Urban environment digital management system based on big data
Through the digital urban environment management system based on big data, environmental data is collected and analyzed in real time, the shortcomings of manual inspection and regular monitoring in traditional urban environmental management methods are solved, real-time monitoring and early warning are achieved, and the scientificity and efficiency of environmental management are improved.
Patent Information
- Application Number
- CN202411743827.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-30
- Publication Date
- 2025-03-07
AI Technical Summary
Traditional urban environmental management methods rely on manual inspections and regular fixed-point monitoring, which has problems such as limited scope and difficulty in real-time monitoring and low frequency of data updates, resulting in regulatory vulnerabilities and difficulty in collaborative management.
The digital management system of urban environment based on big data is adopted to collect and analyze environmental data in real time through sensor arrays, network crawler modules, Internet of Things equipment and urban management modules, provide accurate environmental status information, and predict future environmental change trends through environmental prediction modules.
Real-time monitoring and data analysis are realized, pollution sources are discovered in a timely manner and early warning are made, which improves the scientificity and efficiency of environmental management and promotes communication and trust between the government and the public.
Smart Images
Figure CN119579380A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of environmental management, and in particular relates to a digital urban environmental management system based on big data. Background Art
[0002] With the acceleration of urbanization, urban environmental management faces many challenges. Traditional urban environmental management methods mainly rely on manual inspections, regular fixed-point monitoring, and decentralized data collection and processing by various departments. There are many disadvantages. The scope of manual inspections is limited and it is difficult to achieve real-time monitoring, which is prone to regulatory loopholes; the data from regular monitoring is updated at a low frequency and cannot reflect the dynamic changes of the environment in a timely manner; the data between departments are isolated and lack an effective integration and sharing mechanism, which makes collaborative management difficult and it is difficult to form a unified and effective environmental management strategy. It is also impossible to predict future trends in the environment and cannot solve the problem of declining environmental quality in a timely manner. Therefore, we propose a digital management system for urban environment based on big data. Summary of the invention
[0003] The purpose of the present invention is to provide a digital management system for urban environment based on big data. By collecting and analyzing a large amount of environmental data in real time, it provides accurate environmental status information for urban managers to help them formulate more effective environmental management strategies. The system can monitor key indicators such as air quality, water quality, soil quality, etc., timely discover pollution sources and issue early warnings, and the system can also predict future environmental change trends through the environmental prediction module, take preventive measures in advance, and avoid the occurrence of environmental pollution problems. It solves the problem that the existing urban environmental management method mainly relies on manual inspections, regular fixed-point monitoring, and decentralized data collection and processing by various departments, which has many drawbacks. The scope of manual inspections is limited and it is difficult to achieve real-time monitoring, which is prone to regulatory loopholes; the data updated on a regular basis is low in frequency and cannot reflect the dynamic changes of the environment in a timely manner.
[0004] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:
[0005] The present invention is a digital management system for urban environment based on big data, comprising a data collection unit, a data processing unit and a visual interaction unit;
[0006] The data collection unit includes a sensor array, a web crawler module, an Internet of Things device module and a city management module; the sensor array module includes an air sensor, a water quality sensor and a soil sensor;
[0007] The air sensor user monitors the air quality in the current environment and monitors and records the air quality data in the urban greening area; its functions include detecting PM2.5, PM10, sulfur dioxide, carbon monoxide indicators in the air, and monitoring real-time environmental information; the water quality sensor is responsible for monitoring and recording various physical, chemical and biological parameters in the water body, including pH value, dissolved oxygen, conductivity, turbidity, which are helpful to evaluate the health of the water body and detect pollution problems in time; the soil sensor is used to detect the moisture content in the soil by sensing the changes in humidity in the soil and converting them into readable electrical signals; the web crawler module is responsible for collecting comments, pictures, and video information about the urban environment posted by users on social media platforms, online forums, etc., and providing environmental feedback from the public's perspective; the Internet of Things device module is responsible for real-time acquisition of local microscopic data, such as the full load rate of the garbage bin reflects the surrounding garbage situation, and the local noise and light intensity data monitored by the smart street lamp are used as environmental assessments; the urban management module is responsible for collecting data from sanitation, environmental protection, and municipal departments, and uploading them.
[0008] As a preferred technical solution, the data processing unit includes a data acquisition module, a data preprocessing module, an environmental prediction module, a decision generation module, a data classification module and an environmental storage module; the sensor array, the web crawler module, the Internet of Things device module and the city management module are all wirelessly connected to the data acquisition module; the data acquisition module is electrically connected to the data preprocessing module and the data storage module respectively; the data preprocessing module is electrically connected to the environmental prediction module; the environmental prediction module is electrically connected to the decision generation module; the data storage module is electrically connected to the data classification module.
[0009] As a preferred technical solution, the data acquisition module is responsible for collecting data information uploaded by the sensor array, web crawler module, Internet of Things device module and city management module to ensure the real-time and accuracy of the data; the data preprocessing module is used to clean the collected data, remove noise and outliers, fill in missing data and reduce the complexity of subsequent processing; the environmental prediction module is responsible for in-depth analysis and processing based on urban environment-related data to achieve accurate prediction of future trends of various environmental indicators, and provide decision-making basis for managers, standardize data of different magnitudes to have the same mean and standard deviation, so as to facilitate model training, by using the Z-score standardization method, as follows:
[0010]
[0011] Where U is the original data, O is the mean of the data, is the standard deviation of the data, and X newIt is the new data after standardization; the preprocessed data is divided into training set, validation set and test set according to a certain ratio. Usually it can be divided according to the ratio of 70%:15%:15%. For example, in the data of the past year, the first 8.4 months of data are used as training set, the next 1.8 months of data are used as validation set, and the last 1.8 months of data are used as test set;
[0012] The decision generation module is responsible for generating scientific environmental management decision suggestions based on the analysis results of the environmental prediction module, and evaluating and screening different decision plans to assist managers in formulating the best environmental management strategy; the data storage module is used to store the data collected by the data acquisition module for subsequent queries; the data classification module is responsible for establishing multiple index dimensions according to different attributes of the data (such as time, region, environmental indicator type, etc.). In the time dimension, fine indexing can be performed according to years, months, days, hours and even minutes, so that environmental data within a specific time period can be quickly located; in the regional dimension, indexing can be performed according to the administrative divisions, geographic coordinates, etc. of the city to achieve accurate query of environmental data in different regions; in the environmental indicator type dimension, different environmental indicators (such as air quality, water quality, soil quality, etc.) can be indexed separately to quickly query relevant data of specific environmental indicators.
[0013] As a preferred technical solution, the visual interaction unit includes problem reporting, image uploading, user interaction interface, mobile terminal and graph construction module; the mobile terminal is provided with a user interaction interface; the data classification module is wirelessly connected to the user interaction interface; the graph construction module is wirelessly connected to the mobile terminal; the user interaction interface includes problem reporting and image uploading.
[0014] As a preferred technical solution, the problem reporting is used for citizens to report environmental problems via text messages, and the system performs corresponding processing after receiving the text messages; the image uploading is responsible for clearly observing the degree of environmental deterioration based on the images uploaded by the citizens; the user interaction interface is responsible for customizing different interaction interfaces according to the needs and usage habits of different user groups to focus on displaying macro-environmental status assessment reports and decision-making recommendations; the mobile terminal is used to facilitate users to view current environmental information; the map construction module is responsible for integrating and presenting various types of environment-related data, information and the relationships between them in the form of graphs.
[0015] The present invention has the following beneficial effects:
[0016] The present invention provides accurate environmental status information to city managers by collecting and analyzing a large amount of environmental data in real time, helping them to formulate more effective environmental management strategies. The system can monitor key indicators such as air quality, water quality, and soil quality, promptly discover pollution sources and issue early warnings. The system can also predict future environmental change trends through the environmental prediction module, take preventive measures in advance, and avoid the occurrence of environmental pollution problems. In this way, city managers can plan and manage the urban environment more scientifically and improve overall management efficiency.
[0017] The present invention provides a convenient user interaction interface, and citizens can report environmental problems and upload relevant images through mobile terminals to participate in urban environmental management. This helps to raise public awareness of environmental protection and create a good atmosphere for the participation of the whole society. Citizens can take photos and upload problems such as garbage accumulation and illegal sewage discharge, and relevant departments will handle and feedback the results in a timely manner. This interactive mechanism not only enhances citizens' sense of responsibility and participation, but also promotes communication and trust between the government and the public.
[0018] The present invention integrates and classifies various types of environmental data, establishes multiple index dimensions, and facilitates data sharing and collaboration among different departments and institutions. The environmental protection department can access the water quality monitoring data provided by the water department, while the urban management department can use air quality data to optimize garbage collection routes. This cross-departmental data sharing breaks the problem of information missing, improves resource utilization efficiency, and promotes the scientific and refined development of urban environmental management. It also provides comprehensive data support for policy makers, enabling them to make more informed decisions based on more comprehensive information.
[0019] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.
[0021] Figure 1 This is a flow chart of a digital management system for urban environment based on big data according to the present invention. DETAILED DESCRIPTION
[0022] 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.
[0023] See also Figure 1 As shown, the present invention is a digital management system for urban environment based on big data, including a data collection unit, a data processing unit and a visual interaction unit;
[0024] The data collection unit includes a sensor array, a web crawler module, an IoT device module, and an urban management module; the sensor array module includes an air sensor, a water quality sensor, and a soil sensor;
[0025] Air sensors monitor the air quality in the current environment and monitor and record air quality data in urban green areas. Their functions include detecting PM2.5, PM10, sulfur dioxide, and carbon monoxide indicators in the air and monitoring real-time environmental information. Water quality sensors are responsible for monitoring and recording a variety of physical, chemical, and biological parameters in water bodies, including pH, dissolved oxygen, conductivity, and turbidity. These data help assess the health of water bodies and detect pollution problems in a timely manner. Soil sensors are used to detect the moisture content in the soil by sensing changes in humidity in the soil and converting them into readable electrical signals. The web crawler module is responsible for collecting comments, pictures, and video information about the urban environment posted by users on social media platforms, online forums, etc., and providing feedback on environmental conditions from the public's perspective. The IoT device module is responsible for acquiring local microscopic data in real time, such as the full load rate of garbage bins reflecting the surrounding garbage situation, and the local noise and light intensity data monitored by smart street lights as environmental assessments. The urban management module is responsible for collecting data from sanitation, environmental protection, and municipal departments and uploading them.
[0026] The data processing unit includes a data acquisition module, a data preprocessing module, an environmental prediction module, a decision generation module, a data classification module and an environmental storage module; the sensor array, the web crawler module, the Internet of Things device module and the city management module are all wirelessly connected to the data acquisition module; the data acquisition module is electrically connected to the data preprocessing module and the data storage module respectively; the data preprocessing module is electrically connected to the environmental prediction module; the environmental prediction module is electrically connected to the decision generation module; the data storage module is electrically connected to the data classification module.
[0027] The data acquisition module is responsible for collecting data information uploaded by the sensor array, web crawler module, IoT device module and city management module to ensure the real-time and accuracy of the data; the data preprocessing module is used to clean the collected data, remove noise and outliers, fill in missing data and reduce the complexity of subsequent processing; the environmental prediction module is responsible for in-depth analysis and processing based on urban environment-related data to achieve accurate prediction of future trends of various environmental indicators and provide decision-making basis for managers. Data of different magnitudes are standardized to have the same mean and standard deviation for model training. The Z-score standardization method is used as follows:
[0028]
[0029] Where U is the original data, O is the mean of the data, is the standard deviation of the data, and X new It is the new data after standardization; the preprocessed data is divided into training set, validation set and test set according to a certain ratio. Usually it can be divided according to the ratio of 70%:15%:15%. For example, in the data of the past year, the first 8.4 months of data are used as training set, the next 1.8 months of data are used as validation set, and the last 1.8 months of data are used as test set;
[0030] The decision generation module is responsible for generating scientific environmental management decision recommendations based on the analysis results of the environmental prediction module, and evaluating and screening different decision plans to assist managers in formulating the best environmental management strategy; the data storage module is used to store the data collected by the data acquisition module for subsequent queries; the data classification module is responsible for establishing multiple index dimensions based on different data attributes such as time, region, and environmental indicator type. In the time dimension, it can be finely indexed according to years, months, days, hours, and even minutes, so that it can be quickly located when querying environmental data within a specific time period; in the regional dimension, it can be indexed according to the administrative divisions, geographic coordinates, etc. of the city to achieve accurate queries on environmental data in different regions; in the environmental indicator type dimension, different environmental indicators such as air quality, water quality, soil quality, etc. can be indexed separately to quickly query relevant data of specific environmental indicators.
[0031] The visual interaction unit includes problem reporting, image uploading, user interaction interface, mobile terminal and graph construction module; the mobile terminal is provided with a user interaction interface; the data classification module is wirelessly connected to the user interaction interface; the graph construction module is wirelessly connected to the mobile terminal; the user interaction interface includes problem reporting and image uploading.
[0032] Problem reporting is used for citizens to report environmental problems via text messages, and the system will process the text messages accordingly; image upload is responsible for clearly observing the degree of environmental deterioration based on the images uploaded by citizens; the user interaction interface is responsible for customizing different interaction interfaces based on the needs and usage habits of different user groups to focus on displaying macro-environmental status assessment reports and decision-making recommendations; the mobile terminal is used to facilitate users to view current environmental information; the map construction module is responsible for integrating and presenting various environmental-related data, information and the relationships between them in the form of graphs.
[0033] A specific application of this embodiment is: collecting environmental data such as air quality, water quality, soil moisture, and environmental comments, pictures, video information on social media, and data from sanitation, environmental protection, and municipal departments through a sensor array, a web crawler module, an Internet of Things device module, and a city management module. These data are uploaded to the data processing unit by the data acquisition module. After being cleaned, denoised, and missing data is filled in by the data preprocessing module, they are deeply analyzed and processed by the environmental prediction module to achieve accurate prediction of future trends of various environmental indicators and provide decision-making basis for managers. The decision generation module generates scientific environmental management decision suggestions based on the analysis results, and evaluates and screens different decision plans to assist managers in formulating the optimal environmental management strategy. The data storage module stores the collected data for subsequent queries, and the data classification module classifies the data according to the data. Multiple index dimensions are established based on different attributes such as time, region, and environmental indicator type, so that quick positioning can be achieved when querying environmental data within a specific time period; in the regional dimension, indexing can be performed according to the administrative divisions, geographic coordinates, etc. of the city to achieve accurate query of environmental data in different regions; in the environmental indicator type dimension, indexes can be established for different environmental indicators such as air quality, water quality, soil quality, etc., so as to quickly query relevant data of specific environmental indicators. The visual interaction unit provides users with environmental information display and interaction functions through problem reporting, image uploading, user interaction interface, mobile terminal and map construction modules. Users can view current environmental information, report environmental problems, upload related images, and obtain macro-environmental status assessment reports and decision-making recommendations through the user interaction interface. At the same time, the mobile terminal also provides a function for users to view current environmental information.
[0034] It is worth noting that in the above system embodiment, the various units included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.
[0035] In addition, those skilled in the art can understand that all or part of the steps in the above-mentioned embodiments can be completed by instructing related hardware through a program, and the corresponding program can be stored in a computer-readable storage medium.
[0036] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.
Claims
1. A digital management system for urban environment based on big data, comprising a data collection unit, a data processing unit and a visual interaction unit; characterized in that: The data collection unit includes a sensor array, a web crawler module, an Internet of Things device module and a city management module; the sensor array module includes an air sensor, a water quality sensor and a soil sensor; The air sensor user monitors the air quality in the current environment and monitors and records the air quality data in the urban green area; Its functions include detecting PM2.5, PM10, sulfur dioxide, and carbon monoxide indicators in the air, and monitoring real-time environmental information; the water quality sensor is responsible for monitoring and recording various physical, chemical, and biological parameters in the water body, including pH, dissolved oxygen, conductivity, and turbidity. These data are helpful in assessing the health of the water body and promptly detecting pollution problems; the soil sensor is used to detect the moisture content in the soil by sensing changes in humidity in the soil and converting them into readable electrical signals; the web crawler module is responsible for collecting comments, pictures, and video information about the urban environment posted by users on social media platforms, online forums, etc., and providing environmental feedback from the public's perspective; the Internet of Things device module is responsible for real-time acquisition of local microscopic data, such as the full load rate of garbage bins reflecting the surrounding garbage situation, and the local noise and light intensity data monitored by smart street lights as environmental assessments; the city management module is responsible for collecting data from sanitation, environmental protection, and municipal departments, and uploading them.
2. According to the big data-based urban environment digital management system of claim 1, it is characterized in that: The data processing unit includes a data acquisition module, a data preprocessing module, an environment prediction module, a decision generation module, a data classification module and an environment storage module; the sensor array, the web crawler module, the Internet of Things device module and the city management module are all wirelessly connected to the data acquisition module; the data acquisition module is electrically connected to the data preprocessing module and the data storage module respectively; the data preprocessing module is electrically connected to the environment prediction module; the environment prediction module is electrically connected to the decision generation module; the data storage module is electrically connected to the data classification module.
3. The urban environment digital management system based on big data according to claim 2 is characterized in that: The data acquisition module is responsible for collecting data information uploaded by the sensor array, web crawler module, Internet of Things device module and city management module to ensure the real-time and accuracy of the data; the data preprocessing module is used to clean the collected data, remove noise and outliers, fill in missing data and reduce the complexity of subsequent processing; the environmental prediction module is responsible for in-depth analysis and processing based on urban environment-related data to achieve accurate prediction of future trends of various environmental indicators, and provide decision-making basis for managers, standardize data of different magnitudes to have the same mean and standard deviation, so as to facilitate model training, by using the Z-score standardization method, as follows: Where U is the original data, O is the mean of the data, is the standard deviation of the data, and X new is the new data after standardization; Divide the preprocessed data into training set, validation set and test set according to a certain ratio. Usually, the ratio can be 70%:15%:15%. For example, in the past year's data, the first 8.4 months of data are used as training set, the next 1.8 months of data are used as validation set, and the last 1.8 months of data are used as test set. The decision generation module is responsible for generating scientific environmental management decision suggestions based on the analysis results of the environmental prediction module, and evaluating and screening different decision plans to assist managers in formulating the best environmental management strategy; The data storage module is used to store the data collected by the data collection module for subsequent query; the data classification module is responsible for establishing multiple index dimensions based on different attributes of the data such as time, region and environmental indicator type, so as to quickly query the relevant data of specific environmental indicators.
4. The urban environment digital management system based on big data according to claim 1 is characterized in that: The visualization interaction unit includes problem reporting, image uploading, user interaction interface, mobile terminal and graph construction module; the mobile terminal is provided with a user interaction interface; the data classification module is wirelessly connected to the user interaction interface; the graph construction module is wirelessly connected to the mobile terminal; the user interaction interface includes problem reporting and image uploading.
5. The urban environment digital management system based on big data according to claim 4 is characterized in that: The problem reporting function is used by citizens to report environmental problems via SMS, and the system will process the received SMS accordingly; the image uploading function is responsible for clearly observing the degree of environmental degradation based on the images uploaded by citizens; the user interaction interface is responsible for customizing different interaction interfaces based on the needs and usage habits of different user groups, focusing on displaying macro-environmental status assessment reports and decision-making recommendations; The mobile terminal is used to facilitate users to view current environmental information; the graph construction module is responsible for integrating and presenting various environmental-related data, information and the relationships between them in the form of a graph.