Atmospheric pollution control and pollutant on-line monitoring platform

Abstract

The invention discloses an atmospheric pollution control and pollutant online monitoring platform which comprises a data billboard module, an inspection ledger module, an environmental protection monitoring module, an environmental protection map module, an environmental protection file module, an environmental protection think tank module, a system management module and a system tool module. And the data billboard module comprises an environmental assessment classification form, a pollution discharge permission classification form, a construction progress form and the like. The method has the advantages that new environmental protection monitoring data codes are matched and designed, monitoring data are obtained, processed, stored, inquired and visually displayed, an environmental protection graph is constructed and applied, and objects and environmental protection archives are associated and presented to a management layer in a more visual mode. The sampling speed of the platform is improved by at least 5% compared with the prior art, the data analysis accuracy of the platform is improved by at least 7% compared with the prior art, the access response time of the platform is shorter than 3 seconds, and the platform can be applied to a WEB end and an applet end and has the advantages of rich atmosphere management forms, high accuracy and wider application range.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to an air pollution prevention and control and pollutant online monitoring platform. Background Art

[0002] The rapid development of industry and urbanization has exacerbated the decline in air quality. Environmental management has become particularly important, but the current form of external air management is single, with low accuracy and limited scope of application. The project conducts research and demonstration of the characteristics, influencing factors, online monitoring, and rapid detection technology of air pollutants, which is of great significance in promoting the construction of waste-free cities and beautiful cities. Summary of the invention

[0003] 1. Technical issues to be resolved In view of the shortcomings of the prior art, the present invention provides an air pollution prevention and control and pollutant online monitoring platform, which has the advantages of faster sampling speed, higher analysis accuracy, short platform access response time, rich air management forms, high accuracy, wider application range, etc., and solves the problems existing in the above-mentioned background technology.

[0004] (II) Technical solution To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an air pollution prevention and control and pollutant online monitoring platform, including a data dashboard module, an inspection ledger module, an environmental monitoring module, an environmental protection one-picture module, an environmental protection archive module, an environmental protection think tank module, a system management module and a system tool module; The data dashboard module includes an environmental assessment classification form, a pollutant discharge permit classification form, a construction progress form, an economic code form, an environmental assessment statistics form, a pollutant discharge permit statistics form, an emergency plan statistics form, and an acceptance statistics form; The inspection record module includes an overview unit, an inspection overview unit, an inspection headcount unit, and an inspection record unit; The environmental monitoring module includes an environmental quality monitoring unit, a pollution source monitoring unit, a data query unit and an equipment management unit. The environmental quality monitoring unit includes atmospheric data and surface water data on a map. The environmental quality monitoring unit also includes an air quality detection site form, an ambient air quality analysis form and an AQI hourly change curve form. The pollution source monitoring unit includes waste gas data and wastewater data on a map. The pollution source monitoring unit also includes a waste gas detection site form and an hourly change curve form for each monitoring indicator. The data query unit includes site items, date items and temperature, humidity, air pressure, wind speed, wind direction, SO2, O3, CO, PM2.5, and PM10 data. In the environmental monitoring module, it is necessary to acquire, process, store, query and visualize environmental monitoring data. The Python code framework is as follows: # Import necessary libraries import pandas as pd import flask from flask import Flask, request, jsonify import matplotlib.pyplot as plt # Initialize the Flask application app = Flask(__name__) # Dictionary simulation database # Using SQL Database or NoSQL Database data_store = { 'air_quality': pd.DataFrame(), # Store air quality data 'water_quality': pd.DataFrame(), #Store surface water data 'pollution_sources': pd.DataFrame(), #Store pollution source data 'devices': [] # Storage device information } #Simulate data loading function (load data from database or API) def load_mock_data(): #Sample data #Load data according to specific data format and source data_store['air_quality'] = pd.DataFrame({ 'timestamp': pd.date_range(start='2023-01-01', periods=100, freq='H'), 'SO2': [i * 0.1 for i in range(100)], 'O3': [i * 0.05 for i in range(100)], 'CO': [i * 0.02 for i in range(100)], 'PM2.5': [i * 0.5 for i in range(100)], 'PM10': [i * 1.0 for i in range(100)], # ... other fields }) # Similarly, load surface water data, pollution source data, and equipment information # ... # Data statistics function def calculate_statistics(dataframe, columns): stats = {} for column in columns: if column in dataframe.columns: stats[column] = { 'mean': dataframe[column].mean(), 'max': dataframe[column].max(), 'min': dataframe[column].min(), 'std': dataframe[column].std() } return stats # Data Query API @app.route(' / query', methods=['GET']) def query_data(): params = request.args station = params.get('station') start_date = params.get('start_date') end_date = params.get('end_date') metrics = params.getlist('metrics', default=['SO2', 'O3', 'CO', 'PM2.5', 'PM10']) # Filter data based on parameters filtered_df = data_store['air_quality'].copy() if station: #Further filter data based on site name pass if start_date and end_date: filtered_df = filtered_df[(filtered_df['timestamp']>= start_date)&(filtered_df['timestamp']<= end_date)] # Select the desired metrics result = filtered_df[metrics].to_dict(orient='records') # Data processing and statistical logic # ... return jsonify(result) # Data Statistics API @app.route(' / statistics', methods=['GET']) def get_statistics(): columns = request.args.getlist('columns', default=['SO2', 'O3', 'CO', 'PM2.5', 'PM10']) stats = calculate_statistics(data_store['air_quality'], columns) return jsonify(stats) # Data Visualization API @app.route(' / visualize', methods=['GET']) def visualize_data(): columns = request.args.getlist('columns', default=['SO2', 'PM2.5']) filtered_df = data_store['air_quality'][columns + ['timestamp']] # Create a chart plt.figure(figsize=(10, 5)) for column in columns: plt.plot(filtered_df['timestamp'], filtered_df[column], label=column) plt.xlabel('Timestamp') plt.ylabel('Concentration') plt.title('Air Quality Metrics Over Time') plt.legend() # Save the chart as a PNG file plt.savefig('visualization.png') plt.close() # Demonstration response # Returns the URL or Base64-encoded string of the chart return 'Visualization saved as visualization.png' # Initialize data load_mock_data() # Start the Flask server if __name__ == '__main__': app.run(debug=True); The environmental protection one map module includes a map foundation, and the environmental protection one map module also includes importing vectors, points, texts, lines, polygons, circles, modifying, moving, rotating, scaling, deleting, measuring distance, and measuring area functions. The environmental protection one map module also includes environmental protection layers, self-built layers, and preset layers. The environmental protection layers include project distribution on the map, inspection tracks, illegal wind directions, illegal records, pollution source discharge ports, risk source distribution, and environmental monitoring point data; The environmental protection archive module includes a project management unit and an enterprise management unit; The environmental think tank module includes an enterprise analysis unit, a market analysis unit, a standard policy unit, a classification catalog unit, a hazardous waste catalog unit, an economic code unit, a credit platform unit and a data site unit; The system management module includes a user management unit, a role management unit, a menu management unit, a department management unit, a position management unit, a dictionary management unit, a parameter setting unit, a log management unit and a file management unit, wherein the log unit includes an operation log and a login log; The system tool module includes a form construction unit, a code generation unit and a system interface unit.

[0005] Preferably, in the environmental monitoring module, the equipment management unit includes site name, equipment name, equipment type, equipment status, affiliated unit, and longitude and latitude data.

[0006] Preferably, when the environmental monitoring module displays surface water data, its forms are a surface water detection site form, a surface water quality form and an ambient air quality analysis form.

[0007] Adopting the above technical solution: When the environmental monitoring module of this platform is implemented, Environmental Quality Monitoring Unit Technical architecture: Advanced sensor technology, Internet technology, wireless communication technology and cloud computing technology are used to build an environmental quality monitoring network. Sensors are responsible for collecting atmospheric data and surface water data in real time and transmitting them to the data center via wireless networks.

[0008] Monitoring site deployment: Rationally plan monitoring sites on the map to ensure comprehensive coverage and uniform distribution. Each monitoring site is equipped with necessary sensors and equipment, such as particulate matter sensors, meteorological sensors, etc., to monitor air and water quality in real time.

[0009] Data display and analysis: The monitoring data and analysis results are displayed intuitively through the air quality detection site form, ambient air quality analysis form and AQI hourly change curve form. Using GIS technology, the monitoring data is visualized on the map, which makes it easier for users to intuitively understand the environmental quality status.

[0010] Pollution source monitoring unit Waste gas and wastewater monitoring: Set up waste gas monitoring stations and wastewater monitoring stations near pollution sources to monitor waste gas and wastewater emissions in real time. The data collected by the sensors include the concentration of pollutants such as SO2, O3, CO, NOx in the waste gas, and the concentration of harmful substances in the wastewater.

[0011] Data recording and analysis: Record and analyze the emission data of pollution sources through the exhaust gas detection site form and the hourly change curve form of each monitoring indicator. Use big data analysis technology to identify emission patterns, abnormal conditions and potential risks.

[0012] Data query unit Query function: Provides query functions for site items, date items, and data such as temperature, humidity, air pressure, wind speed, wind direction, SO2, O3, CO, PM2.5, PM10, etc. Users can select query conditions as needed to obtain corresponding monitoring data.

[0013] Data export: Supports data export function, users can export query results to Excel or CSV formats for subsequent analysis and processing.

[0014] Device Management Unit Equipment management: unified management and maintenance of equipment at monitoring sites, including recording and updating of site name, equipment name, equipment type, equipment status, affiliated unit, longitude and latitude, etc.

[0015] Remote monitoring: Through remote monitoring technology, you can understand the operating status and monitoring data of the equipment in real time. Once an abnormal situation is found, it can be handled and repaired in time.

[0016] Environmental monitoring data collection and preprocessing Data collection: Use sensors to collect monitoring data in real time and transmit it to the data center via wireless networks.

[0017] Data preprocessing: Perform preprocessing operations such as cleaning, verification, and format conversion on the collected data to ensure the accuracy and consistency of the data.

[0018] Data Analysis and Statistics Real-time data analysis: Use real-time data analysis algorithms to quickly analyze and process the collected data, including calculating AQI values ​​and identifying abnormal data.

[0019] Historical data statistics: Statistics and analysis of historical monitoring data, including calculation of statistical indicators such as average value, maximum value, minimum value, standard deviation, and drawing of change curves.

[0020] Data Visualization Map display: Using GIS technology, the monitoring data can be visualized on the map, including the distribution map of air quality monitoring stations, AQI change curve, etc.

[0021] Report generation: Generate various reports and charts according to user needs, including daily, weekly, monthly and other statistical reports, as well as bar charts, line charts and other chart displays.

[0022] Abnormal alarm and early warning Abnormal alarm: Set a threshold value. When the monitoring data exceeds the threshold value, an abnormal alarm is triggered. Relevant personnel are notified through SMS, email, etc. for processing.

[0023] Early warning mechanism: Based on historical data and real-time data, an early warning model is established. When it is predicted that pollution may exceed the standard, early warning information is issued in advance so that corresponding prevention and control measures can be taken.

[0024] Using the above technical solution: The present invention builds an online monitoring platform for air pollution prevention and control and pollutants, which reflects the real-time changes in air quality while realizing online monitoring data exchange. It realizes rapid sampling of various air pollutants and rapid qualitative and quantitative analysis of characteristic pollutants from pollution sources. A new environmental monitoring data code is designed to acquire, process, store, query and visualize the monitoring data. The construction and application of an environmental protection map associates objects with environmental protection archives and presents them to the management in a more intuitive form. The platform sampling speed is at least 5% higher than before, the platform data analysis accuracy is at least 7% higher than before, and the platform access response time is less than 3 seconds. This platform can be applied on the WEB side and the mini-program side, and has the advantages of rich air management forms, high accuracy, and a wider range of applications.

[0025] (III) Beneficial effects Compared with the prior art, the present invention provides an air pollution prevention and control and pollutant online monitoring platform, which has the following beneficial effects: The air pollution prevention and control and pollutant online monitoring platform, the present invention, builds an air pollution prevention and control and pollutant online monitoring platform, and its focus is on the application of environmental monitoring modules, which reflects the real-time changes in air quality while realizing online monitoring data exchange. Rapid sampling of various air pollutants is realized, and rapid qualitative and quantitative analysis of characteristic pollutants of pollution sources is carried out. With the design of new environmental monitoring data codes, the monitoring data is acquired, processed, stored, queried and visualized. The construction and application of an environmental protection map associates objects with environmental protection archives and presents them to the management in a more intuitive form. The platform sampling speed is at least 5% higher than before, the platform data analysis accuracy is at least 7% higher than before, and the platform access response time is less than 3 seconds. This platform can be applied on the WEB side and the mini-program side, and has the advantages of rich air management forms, high accuracy, and a wider range of applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is an overall schematic diagram of an air pollution prevention and control and pollutant online monitoring platform proposed by the present invention; Figure 2This is a structural schematic diagram of a data dashboard module in an air pollution prevention and control and pollutant online monitoring platform proposed by the present invention; Figure 3 This is a structural diagram of an inspection ledger module in an air pollution prevention and control and pollutant online monitoring platform proposed by the present invention; Figure 4 This is a structural schematic diagram of an environmental quality monitoring unit in an air pollution prevention and control and pollutant online monitoring platform proposed by the present invention; Figure 5 This is a schematic diagram of the structure of a pollution source monitoring unit in an air pollution prevention and control and pollutant online monitoring platform proposed by the present invention; Figure 6 This is a structural schematic diagram of a data query unit in an air pollution prevention and control and pollutant online monitoring platform proposed by the present invention; Figure 7 This is a structural schematic diagram of an equipment management unit in an air pollution prevention and control and pollutant online monitoring platform proposed by the present invention; Figure 8 This is a structural schematic diagram of an environmental protection one-picture module in an air pollution prevention and control and pollutant online monitoring platform proposed by the present invention; Fig. 9 This is a structural schematic diagram of an environmental think tank module in an air pollution prevention and control and pollutant online monitoring platform proposed by the present invention; Fig.10 This is a structural schematic diagram of a system management module in an air pollution prevention and control and pollutant online monitoring platform proposed by the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] See also Figure 1-10 , an air pollution prevention and control and pollutant online monitoring platform, including a data dashboard module, an inspection ledger module, an environmental monitoring module, an environmental picture module, an environmental archive module, an environmental think tank module, a system management module and a system tool module; The data dashboard module includes environmental assessment classification form, pollution discharge permit classification form, construction progress form, economic code form, environmental assessment statistics form, pollution discharge permit statistics form, emergency plan statistics form, and acceptance statistics form; The inspection record module includes overview unit, inspection overview unit, inspection personnel unit, and inspection record unit; The environmental monitoring module includes an environmental quality monitoring unit, a pollution source monitoring unit, a data query unit and an equipment management unit. The environmental quality monitoring unit includes atmospheric data and surface water data on the map. The environmental quality monitoring unit also includes an air quality detection site form, an ambient air quality analysis form and an AQI hourly change curve form. The pollution source monitoring unit includes waste gas data and wastewater data on the map. The pollution source monitoring unit also includes a waste gas detection site form and an hourly change curve form for each monitoring indicator. The data query unit includes site items, date items and temperature, humidity, air pressure, wind speed, wind direction, SO2, O3, CO, PM2.5, and PM10 data. In the environmental monitoring module, it is necessary to acquire, process, store, query and visualize environmental monitoring data. The Python code framework is as follows: # Import necessary libraries import pandas as pd import flask from flask import Flask, request, jsonify import matplotlib.pyplot as plt # Initialize the Flask application app = Flask(__name__) # Dictionary simulation database # Using SQL Database or NoSQL Database data_store = { 'air_quality': pd.DataFrame(), # Store air quality data 'water_quality': pd.DataFrame(), #Store surface water data 'pollution_sources': pd.DataFrame(), #Store pollution source data 'devices': [] # Storage device information } #Simulate data loading function (load data from database or API) def load_mock_data(): #Sample data #Load data according to specific data format and source data_store['air_quality'] = pd.DataFrame({ 'timestamp': pd.date_range(start='2023-01-01', periods=100, freq='H'), 'SO2': [i * 0.1 for i in range(100)], 'O3': [i * 0.05 for i in range(100)], 'CO': [i * 0.02 for i in range(100)], 'PM2.5': [i * 0.5 for i in range(100)], 'PM10': [i * 1.0 for i in range(100)], # ... other fields }) # Similarly, load surface water data, pollution source data, and equipment information # ... # Data statistics function def calculate_statistics(dataframe, columns): stats = {} for column in columns: if column in dataframe.columns: stats[column] = { 'mean': dataframe[column].mean(), 'max': dataframe[column].max(), 'min': dataframe[column].min(), 'std': dataframe[column].std() } return stats # Data Query API @app.route(' / query', methods=['GET']) def query_data(): params = request.args station = params.get('station') start_date = params.get('start_date') end_date = params.get('end_date') metrics = params.getlist('metrics', default=['SO2', 'O3', 'CO', 'PM2.5', 'PM10']) # Filter data based on parameters filtered_df = data_store['air_quality'].copy() if station: #Further filter data based on site name pass if start_date and end_date: filtered_df = filtered_df[(filtered_df['timestamp']>= start_date)&(filtered_df['timestamp']<= end_date)] # Select the desired metrics result = filtered_df[metrics].to_dict(orient='records') # Data processing and statistical logic # ... return jsonify(result) # Data Statistics API @app.route(' / statistics', methods=['GET']) def get_statistics(): columns = request.args.getlist('columns', default=['SO2', 'O3', 'CO', 'PM2.5', 'PM10']) stats = calculate_statistics(data_store['air_quality'], columns) return jsonify(stats) # Data Visualization API @app.route(' / visualize', methods=['GET']) def visualize_data(): columns = request.args.getlist('columns', default=['SO2', 'PM2.5']) filtered_df = data_store['air_quality'][columns + ['timestamp']] # Create a chart plt.figure(figsize=(10, 5)) for column in columns: plt.plot(filtered_df['timestamp'], filtered_df[column], label=column) plt.xlabel('Timestamp') plt.ylabel('Concentration') plt.title('Air Quality Metrics Over Time') plt.legend() # Save the chart as a PNG file plt.savefig('visualization.png') plt.close() # Demonstration response # Returns the URL or Base64-encoded string of the chart return 'Visualization saved as visualization.png' # Initialize data load_mock_data() # Start the Flask server if __name__ == '__main__': app.run(debug=True); The environmental protection one map module includes map foundation, and also includes importing vectors, points, texts, lines, polygons, circles, modifying, moving, rotating, scaling, deleting, measuring distance, and measuring area. The environmental protection one map module also includes environmental protection layers, self-built layers, and preset layers. The environmental protection layers include project distribution on the map, inspection tracks, illegal wind directions, illegal records, pollution source discharge ports, risk source distribution, and environmental monitoring point data; The environmental profile module includes project management unit and enterprise management unit; The environmental think tank module includes enterprise analysis unit, market analysis unit, standard policy unit, classification list unit, hazardous waste list unit, economic code unit, credit platform unit and data site unit; The system management module includes a user management unit, a role management unit, a menu management unit, a department management unit, a position management unit, a dictionary management unit, a parameter setting unit, a log management unit and a file management unit, wherein the log unit includes an operation log and a login log; The system tool module includes a form building unit, a code generation unit and a system interface unit.

[0029] In the environmental monitoring module, the equipment management unit includes site name, equipment name, equipment type, equipment status, affiliated unit, and longitude and latitude data. When the environmental monitoring module displays surface water data, its forms are surface water detection site form, surface water quality form, and ambient air quality analysis form.

[0030] Example 1: One system platform for "air pollution prevention and control and online monitoring and rapid detection of pollutants" in key areas and key fields (i.e., integrated air information management system), which is divided into mini-program side and WEB side. Three application modules: factors affecting air pollution in key areas and key fields and their correlation, online monitoring data collection for carbon neutral air pollution, and rapid detection of air pollutants.

[0031] Example 2: When the environmental monitoring module of this platform is implemented, Environmental Quality Monitoring Unit Technical architecture: Advanced sensor technology, Internet technology, wireless communication technology and cloud computing technology are used to build an environmental quality monitoring network. Sensors are responsible for collecting atmospheric data and surface water data in real time and transmitting them to the data center via wireless networks.

[0032] Monitoring site deployment: Rationally plan monitoring sites on the map to ensure comprehensive coverage and uniform distribution. Each monitoring site is equipped with necessary sensors and equipment, such as particulate matter sensors, meteorological sensors, etc., to monitor air and water quality in real time.

[0033] Data display and analysis: The monitoring data and analysis results are displayed intuitively through the air quality detection site form, ambient air quality analysis form and AQI hourly change curve form. Using GIS technology, the monitoring data is visualized on the map, which makes it easier for users to intuitively understand the environmental quality status.

[0034] Pollution source monitoring unit Waste gas and wastewater monitoring: Set up waste gas monitoring stations and wastewater monitoring stations near pollution sources to monitor waste gas and wastewater emissions in real time. The data collected by the sensors include the concentration of pollutants such as SO2, O3, CO, NOx in the waste gas, and the concentration of harmful substances in the wastewater.

[0035] Data recording and analysis: Record and analyze the emission data of pollution sources through the exhaust gas detection site form and the hourly change curve form of each monitoring indicator. Use big data analysis technology to identify emission patterns, abnormal conditions and potential risks.

[0036] Data query unit Query function: Provides query functions for site items, date items, and data such as temperature, humidity, air pressure, wind speed, wind direction, SO2, O3, CO, PM2.5, PM10, etc. Users can select query conditions as needed to obtain corresponding monitoring data.

[0037] Data export: Supports data export function, users can export query results to Excel or CSV formats for subsequent analysis and processing.

[0038] Device Management Unit Equipment management: unified management and maintenance of equipment at monitoring sites, including recording and updating of site name, equipment name, equipment type, equipment status, affiliated unit, longitude and latitude, etc.

[0039] Remote monitoring: Through remote monitoring technology, you can understand the operating status and monitoring data of the equipment in real time. Once an abnormal situation is found, it can be handled and repaired in time.

[0040] Environmental monitoring data collection and preprocessing Data collection: Use sensors to collect monitoring data in real time and transmit it to the data center via wireless networks.

[0041] Data preprocessing: Perform preprocessing operations such as cleaning, verification, and format conversion on the collected data to ensure the accuracy and consistency of the data.

[0042] Data Analysis and Statistics Real-time data analysis: Use real-time data analysis algorithms to quickly analyze and process the collected data, including calculating AQI values ​​and identifying abnormal data.

[0043] Historical data statistics: Statistics and analysis of historical monitoring data, including calculation of statistical indicators such as average value, maximum value, minimum value, standard deviation, and drawing of change curves.

[0044] Data Visualization Map display: Using GIS technology, the monitoring data can be visualized on the map, including the distribution map of air quality monitoring stations, AQI change curve, etc.

[0045] Report generation: Generate various reports and charts according to user needs, including daily, weekly, monthly and other statistical reports, as well as bar charts, line charts and other chart displays.

[0046] Abnormal alarm and early warning Abnormal alarm: Set a threshold value. When the monitoring data exceeds the threshold value, an abnormal alarm is triggered. Relevant personnel are notified through SMS, email, etc. for processing.

[0047] Early warning mechanism: Based on historical data and real-time data, an early warning model is established. When it is predicted that pollution may exceed the standard, early warning information is issued in advance so that corresponding prevention and control measures can be taken.

[0048] In summary, the air pollution prevention and control and pollutant online monitoring platform, the present invention, builds an air pollution prevention and control and pollutant online monitoring platform, and its focus is on the application of environmental monitoring modules, which reflects the real-time changes in air quality while realizing online monitoring data exchange. Rapid sampling of various air pollutants is achieved, and rapid qualitative and quantitative analysis of characteristic pollutants from pollution sources is performed. A new environmental monitoring data code is designed to acquire, process, store, query and visualize the monitoring data. The construction and application of an environmental protection map associates objects with environmental protection archives and presents them to the management in a more intuitive form. The platform sampling speed is at least 5% higher than before, the platform data analysis accuracy is at least 7% higher than before, and the platform access response time is less than 3 seconds. This platform can be applied on the WEB side and the mini-program side, and has the advantages of rich forms of atmospheric management, high accuracy, and a wider range of applications.

[0049] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise one" do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0050] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An air pollution prevention and control and pollutant online monitoring platform, characterized in that: It includes data dashboard module, inspection ledger module, environmental monitoring module, environmental picture module, environmental archive module, environmental think tank module, system management module and system tool module; The data dashboard module includes an environmental assessment classification form, a pollutant discharge permit classification form, a construction progress form, an economic code form, an environmental assessment statistics form, a pollutant discharge permit statistics form, an emergency plan statistics form, and an acceptance statistics form; The inspection record module includes an overview unit, an inspection overview unit, an inspection headcount unit, and an inspection record unit; The environmental monitoring module includes an environmental quality monitoring unit, a pollution source monitoring unit, a data query unit and an equipment management unit. The environmental quality monitoring unit includes atmospheric data and surface water data on a map. The environmental quality monitoring unit also includes an air quality detection site form, an ambient air quality analysis form and an AQI hourly change curve form. The pollution source monitoring unit includes waste gas data and wastewater data on a map. The pollution source monitoring unit also includes a waste gas detection site form and an hourly change curve form for each monitoring indicator. The data query unit includes site items, date items and temperature, humidity, air pressure, wind speed, wind direction, SO2, O3, CO, PM2.5, and PM10 data. In the environmental monitoring module, it is necessary to acquire, process, store, query and visualize environmental monitoring data. The Python code framework is as follows: # Import necessary libraries import pandas as pd import flask from flask import Flask, request, jsonify import matplotlib.pyplot as plt # Initialize the Flask application app = Flask(__name__) # Dictionary simulation database # Using SQL Database or NoSQL Database data_store = { 'air_quality': pd.DataFrame(), # Store air quality data 'water_quality': pd.DataFrame(), #Store surface water data 'pollution_sources': pd.DataFrame(), #Store pollution source data 'devices': [] # Storage device information } #Simulate data loading function (load data from database or API) def load_mock_data(): #Sample data #Load data according to specific data format and source data_store['air_quality'] = pd.DataFrame({ 'timestamp': pd.date_range(start='2023-01-01', periods=100, freq='H'), 'SO2': [i * 0.1 for i in range(100)], 'O3': [i * 0.05 for i in range(100)], 'CO': [i * 0.02 for i in range(100)], 'PM2.5': [i * 0.5 for i in range(100)], 'PM10': [i * 1.0 for i in range(100)], # ... other fields }) # Similarly, load surface water data, pollution source data, and equipment information # ... # Data statistics function def calculate_statistics(dataframe, columns): stats = {} for column in columns: if column in dataframe.columns: stats[column] = { 'mean': dataframe[column].mean(), 'max': dataframe[column].max(), 'min': dataframe[column].min(), 'std': dataframe[column].std() } return stats # Data Query API @app.route(' / query', methods=['GET']) def query_data(): params = request.args station = params.get('station') start_date = params.get('start_date') end_date = params.get('end_date') metrics = params.getlist('metrics', default=['SO2', 'O3', 'CO', 'PM2.5','PM10']) # Filter data based on parameters filtered_df = data_store['air_quality'].copy() if station: #Further filter data based on site name pass if start_date and end_date: filtered_df = filtered_df[(filtered_df['timestamp'] >= start_date) &(filtered_df['timestamp'] <= end_date)] # Select the desired metrics result = filtered_df[metrics].to_dict(orient='records') # Data processing and statistical logic # ... return jsonify(result) # Data Statistics API @app.route(' / statistics', methods=['GET']) def get_statistics(): columns = request.args.getlist('columns', default=['SO2', 'O3', 'CO', 'PM2.5', 'PM10']) stats = calculate_statistics(data_store['air_quality'], columns) return jsonify(stats) # Data Visualization API @app.route(' / visualize', methods=['GET']) def visualize_data(): columns = request.args.getlist('columns', default=['SO2', 'PM2.5']) filtered_df = data_store['air_quality'][columns + ['timestamp']] # Create a chart plt.figure(figsize=(10, 5)) for column in columns: plt.plot(filtered_df['timestamp'], filtered_df[column], label=column) plt.xlabel('Timestamp') plt.ylabel('Concentration') plt.title('Air Quality Metrics Over Time') plt.legend() # Save the chart as a PNG file plt.savefig('visualization.png') plt.close() # Demonstration response # Returns the URL or Base64-encoded string of the chart return 'Visualization saved as visualization.png' # Initialize data load_mock_data() # Start the Flask server if __name__ == '__main__': app.run(debug=True); The environmental protection one map module includes a map foundation, and the environmental protection one map module also includes importing vectors, points, texts, lines, polygons, circles, modifying, moving, rotating, scaling, deleting, measuring distance, and measuring area functions. The environmental protection one map module also includes environmental protection layers, self-built layers, and preset layers. The environmental protection layers include project distribution on the map, inspection tracks, illegal wind directions, illegal records, pollution source discharge ports, risk source distribution, and environmental monitoring point data; The environmental protection archive module includes a project management unit and an enterprise management unit; The environmental think tank module includes an enterprise analysis unit, a market analysis unit, a standard policy unit, a classification catalog unit, a hazardous waste catalog unit, an economic code unit, a credit platform unit and a data site unit; The system management module includes a user management unit, a role management unit, a menu management unit, a department management unit, a position management unit, a dictionary management unit, a parameter setting unit, a log management unit and a file management unit, wherein the log unit includes an operation log and a login log; The system tool module includes a form construction unit, a code generation unit and a system interface unit.

2. The air pollution prevention and control and pollutant online monitoring platform according to claim 1 is characterized by: In the environmental monitoring module, the equipment management unit includes site name, equipment name, equipment type, equipment status, affiliated unit, and longitude and latitude data.

3. The air pollution prevention and control and pollutant online monitoring platform according to claim 1 is characterized by: When the environmental monitoring module displays surface water data, its forms include a surface water detection site form, a surface water quality form, and an ambient air quality analysis form.

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