to be regulated through an interactive module; divides the regulated area into several sub-regions based on the input information; generates several analysis priorities for each sub-region based on the input information of each enterprise in each sub-region; and constructs a region priority sorting table and an analysis priority sorting table based on the aforementioned analysis priorities. Main processing unit: According to the order of the regional priority sorting table, it obtains the monitoring data of the corresponding analysis priority in the regulatory sub-region; generates the main monitoring result based on the monitoring data; and outputs the main monitoring result to the early warning module; and performs supplementary analysis to generate a comprehensive monitoring result, and outputs the comprehensive result to the early warning module. Secondary processing unit: When the main monitoring status is out of control, it obtains the analysis priority ranking table of the regulatory sub-region corresponding to the regulatory data, and obtains the monitoring data corresponding to the analysis priority in sequence according to the order of the analysis priority table; and obtains the comprehensive monitoring result of the regulatory sub-region based on the analysis of each monitoring data. Early warning module: issues early warnings based on the analysis results of monitoring data; the analysis results include main monitoring results and comprehensive monitoring results; Interactive module: Performs alert operations and retrieves data entered by the enterprise.

[0018] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a park environmental monitoring device based on multi-data adaptive processing, cause the park environmental monitoring device based on multi-data adaptive processing to perform the method described in the first aspect and any possible implementation thereof.

[0019] Fifthly, this application provides a computer program product containing instructions that, when the computer program product is run on a park environmental protection monitoring device based on multi-data adaptive processing, causes the park environmental protection monitoring device based on multi-data adaptive processing to perform the method described in the first aspect and any possible implementation thereof.

[0020] This application provides a method and system for environmental protection supervision of industrial parks based on multi-data adaptive processing. It can acquire the input information of each enterprise in the park to be supervised; divide the supervision area into several sub-regions based on the input information; generate several analysis priorities for each sub-region based on the input information of each enterprise; acquire monitoring data within the sub-regions according to the analysis priorities, and obtain the monitoring data analysis results for each sub-region; issue early warnings based on the monitoring data analysis results; divide the monitoring data corresponding to each sub-region, and analyze the monitoring data of each sub-region in stages according to the analysis priorities, thereby timely analyzing the pollution situation of each sub-region and issuing timely early warnings, thus improving the efficiency of park management.

[0021] It should be understood that the descriptions of technical features, technical solutions, beneficial effects, or similar language in this application do not imply that all features and advantages can be achieved in any single embodiment. Rather, it is understood that the description of a feature or beneficial effect means that a specific technical feature, technical solution, or beneficial effect is included in at least one embodiment. Therefore, the descriptions of technical features, technical solutions, or beneficial effects in this specification do not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions, and beneficial effects described in this embodiment can be combined in any suitable manner. Those skilled in the art will understand that embodiments can be implemented without one or more specific technical features, technical solutions, or beneficial effects of a particular embodiment. In other embodiments, additional technical features and beneficial effects may be identified in specific embodiments that do not embody all embodiments. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram illustrating the steps of the park environmental protection supervision method based on multi-data adaptive processing in this application; Figure 2 This is a schematic diagram of the module connections of the park environmental protection supervision system based on multi-data adaptive processing in this application. Detailed Implementation

[0024] The technical solutions of this application will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0025] Please see Figure 1 The first aspect of this application provides a method for environmental protection supervision of industrial parks based on multi-data adaptive processing, including: The process involves: acquiring the input information of each enterprise in the park to be regulated; dividing the regulated area into several sub-regions based on the input information; generating several analysis priorities for each sub-region based on the input information of each enterprise in each sub-region; and defining the analysis priorities as the priorities of various pollution forms within each sub-region. Based on the analysis priority, monitoring data within the regulated sub-regions are acquired sequentially. This monitoring data includes hazardous waste monitoring data, water quality monitoring data, and air quality monitoring data. Hazardous waste detection data is collected by acquisition devices installed at designated waste dumping sites within the enterprise, including hazardous waste quality and images. Water quality detection data is collected by acquisition devices installed in sewer pipes or drainage pipes within the corresponding monitoring sub-region, including the content of various pollutants in the water. Air quality monitoring data is collected by acquisition devices installed within the corresponding regulated sub-region to monitor the content of relevant pollutants in the air. The monitoring data analysis results for each regulated sub-region are then obtained, and these results include: early warning systems are issued based on the monitoring data analysis results.

[0026] Based on the above technical solution, in the park environmental protection supervision method based on multi-data adaptive processing provided in this application, the following steps are taken: First, the input information of each enterprise in the park to be supervised is obtained. Then, the supervision area is divided into several supervision sub-areas based on the input information. Next, several analysis priorities for each supervision sub-area are generated based on the input information of each enterprise in each supervision sub-area. Then, monitoring data within the supervision sub-area is obtained sequentially according to the analysis priorities, and the monitoring data analysis results for the supervision sub-area are obtained based on the monitoring data analysis results. Finally, early warnings are issued based on the monitoring data analysis results. By dividing the monitoring data corresponding to each supervision sub-area and analyzing the monitoring data of each supervision sub-area in stages according to the analysis priorities, the pollution situation of each supervision sub-area can be analyzed in a timely manner, and early warnings can be issued promptly, thereby improving the efficiency of park management.

[0027] In one possible implementation, the regulatory area is divided into several sub-regions based on the information entered by the enterprise, including: Extract the waste form and waste percentage of each production waste from the information entered by each enterprise; the waste form includes solid waste, liquid waste and gaseous waste; the waste percentage is the proportion of the corresponding waste form in the total waste; Extract the enterprise coordinates from the information entered by each enterprise. Specifically, establish a Cartesian coordinate system within the park to be regulated, and use the coordinates of the center of the corresponding factory building as the enterprise coordinates. Integrate the enterprise coordinates and the proportion of waste in each form according to a set order to form the feature vector of the corresponding enterprise. Perform cluster analysis on the feature vectors of each enterprise to obtain several clusters. Divide the enterprises in the same cluster into the same regulatory sub-region. Sequentially obtain the regulatory sub-regions corresponding to each cluster.

[0028] This embodiment uses the above steps to group enterprises that are close to each other and produce similar waste into the same regulatory sub-area. Since the data types of monitoring data corresponding to the same type of production waste are the same, it is convenient to conduct unified analysis. For example, the monitoring data of solid waste includes the weight of solid waste, images of solid waste, etc.; the monitoring data of gaseous waste includes the types and concentrations of pollutants, etc.

[0029] In one possible implementation, several analysis priorities are generated based on the information entered by each enterprise in each regulatory sub-region, including: extracting historical emission data from the information entered by each enterprise in the regulatory sub-region, the historical emission data including data such as the emission amount of various waste materials; inputting each of the historical emission data into a risk analysis model to obtain an emission risk score for the pollutants emitted in the regulatory sub-region; the larger the value of the emission risk score, the more serious the situation of pollutant emission in the region or the higher the risk. Extract the waste type and waste percentage from the information entered by each enterprise in the regulated sub-region; calculate the average waste percentage of the same waste type for each enterprise in the regulated sub-region; and sequentially obtain the average waste percentage of each waste type. The product of the emission risk score of the regulated sub-region and the average value of the waste form is used as the analysis priority for the corresponding waste form in the regulated sub-region.

[0030] This embodiment, through the above steps, sets the analysis priority for each pollutant form within each regulated sub-region based on historical emissions data and the proportion of pollution forms within that sub-region. When the risk of pollutant emissions from a corresponding regulated sub-region is higher, the monitoring data for that sub-region should be analyzed first to ensure timely detection and treatment of pollutant emissions. When a regulated sub-region contains multiple pollutant forms, the primary pollutant form is analyzed first. For example, in water treatment companies, where liquid waste accounts for a high proportion and pollution is mainly generated in liquid form, water quality monitoring data should be analyzed first to ensure timely detection and treatment of pollutant emissions. Simultaneously, analyzing data of a single nature can improve analysis speed.

[0031] In one possible implementation, a training method for the risk analysis model includes: acquiring several historical emission data sets and corresponding emission risk scores; the historical emission data sets include data on the types and amounts of pollutants emitted by various enterprises in the corresponding region; the emission risk scores are scores given by experts based on pollutant-related emission data in the historical emission data sets regarding the emission risk of pollutants in the region, with higher emission risk scores for more types of pollutants, larger emission amounts, and longer emission periods. In this embodiment, the emission risk scores are set between 0 and 100, with higher scores indicating greater risk of pollutant emissions in the corresponding region; the historical emission data sets and their corresponding emission risk scores are then integrated into several training and testing data sets. The AI ​​model is trained using training data and tested using validation data. The final result is a risk analysis model with historical emission data as input and emission risk score as output. The AI ​​model includes a BP neural network model and an RBF neural network model.

[0032] In one possible implementation, monitoring data within the monitored sub-regions are acquired sequentially based on analysis priority, and monitoring data analysis results are obtained based on the analysis of the monitoring data, including: S1: Obtain several analysis priorities for each regulatory sub-region, and construct a region priority sorting table and an analysis priority sorting table based on each of the analysis priorities; S2: Obtain the regulatory sub-region corresponding to analysis priority 1 in the regional priority ranking table; obtain the monitoring data corresponding to the analysis priority in the regulatory sub-region; the monitoring data includes one of hazardous waste monitoring data, water quality monitoring data, and air monitoring data; when the waste form corresponding to the analysis priority is solid waste, the corresponding monitoring data is hazardous waste monitoring data; when the waste form corresponding to the analysis priority is liquid waste, the corresponding monitoring data is water quality monitoring data; when the waste form corresponding to the analysis priority is gaseous waste, the corresponding monitoring data is air monitoring data; the hazardous waste detection data is relevant data collected by the collection equipment set at the corresponding waste dumping point of the enterprise, including hazardous waste quality and hazardous waste images; the water quality detection data is relevant data collected by the collection equipment set in the sewer pipes or drainage pipes in the corresponding detection sub-region, including the content of various pollutants in the water; the air monitoring data is data collected by the collection equipment set in the corresponding regulatory sub-region for monitoring the content of relevant pollutants in the air; S3: Extract each monitoring item from the monitoring data, and determine in turn whether the monitoring value of each monitoring item is within the set warning range; the warning range is the warning threshold set by professionals for different pollutants; specifically, it can be set according to relevant environmental protection regulations; if yes, then record the main monitoring status of the monitoring item as qualified; otherwise, record the main monitoring status of the monitoring item as exceeding the standard. S4: Determine whether there is an out-of-standard status for the main monitoring status corresponding to each monitoring item; if yes, set the main monitoring result of the regulatory sub-area to out of standard and output the main monitoring result; proceed to S5; if no, set the main monitoring result of the regulatory sub-area to qualified and output the main monitoring result; proceed to S6; S5: Obtain the analysis priority ranking table of the regulatory sub-regions corresponding to the regulatory data, and obtain the monitoring data corresponding to the analysis priority in sequence according to the order of the analysis priority table; obtain the comprehensive monitoring result of the regulatory sub-region based on the analysis of each monitoring data; proceed to S8; S6: Obtain the analysis priority number M corresponding to the regulatory sub-region, and determine whether M is less than N, where N is the maximum number in the region priority ranking table; if yes, proceed to step S7; if no, proceed to supplementary analysis; the supplementary analysis is the data analysis of other monitoring data of each regulatory sub-region that has not generated comprehensive monitoring results. S7: Obtain the corresponding monitoring data in the regulatory sub-area corresponding to the analysis priority number M+1; Proceed to S3; S8: Output comprehensive monitoring results, which include main monitoring results and comprehensive monitoring results.

[0033] In one possible implementation, the construction of the regional priority ranking table includes: extracting several analysis priorities from each regulatory sub-region, sorting the largest analysis priority in each regulatory sub-region in descending order, and using the ranking as the corresponding analysis priority and the corresponding regulatory sub-region number, thereby generating the regional priority ranking table.

[0034] This embodiment uses the analysis priority with the highest value in each regulatory sub-region as the representative of that sub-region, and constructs a regional priority ranking table in descending order; it prioritizes the analysis of the main monitoring data of each region, and can quickly and accurately analyze each regulatory sub-region through the main monitoring data, ensuring the timeliness of regional environmental protection supervision.

[0035] One way to construct an analysis priority ranking table is to extract several analysis priorities from the regulatory sub-regions and sort each analysis priority in descending order to generate an analysis priority ranking table.

[0036] In one possible implementation, the supplementary analysis includes the following steps: obtaining each regulatory sub-region whose main monitoring result is qualified, and the corresponding number of the regulatory sub-region in the region priority ranking table; sorting each regulatory sub-region according to the order of its corresponding number to obtain a supplementary analysis ranking table; the supplementary analysis ranking table is a table that sorts the regulatory sub-regions that did not have monitoring data analyzed in the first analysis, and performs supplementary analysis on these monitoring data to ensure the comprehensiveness and accuracy of the analysis. Following the order of the supplementary analysis sorting table, the analysis priority sorting tables for each regulatory sub-region are obtained sequentially. Based on the sorting order of the analysis priorities, the monitoring data corresponding to each analysis priority is obtained. Based on the analysis of the monitoring data, the comprehensive monitoring results of the regulatory sub-region are obtained.

[0037] This embodiment sets up supplementary analysis to analyze relevant auxiliary monitoring data of each regulatory sub-region when the processor completes its main tasks, thereby ensuring the comprehensiveness of the data analysis of each regulatory sub-region within an analysis cycle.

[0038] In one possible implementation, the comprehensive monitoring results are obtained based on the analysis of various monitoring data, including: sequentially acquiring each monitoring item from each monitoring data, and obtaining several pollutant correlation maps; the pollutant correlation maps include the forms of several related pollutants, and the correlation between pollutants in different forms; for example, the main pollutants in a pharmaceutical factory are liquid pollutants, but because some pollutants have volatile properties, some pollutants will evaporate into the air. In this case, the same or related pollutants can be detected in different forms in both water quality monitoring data and air monitoring data; the same or related pollutants in different forms form a pollutant correlation map; it is understood that the pollutant correlation map is a series of pollutant maps constructed by professionals by analyzing the relationships between common pollutants in different forms. The monitoring items corresponding to each form of pollutant in the pollutant association map are obtained, and the monitoring values ​​of each monitoring item are summed to obtain the comprehensive monitoring value corresponding to the pollutant association map. It is worth noting that before summing the monitoring values ​​of each monitoring item, the monitoring values ​​of each monitoring item need to be converted to a unified unit. If the comprehensive monitoring value is within the set comprehensive warning range, then the comprehensive monitoring results of the several monitoring items corresponding to the pollutant association map are set to exceed the standard; otherwise, the comprehensive monitoring results of the several monitoring items corresponding to the pollutant association map are set to qualified. The comprehensive warning range is the minimum value of each warning range of each monitoring item corresponding to the pollutant association map converted to the same unit as the monitoring value.

[0039] In one possible implementation, the early warning based on monitoring data analysis results includes: extracting the main monitoring result and comprehensive monitoring result from the monitoring data analysis results corresponding to the regulated sub-region; issuing an early warning for the regulated sub-region when the main monitoring result exceeds the standard; issuing an early warning for the regulated sub-region when the comprehensive monitoring result exceeds the standard; the early warning includes a display warning, that is, highlighting the monitoring items corresponding to the main monitoring result and comprehensive monitoring result on the corresponding display device, such as changing the background color of the display to red or yellow.

[0040] Secondly, this application provides a park environmental protection monitoring device based on multi-data adaptive processing, comprising: a processor and a storage medium; the storage medium includes instructions, and the processor is used to execute the instructions to implement the method described in the first aspect and any possible implementation thereof. This park environmental protection monitoring device based on multi-data adaptive processing can be an electronic device or a chip within an electronic device.

[0041] Please see Figure 2Thirdly, this application provides a park environmental protection monitoring system based on multi-data adaptive processing, including: an interaction module, a data acquisition module, a data analysis module, and an early warning module; wherein, Data acquisition module: acquires monitoring data of each regulatory sub-area through several data acquisition devices connected to it, including hazardous waste monitoring data, water quality monitoring data and air monitoring data; The data analysis module includes an analysis and sorting unit, a main processing unit, and a secondary processing unit; Analysis and sorting unit: This unit acquires the input information of each enterprise in the park to be regulated through an interactive module; divides the regulated area into several sub-regions based on the input information; generates several analysis priorities for each sub-region based on the input information of each enterprise in each sub-region; and constructs a region priority sorting table and an analysis priority sorting table based on the aforementioned analysis priorities. Main processing unit: According to the order of the regional priority sorting table, it obtains the monitoring data of the corresponding analysis priority in the regulatory sub-region; generates the main monitoring result based on the monitoring data; and outputs the main monitoring result to the early warning module; and performs supplementary analysis to generate a comprehensive monitoring result, and outputs the comprehensive result to the early warning module. Secondary processing unit: When the main monitoring status is out of control, it obtains the analysis priority ranking table of the regulatory sub-region corresponding to the regulatory data, and obtains the monitoring data corresponding to the analysis priority in sequence according to the order of the analysis priority table; and obtains the comprehensive monitoring result of the regulatory sub-region based on the analysis of each monitoring data. Early warning module: issues early warnings based on the analysis results of monitoring data; the analysis results include main monitoring results and comprehensive monitoring results; Interactive module: Performs alert operations and retrieves data entered by the enterprise.

[0042] It is worth noting that the functions executed by the main processing unit and the secondary processing unit are located in different processes; the data processing of the two processes will not interfere with each other, which further improves the efficiency of data analysis.

[0043] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a park environmental monitoring device based on multi-data adaptive processing, cause the park environmental monitoring device based on multi-data adaptive processing to perform the method described in the first aspect and any possible implementation thereof.

[0044] Fifthly, this application provides a computer program product containing instructions that, when the computer program product is run on a park environmental protection monitoring device based on multi-data adaptive processing, causes the park environmental protection monitoring device based on multi-data adaptive processing to perform the method described in the first aspect and any possible implementation thereof.

[0045] Some of the data in the above formula are calculated by removing dimensions and taking their numerical values. The formula is the closest to the real situation obtained by software simulation of a large amount of collected data. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained through simulation of a large amount of data.

[0046] How this application works: By acquiring the input information of each enterprise in the park to be regulated; dividing the regulated area into several sub-regions based on the input information; generating several analysis priorities for each sub-region based on the input information of each enterprise in each sub-region; acquiring monitoring data within each sub-region according to the analysis priorities; analyzing the monitoring data to obtain the monitoring data analysis results for each sub-region; issuing early warnings based on the monitoring data analysis results; dividing the monitoring data corresponding to each sub-region and analyzing the monitoring data of each sub-region in stages according to the analysis priorities, the pollution situation of each sub-region can be analyzed in a timely manner, and early warnings can be issued in a timely manner, thereby improving the efficiency of park management.

[0047] The above embodiments are only used to illustrate the technical methods of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of this application without departing from the spirit and scope of the technical methods of this application.

Claims

1. A method for environmental protection supervision of industrial parks based on multi-data adaptive processing, characterized in that, include: Obtain the data entry information of each enterprise in the park under supervision; Based on the entered information, the regulatory area is divided into several regulatory sub-areas; Based on the information entered by each enterprise in each regulatory sub-region, several analysis priorities for the regulatory sub-regions are generated. Based on the analysis priority, the monitoring data of the regulatory sub-regions are obtained sequentially, and the monitoring data analysis results of the regulatory sub-regions are obtained based on the analysis of the monitoring data. Early warnings are issued based on the analysis results of monitoring data.

2. The park environmental protection supervision method based on multi-data adaptive processing according to claim 1, characterized in that, Based on the information entered by enterprises, the regulatory area is divided into several sub-regions, including: Extract the waste form and waste percentage of each production waste from the information entered by each enterprise; the waste form includes solid waste, liquid waste and gaseous waste; the waste percentage is the proportion of the corresponding waste form in the total waste; Extract the enterprise coordinates from the information entered by each enterprise; integrate the enterprise coordinates and the proportion of waste in each form of waste into the corresponding enterprise feature vector according to the set order; perform cluster analysis on the feature vectors of each enterprise to obtain several clusters; divide each enterprise in the same cluster into the same regulatory sub-region; and obtain the regulatory sub-regions corresponding to each cluster in turn.

3. The park environmental protection supervision method based on multi-data adaptive processing according to claim 1, characterized in that, Several analysis priorities are generated based on the information entered by each enterprise in each regulatory sub-region, including: Historical emission data are extracted from the information entered by each enterprise within the regulatory sub-region, and the historical emission data are input into the risk analysis model to obtain the emission risk score of the pollutants emitted in the regulatory sub-region. Extract the waste type and waste percentage from the information entered by each enterprise in the regulated sub-region; calculate the average waste percentage of the same waste type for each enterprise in the regulated sub-region; and sequentially obtain the average waste percentage of each waste type. The product of the emission risk score of the regulated sub-region and the average value of the waste form is used as the analysis priority for the corresponding waste form in the regulated sub-region.

4. The park environmental protection supervision method based on multi-data adaptive processing according to claim 3, characterized in that, One training method for the risk analysis model includes: Acquire several historical emission data and their corresponding emission risk scores; integrate the historical emission data and their corresponding emission risk scores into several training data and test data. The AI ​​model is trained using training data and tested using validation data. The final result is a risk analysis model with historical emission data as input and emission risk score as output. The AI ​​model includes a BP neural network model and an RBF neural network model.

5. The park environmental protection supervision method based on multi-data adaptive processing according to claim 1, characterized in that, Based on the analysis priority, monitoring data within the monitored sub-regions are acquired sequentially, and the monitoring data analysis results are obtained based on the analysis of the monitoring data, including: S1: Obtain several analysis priorities for each regulatory sub-region, and construct a region priority sorting table and an analysis priority sorting table based on each of the analysis priorities; S2: Obtain the regulatory sub-region corresponding to analysis priority number 1 in the regional priority sorting table; obtain the monitoring data of the corresponding analysis priority in the regulatory sub-region; S3: Extract each monitoring item from the monitoring data, and determine in turn whether the monitoring value of each monitoring item is within the set warning range; if yes, record the main monitoring status of the monitoring item as qualified; otherwise, record the main monitoring status of the monitoring item as exceeding the standard. S4: Determine whether there is an out-of-standard status for the main monitoring status corresponding to each monitoring item; if yes, set the main monitoring result of the regulatory sub-area to out of standard and output the main monitoring result; proceed to S5; if no, set the main monitoring result of the regulatory sub-area to qualified and output the main monitoring result; proceed to S6; S5: Obtain the analysis priority ranking table of the regulatory sub-regions corresponding to the regulatory data, and obtain the monitoring data corresponding to the analysis priority in sequence according to the order of the analysis priority table; obtain the comprehensive monitoring result of the regulatory sub-region based on the analysis of each monitoring data; proceed to S8; S6: Obtain the analysis priority number M corresponding to the regulatory sub-region, and determine whether M is less than N, where N is the maximum number in the region priority ranking table; if yes, proceed to step S7; if no, proceed to supplementary analysis; the supplementary analysis is the data analysis of other monitoring data of each regulatory sub-region that has not generated comprehensive monitoring results. S7: Obtain the corresponding monitoring data in the regulatory sub-area corresponding to the analysis priority number M+1; Proceed to S3; S8: Output comprehensive monitoring results, which include main monitoring results and comprehensive monitoring results.

6. The park environmental protection supervision method based on multi-data adaptive processing according to claim 5, characterized in that, The method for constructing the region priority sorting table includes: Extract several analysis priorities from each regulatory sub-region, sort the largest analysis priorities in each regulatory sub-region in descending order, and use the ranking as the corresponding analysis priority and the corresponding regulatory sub-region number, thereby generating a regional priority ranking table.

7. The park environmental protection supervision method based on multi-data adaptive processing according to claim 5, characterized in that, One method for constructing the analysis priority ranking table includes: Extract several analysis priorities from the regulatory sub-regions, and sort each analysis priority in descending order to generate an analysis priority ranking table.

8. The park environmental protection supervision method based on multi-data adaptive processing according to claim 5, characterized in that, The comprehensive monitoring results are obtained based on the analysis of various monitoring data, including: The monitoring items in each monitoring data are obtained sequentially to obtain several pollutant correlation maps; the pollutant correlation maps include the morphology of several related pollutants and the correlation between pollutants of each morphology. The monitoring items corresponding to each form of pollutant in the pollutant association map are obtained, and the monitoring values ​​of each monitoring item are summed to obtain the comprehensive monitoring value corresponding to the pollutant association map; specifically... If the comprehensive monitoring value is within the set comprehensive warning range, then the comprehensive monitoring results of the several monitoring items corresponding to the pollutant association map are set to exceed the standard; otherwise, the comprehensive monitoring results of the several monitoring items corresponding to the pollutant association map are set to qualified.

9. A park environmental protection supervision method based on multi-data adaptive processing according to claim 1, characterized in that, The early warning based on the analysis results of monitoring data includes: Extract the main monitoring results and comprehensive monitoring results from the monitoring data analysis results corresponding to the regulated sub-region; when the main monitoring result exceeds the standard, issue an early warning for the regulated sub-region; when the comprehensive monitoring result exceeds the standard, issue an early warning for the regulated sub-region.

10. A park environmental protection supervision system based on multi-data adaptive processing, based on the application of the park environmental protection supervision method based on multi-data adaptive processing as described in any one of claims 1 to 9, characterized in that, include: The system comprises a data acquisition module, a data analysis module, and an early warning module; among which, Data acquisition module: acquires monitoring data of each regulatory sub-area through several data acquisition devices connected to it, including hazardous waste monitoring data, water quality monitoring data and air monitoring data; The data analysis module includes an analysis and sorting unit, a main processing unit, and a secondary processing unit; Analysis and sorting unit: This unit acquires the input information of each enterprise in the park to be regulated through an interactive module; divides the regulated area into several sub-regions based on the input information; generates several analysis priorities for each sub-region based on the input information of each enterprise in each sub-region; and constructs a region priority sorting table and an analysis priority sorting table based on the aforementioned analysis priorities. Main processing unit: According to the order of the regional priority sorting table, it obtains the monitoring data of the corresponding analysis priority in the regulatory sub-region; generates the main monitoring result based on the monitoring data; and outputs the main monitoring result to the early warning module; and performs supplementary analysis to generate a comprehensive monitoring result, and outputs the comprehensive result to the early warning module. Secondary processing unit: When the main monitoring status is out of control, it obtains the analysis priority ranking table of the regulatory sub-region corresponding to the regulatory data, and obtains the monitoring data corresponding to the analysis priority in sequence according to the order of the analysis priority table; and obtains the comprehensive monitoring result of the regulatory sub-region based on the analysis of each monitoring data. Early warning module: issues early warnings based on the analysis results of monitoring data; the analysis results of monitoring data include main monitoring results and comprehensive monitoring results.

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