Soil environment data acquisition and analysis monitoring system for preventing and controlling soil pollution

Abstract

The invention discloses a soil environment data acquisition and analysis monitoring system for preventing and controlling soil pollution, and belongs to the technical field of environment monitoring. Comprising a soil environment data acquisition module, a data preprocessing module, a feature extraction and analysis module, a model training and prediction module, a visualization and decision support module, a data sharing and collaborative management module, a soil environment archive management module and a soil environment database. According to the invention, comprehensive acquisition of soil environment data is realized, and multiple links of multi-layer soil, underground water, atmospheric environment and biological monitoring are covered; through data cleaning, correction and fusion, the quality and consistency of the data are ensured; comprehensive analysis of the soil environment is realized through feature extraction and model training; through the data sharing and collaborative management module, the collaboration and effectiveness of soil pollution prevention and control work are improved; through the soil environment file management module, various data in the soil environment pollution prevention and control process are managed in a unified mode, and a user can search and manage the data conveniently.

Description

Technical Field

[0001] The invention belongs to the technical field of environmental monitoring, and in particular relates to a soil environmental data collection and analysis monitoring system for preventing and controlling soil pollution. Background Art

[0002] Soil is the material basis for sustainable social and economic development, and is related to the health of the people and the safety of the ecological environment. However, with the rapid development of industrialization and urbanization, soil pollution has become increasingly serious. Soil pollution not only affects the growth and yield of crops, but may also lead to groundwater pollution and threaten human health. Therefore, effective prevention and control of soil pollution and protection of the soil environment have become urgent issues that need to be addressed. In recent years, with the development of science and technology, soil environmental monitoring technology has also made significant progress. Traditional soil environmental monitoring methods mainly rely on manual sampling and laboratory testing, which is time-consuming and labor-intensive, and it is difficult to achieve large-scale, high-frequency monitoring. The application of modern technical means such as sensors, the Internet of Things, big data, and artificial intelligence provides new solutions for soil environmental monitoring.

[0003] However, the existing soil environment monitoring system still has some problems, mainly manifested in the following aspects: (1) Incomplete data collection: The existing soil environment monitoring system can only collect a single type of soil data, such as soil moisture or pH value, and lacks comprehensive collection of soil physical, chemical and other characteristics; the sampling points are unevenly distributed, making it difficult to cover the entire monitoring area, resulting in insufficient data representativeness. (2) Insufficient data processing capabilities: The collected soil data often contain noise and missing values, and there is no effective data cleaning and correction method, resulting in low data quality; data processing and analysis capabilities are limited, making it difficult to extract useful information from large amounts of data to support decision-making. (3) Imperfect data sharing and collaboration mechanisms: The existing soil environment monitoring system often operates independently and lacks a data sharing mechanism with other departments and systems, resulting in serious data islands; poor information transmission makes it difficult to achieve cross-departmental collaboration, affecting the overall effect of soil pollution prevention and control. (4) Insufficient comprehensive analysis and prediction capabilities: The existing system lacks comprehensive analysis capabilities for the soil environment, making it difficult to comprehensively assess the extent and risk of soil pollution; insufficient prediction capabilities make it impossible to warn of potential soil pollution problems in advance, affecting the effectiveness of prevention and control measures. (5) Irregular file management: The large amount of data generated during the prevention and control of soil environmental pollution lacks unified management, making it difficult to find and manage; irregular file management affects the traceability of data and the lifelong responsibility system of the project.

[0004] In order to solve the above problems, it is necessary to develop a soil environmental data collection and analysis monitoring system for soil pollution prevention and control, so as to realize the comprehensive collection, efficient processing and comprehensive analysis of soil environmental data, so as to improve the efficiency and effectiveness of soil pollution prevention and control. Summary of the invention

[0005] The present invention aims at the above-mentioned problems, makes up for the deficiencies of the prior art, and provides a soil environment data collection and analysis monitoring system for preventing and controlling soil pollution; the present invention can realize the comprehensive collection, efficient processing and comprehensive analysis of soil environment data, and can improve the efficiency and effect of soil pollution prevention and control.

[0006] To achieve the above purpose, the present invention adopts the following technical solution.

[0007] The present invention provides a soil environment data collection and analysis monitoring system for preventing and controlling soil pollution, comprising a soil environment data collection module, a data preprocessing module, a feature extraction and analysis module, a model training and prediction module, a data sharing and collaborative management module, and a soil environment archive management module;

[0008] The soil environment data acquisition module includes a multi-layer soil sampling unit, a groundwater sampling unit, and a biological monitoring unit; the multi-layer soil sampling unit is used to collect soil data at different depths through multi-layer soil sensors, including soil moisture, temperature, pH value, and conductivity; the groundwater sampling unit is used to automatically collect groundwater samples at different depths through intelligent drilling equipment and detect water quality parameters, including dissolved oxygen, pH value, turbidity, and harmful substance content; the biological monitoring unit is used to monitor the microbial activity and plant growth status in the soil through biological sensors and evaluate the biological health status of the soil;

[0009] The data preprocessing module is used to preprocess the soil environment data collected by the soil environment data collection module. The data preprocessing module includes a data cleaning unit and a data correction unit. The data cleaning unit is used to remove duplicate data and delete redundant data points. For missing data, a filling method is selected according to the nature of the data. The filling method includes a mean method, an interpolation method, or a method of deleting records containing missing values. The data correction unit is used to correct systematic errors caused by instrument errors or environmental interference. The systematic errors include the influence of temperature and humidity environmental parameters on soil data.

[0010] The feature extraction and analysis module is used to extract and analyze the features of the soil environmental data processed by the data preprocessing module; the feature extraction and analysis module includes a physical feature extraction unit, a chemical feature extraction unit and a biological feature extraction unit. The physical feature extraction unit is used to extract the physical features of soil water holding capacity, soil water content and water holding curve, and uses an advanced algorithm for feature enhancement, and the advanced algorithm adopts wavelet transform; the chemical feature extraction unit is used to extract the chemical features of soil pH value, organic matter content and nutrient content, and uses a chemometric method for feature optimization; the biological feature extraction unit is used to extract the biological features of soil microbial activity and plant growth status, and uses a bioinformatics method for feature extraction;

[0011] The model training and prediction module is used to perform model training on the feature data extracted by the feature extraction and analysis module. The model training and prediction module includes a data preprocessing unit, a model training unit and a model evaluation unit; the data preprocessing unit is used to perform normalization and standardization preprocessing on the extracted feature data to ensure the consistency and comparability of the data; the model training unit is used to train the soil environment analysis model through a deep learning algorithm to predict or classify different characteristics of the soil environment, and the deep learning algorithm is a convolutional neural network or a long short-term memory network; the model evaluation unit is used to evaluate the trained model to ensure the accuracy and robustness of the model, and the evaluation is performed using cross-validation and AUC indicators;

[0012] The data sharing and collaborative management module is used to realize the information sharing of the soil environmental data processed and analyzed by the above-mentioned model training and prediction modules. The data sharing and collaborative management module includes a data interface unit, a data link management unit, and a collaborative management unit; the data interface unit is used to connect with the official platform and the existing information systems of the Ecological Environment Bureau and the Natural Resources and Planning Bureau; the data link management unit is used to open up the data link with the superior department, effectively support the interconnection and sharing of soil pollution prevention and control related data with horizontal departments, and communicate with vertical departments; the collaborative management unit is used to provide multi-user and multi-role collaborative management functions, and support the management process of task allocation, progress tracking, and results review; the soil environment archive management module includes a data management unit and an archive query unit. The data management unit is used to uniformly manage the electronic and / or paper data generated in the process of soil environmental pollution prevention and control, including reference data, process data and result data; the archive query unit is used to provide an archive query function to facilitate users to find and manage relevant data.

[0013] As a preferred solution of the present invention, the soil environment data acquisition module also includes an atmospheric environment monitoring unit; the atmospheric environment monitoring unit: monitors the concentration of particulate matter and volatile organic compounds in the atmosphere through atmospheric sensors, and evaluates the impact of the atmosphere on the soil.

[0014] As another preferred solution of the present invention, the data preprocessing module further includes a fusion unit, which is used to fuse data from different sources to form a complete soil environment data set to support multi-dimensional analysis.

[0015] As another preferred embodiment of the present invention, the feature extraction and analysis module also includes a spatiotemporal feature extraction unit, which is used to extract the spatiotemporal characteristics of soil data and use a spatiotemporal analysis method to perform feature extraction, and the spatiotemporal analysis method is implemented using a spatiotemporal autoregressive model.

[0016] As another preferred embodiment of the present invention, the soil environment data collection and analysis monitoring system for preventing and controlling soil pollution also includes a visualization and decision support module, which is arranged between the model training and prediction module and the data sharing and collaborative management module.

[0017] Furthermore, the visualization and decision support module includes a data visualization unit, which is used to visualize the soil environmental data and prediction results trained by the model training unit in the form of charts, including time series charts, heat maps, and three-dimensional maps, to facilitate users to perform data analysis and decision support.

[0018] Furthermore, the visualization and decision support module also includes a decision support unit, which is used to provide decision support for soil pollution warning, soil remediation suggestions, and environmental management strategies to help users formulate scientific prevention and control measures.

[0019] As another preferred embodiment of the present invention, the soil environment data collection and analysis monitoring system for preventing and controlling soil pollution also includes a soil environment database, which includes a business database, a thematic database, and a geographic database; the business database is used to store soil survey data, analysis and evaluation data, soil remediation data, soil expert data, and archival data; the thematic database is used to store soil environment data in specific fields, such as agricultural soil and industrial soil; the geographic database is used to store soil environment data related to geographical location, such as soil distribution maps and pollution area maps.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] The soil environment data collection and analysis monitoring system for preventing and controlling soil pollution provided by the present invention realizes the comprehensive collection, efficient processing and comprehensive analysis of soil environment data, improves the efficiency and effect of soil pollution prevention and control, and has the following advantages:

[0022] (1) Comprehensive coverage: This system realizes the comprehensive collection of soil environmental data, covering multiple layers of soil, groundwater, atmospheric environment and biological monitoring;

[0023] (2) Efficient processing: Through data cleaning, correction and fusion, the quality and consistency of data are ensured, and the efficiency of data processing is improved;

[0024] (3) Comprehensive analysis: Through feature extraction and model training, a comprehensive analysis of the soil environment is achieved, providing scientific decision support;

[0025] (4) Information sharing: Through the data sharing and collaborative management module, information sharing with official platforms and relevant departments is achieved, improving the coordination and effectiveness of soil pollution prevention and control work;

[0026] (5) File management: Through the soil environment file management module, various data in the process of soil environmental pollution prevention and control are managed in a unified manner, making it convenient for users to search and manage. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the overall structure of the system of the present invention.

[0028] Figure 2 It is a structural schematic diagram of the soil environment data acquisition module of the system of the present invention.

[0029] Figure 3 It is a structural schematic diagram of the data preprocessing module of the system of the present invention.

[0030] Figure 4 It is a structural schematic diagram of the feature extraction and analysis module of the system of the present invention.

[0031] Figure 5 It is a schematic diagram of the structure of the model training and prediction module of the system of the present invention.

[0032] Figure 6 It is a structural diagram of the visualization and decision support module of the system of the present invention.

[0033] Figure 7 It is a structural diagram of the data sharing and collaborative management module of the system of the present invention.

[0034] Figure 8 It is a structural schematic diagram of the soil environment archive management module of the system of the present invention.

[0035] Fig. 9 It is a schematic diagram of the structure of the soil environment database of the system of the present invention.

[0036] Markings in the figure: 1 is soil environment data acquisition module, 2 is data preprocessing module, 3 is feature extraction and analysis module, 4 is model training and prediction module, 5 is visualization and decision support module, 6 is data sharing and collaborative management module, 7 is soil environment archive management module, and 8 is soil environment database;

[0037] 101 is a multi-layer soil sampling unit, 102 is a groundwater sampling unit, 103 is an atmospheric environment monitoring unit, and 104 is a biological monitoring unit; 201 is a data cleaning unit, 202 is a data correction unit, and 203 is a data fusion unit; 301 is a physical feature extraction unit, 302 is a chemical feature extraction unit, 303 is a biological feature extraction unit, and 304 is a spatiotemporal feature extraction unit; 401 is a data preprocessing unit, 402 is a model training unit, and 403 is a model evaluation unit; 501 is a data visualization unit, and 502 is a decision support unit; 601 is a data interface unit, 602 is a data link management unit, and 603 is a collaborative management unit; 701 is a material management unit, and 702 is an archive query unit; 801 is a business database, 802 is a thematic database, and 803 is a geographic database. DETAILED DESCRIPTION

[0038] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. It should be understood that the specific implementation methods described herein are only used to explain the present invention and are not used to limit the present invention.

[0039] Reference Figure 1 The present invention provides a soil environment data collection and analysis monitoring system for preventing and controlling soil pollution, comprising a soil environment data collection module 1, a data preprocessing module 2, a feature extraction and analysis module 3, a model training and prediction module 4, a visualization and decision support module 5, a data sharing and collaborative management module 6, a soil environment archive management module 7 and a soil environment database 8.

[0040] Specifically, Figure 2As shown, the soil environment data acquisition module 1 includes a multi-layer soil sampling unit 101, a groundwater sampling unit 102, an atmospheric environment monitoring unit 103 and a biological monitoring unit 104; the multi-layer soil sampling unit 101 uses a multi-layer soil sensor to collect soil data at different depths, including soil moisture, temperature, pH value, and conductivity. The multi-layer soil sensor uses the EC-5 multi-layer soil moisture sensor produced by METER Group. The sensor has the characteristics of high sensitivity and low power consumption, and can accurately measure soil moisture, temperature, pH value and conductivity at different depths; the sensor probes of the multi-layer soil sensor are distributed at depths of 10 cm, 30 cm, 50 cm and 100 cm in the soil, which can fully cover the vertical profile of the soil; the EC-5 multi-layer soil sensor can more comprehensively understand the vertical profile characteristics of the soil, thereby providing more accurate data support for soil environmental protection. The groundwater sampling unit 102 automatically collects groundwater samples at different depths and detects water quality parameters through intelligent drilling equipment; the intelligent drilling equipment uses the SmartDrill 2024 intelligent drilling equipment produced by Enviro Core Technologies, which can penetrate into the soil at different depths, automatically collect groundwater samples, and detect water quality parameters such as dissolved oxygen, pH value, turbidity and harmful substance content; this intelligent drilling equipment is equipped with an automatic cleaning mechanism, which can properly clean the plant leaves on the surface before collecting data to ensure that the collected groundwater samples can accurately reflect the water quality. The biological monitoring unit 104 monitors the microbial activity and plant growth status in the soil through biosensors. The biosensors include Bio Sens soil microbial activity sensors and Plant Sens plant growth status sensors. These biosensors can monitor the microbial activity and plant growth status in the soil, such as the number of soil microorganisms, enzyme activity, and plant photosynthesis rate. The atmospheric environment monitoring unit 103 uses an atmospheric sensor to monitor the concentration of particulate matter and volatile organic compounds in the atmosphere; the atmospheric environment monitoring unit uses Eco Tech AQ Mesh atmospheric sensor, which can specifically monitor the concentration of PM2.5 and PM10 particulate matter, VOC volatile organic compounds, sulfur dioxide, and nitrogen oxides in the atmosphere.

[0041] Specifically, Figure 3 As shown, the data preprocessing module 2 includes a data cleaning unit 201, a data correction unit 202 and a data fusion unit 203. The data cleaning unit 201 removes duplicate data and deletes redundant data points. For missing data, a filling method is selected according to the nature of the data; the data correction unit 202 corrects the systematic errors caused by instrument errors or environmental interference; the data fusion unit 203 fuses data from different sources to form a complete soil environmental data set.

[0042] The data cleaning unit 201 specifically includes: firstly, removing duplicate data to ensure the uniqueness of the data, deduplicating the data through a hash algorithm to avoid the impact of duplicate data on subsequent analysis; deleting redundant data points, including obviously abnormal data points and meaningless data points, identifying and deleting these data points through statistical analysis and threshold setting; for missing data, selecting a filling method according to the nature of the data, the filling method includes a mean method, an interpolation method, or a method of deleting records containing missing values ​​to ensure the integrity of the data. The data correction unit 202 specifically includes: correcting the systematic errors caused by instrument errors, by comparing the calibration data with the actual data, establishing a correction model, and correcting the data; correcting the systematic errors caused by environmental interference, by monitoring environmental parameters, establishing an interference model, and correcting the data; regularly verifying the corrected data to ensure the accuracy and consistency of the data. The data fusion unit 203 specifically includes: fusing data from different sources to form a complete soil environment data set, integrating multiple layers of soil data, groundwater data, atmospheric data and biological data through a data fusion algorithm to generate a multi-dimensional soil environment data set; ensuring the consistency of the fused data to avoid data conflicts and contradictions, and ensuring the accuracy and reliability of the data through data alignment and verification.

[0043] Specifically, Figure 4 As shown, the feature extraction and analysis module 3 includes a physical feature extraction unit 301, a chemical feature extraction unit 302, a biological feature extraction unit 303 and a spatiotemporal feature extraction unit 304; the physical feature extraction unit 301 extracts the physical features of soil water holding capacity, soil water content and water holding curve; the chemical feature extraction unit 302 extracts the chemical features of soil pH value, organic matter content and nutrient content; the biological feature extraction unit 303 extracts the biological features of soil microbial activity and plant growth status; the spatiotemporal feature extraction unit 304 extracts the spatiotemporal features of soil data.

[0044] The physical feature extraction unit 301 specifically includes: extracting the water holding capacity of the soil, evaluating the water holding capacity of the soil through the analysis of the soil moisture content and soil texture; extracting the water content of the soil, evaluating the moisture status of the soil through the moisture data of the multi-layer soil sensor; generating the water holding curve of the soil, drawing the water holding curve of the soil through the soil moisture data of different depths, and evaluating the dynamic change of soil moisture. The chemical feature extraction unit 302 specifically includes: extracting the pH value of the soil, evaluating the acidity and alkalinity of the soil through the soil pH value data of the multi-layer soil sensor; extracting the organic matter content of the soil, evaluating the organic matter status of the soil through laboratory analysis and sensor data; extracting the nutrient content of the soil, such as nitrogen, phosphorus, and potassium, and evaluating the nutrient status of the soil through laboratory analysis and sensor data. The biological feature extraction unit 303 specifically includes: extracting the microbial activity of the soil, evaluating the biological health status of the soil through the data of the soil microbial activity sensor; extracting the growth status of the plant, and evaluating the growth status and health status of the plant through the data of the plant growth status sensor. The spatiotemporal feature extraction unit 304 specifically includes: extracting the temporal features of soil data, and evaluating the dynamic changes of soil parameters through time series analysis; extracting the spatial features of soil data, and evaluating the spatial distribution of soil parameters through spatial analysis; generating the spatiotemporal features of soil data, and evaluating the spatiotemporal change laws of soil parameters through spatiotemporal analysis.

[0045] Specifically, Figure 5As shown, the model training and prediction module 4 is used to perform model training on the feature data extracted by the feature extraction and analysis module 3. The model training and prediction module 4 includes a data preprocessing unit 401, a model training unit 402 and a model evaluation unit 403; the data preprocessing unit 401 is used to normalize and standardize the extracted feature data to ensure the consistency and comparability of the data; wherein, the normalization: normalizes the extracted feature data, scales the data to between 0 and 1, and eliminates the influence of the dimension; the standardization: standardizes the extracted feature data, converts the data into a standard normal distribution with a mean of 0 and a standard deviation of 1, and eliminates the discreteness of the data. The model training unit 402 is used to train the soil environment analysis model through a deep learning algorithm to predict or classify different characteristics of the soil environment. The deep learning algorithm is a convolutional neural network or a long short-term memory network. The performance and generalization ability of the model are improved through hyperparameter tuning and model structure optimization. The cross-validation and grid search methods are used to find the optimal model parameters. The model evaluation unit 403 is used to evaluate the trained model to ensure the accuracy and robustness of the model. The evaluation of the trained model includes accuracy evaluation and robustness evaluation. Accuracy evaluation: using accuracy, precision, recall and F1 score indicators to evaluate the classification performance of the model; robustness evaluation: by testing the performance of the model in different environments, evaluating the robustness and stability of the model; using the AUC indicator to evaluate the comprehensive performance of the model.

[0046] Specifically, Figure 6 As shown, the visualization and decision support module 5 includes a data visualization unit 501 and a decision support unit 502. The data visualization unit 501 is used to visualize the soil environment data and prediction results in charts, including time series charts, heat maps, and three-dimensional maps, so as to facilitate data analysis and decision support for users; wherein, the time series chart: generates a time series chart of soil environment data to show the dynamic changes of soil parameters; the heat map: generates a heat map of soil environment data to show the spatial distribution of soil parameters; the three-dimensional map: generates a three-dimensional map of soil environment data to show the spatiotemporal changes of soil parameters. The decision support unit 502 is used to provide decision support for soil pollution warning, soil remediation suggestions, and environmental management strategies; wherein, the soil pollution warning: generates a soil pollution warning based on the soil environment data and prediction results to remind users to take timely measures; the soil remediation suggestion: generates a soil remediation suggestion based on the soil environment data and prediction results to guide users to carry out soil remediation; the environmental management strategy: generates an environmental management strategy based on the soil environment data and prediction results to help users formulate scientific environmental management measures.

[0047] Specifically, Figure 7As shown, the data sharing and collaborative management module 6 includes a data interface unit 601, a data link management unit 602 and a collaborative management unit 603. The data interface unit 601 is connected to the official platform to realize the information sharing of soil environmental data. The data link management unit 602 opens the data link with the superior department, and the collaborative management unit 603 provides multi-user and multi-role collaborative management functions. Among them, the data interface unit 601: is used to complete the connection with the existing information system platform of the Ecological Environment Bureau and the Natural Resources and Planning Bureau to realize the information sharing of soil environmental data, and ensure the safe transmission and sharing of data through the API interface and data exchange protocol; standardize the shared data to ensure that the format and content of the data meet the requirements of the official platform. Among them, the data link management unit 602: is used to open the data link with the superior department to realize the data transmission and transmission, and ensure the real-time transmission and synchronous update of data through data link management; back up the shared data to ensure the security and reliability of the data. Among them, the collaborative management unit 603 is used to provide multi-user management functions, support users of different roles to access and manage soil environmental data, and ensure data security and privacy through permission settings; provide task allocation functions, support multi-user collaborative completion of soil environmental monitoring and management tasks, and improve work efficiency and collaborative capabilities through task allocation and progress tracking.

[0048] Specifically, Figure 8 As shown, the soil environment archive management module 7 includes a data management unit 701 and an archive query unit 702. The data management unit 701 uniformly manages the electronic and / or paper data generated in the process of soil environmental pollution prevention and control, and the archive query unit 702 provides an archive query function to facilitate users to find and manage relevant data. Among them, the data management unit 701 is used to classify and manage the data generated in the process of soil environmental pollution prevention and control, including reference data, process data and result data; store the data in a central database to ensure the security and reliability of the data, and realize remote access and backup of the data through cloud storage technology; provide a data sharing function, support multi-user access and management of data, and ensure the security and privacy of the data through permission setting. Among them, the archive query unit 702 is used to provide an archive query function, support users to query relevant data through keywords and date conditions, and improve query efficiency and accuracy through full-text search and intelligent recommendation; provide an archive management function, support users to add, modify and delete data, and ensure the integrity and traceability of data through version control.

[0049] Specifically, Fig. 9As shown, the soil environment database 8 includes a business database 801, a thematic database 802 and a geographic database 803. The business database 801 stores soil survey data, analysis and evaluation data, soil remediation data, soil expert data and archival data. The thematic database 802 stores soil environment data in a specific field. The geographic database 803 stores soil environment data related to the geographic location.

[0050] The soil survey data, analysis and evaluation data, soil remediation data, soil expert data and archive data stored in the business database 801 are as follows: the soil survey data include soil sampling data, groundwater sampling data, atmospheric environment monitoring data and biological monitoring data; the analysis and evaluation data include soil water holding capacity, soil pH value, soil organic matter content and soil microbial activity; the soil remediation data include soil remediation scheme and soil remediation effect evaluation; the soil expert data include the opinions and suggestions of soil experts; the archive data include electronic and / or paper materials generated in the process of soil environmental pollution prevention and control. The soil environmental data in specific fields stored in the subject database 802 include agricultural soil data, industrial soil data and urban green space data, as follows: the agricultural soil data include farmland soil survey data and farmland soil environmental analysis and evaluation data; the industrial soil data include industrial zone soil survey data and industrial zone soil environmental analysis and evaluation data; the urban green space data include urban green space soil survey data and urban green space soil environmental analysis and evaluation data. Among them, the soil environmental data related to the geographical location stored in the geographic database 803 include soil distribution maps and pollution area maps, as follows; the soil distribution map: includes soil distribution maps of different depths and soil distribution maps of different areas; the pollution area map: includes soil pollution area maps and groundwater pollution area maps.

[0051] In actual use, the soil environment data collection and analysis monitoring system for preventing and controlling soil pollution provided by the present invention can be applied to various scenes such as farmland, industrial area and urban green space. Soil data of different depths are collected through multi-layer soil sampling unit 101, groundwater samples are collected through groundwater sampling unit 102, atmospheric environment is monitored through atmospheric environment monitoring unit 103, biological health status is monitored through biological monitoring unit 104, and the collected data are cleaned, corrected and integrated through data preprocessing module 2 to form a complete soil environment data set; then the physical, chemical, biological and spatiotemporal characteristics of the soil are extracted by feature extraction and analysis module 3 according to the soil environment data set, and the soil environment analysis model is trained by model training and prediction module 4 through deep learning algorithm to generate prediction results; the prediction results generated by model training and prediction module 4 are displayed by visualization and decision support module 5 through charts to provide decision support; data sharing and collaborative management module 6 realizes information sharing with official platforms and relevant departments, and soil environment archive management module 7 uniformly manages relevant information; soil environment database 8 stores all data to support the operation of the system.

[0052] In summary, the soil environment data collection and analysis monitoring system for preventing and controlling soil pollution of the present invention, with the help of advanced sensor technology, Internet of Things technology and deep learning algorithm, realizes the comprehensive collection, efficient processing and comprehensive analysis of soil environment data, and improves the efficiency and effect of soil pollution prevention and control.

[0053] It can be understood that the above specific description of the present invention is only used to illustrate the present invention and is not limited to the technical solutions described in the embodiments of the present invention. Those skilled in the art should understand that the present invention can still be modified or replaced by equivalents to achieve the same technical effects; as long as the use requirements are met, they are within the protection scope of the present invention.

Claims

1. A soil environment data collection and analysis monitoring system for preventing and controlling soil pollution, characterized by: It includes soil environment data collection module, data preprocessing module, feature extraction and analysis module, model training and prediction module, data sharing and collaborative management module and soil environment archive management module; The soil environment data acquisition module includes a multi-layer soil sampling unit, a groundwater sampling unit, and a biological monitoring unit; the multi-layer soil sampling unit is used to collect soil data at different depths through multi-layer soil sensors, including soil moisture, temperature, pH value, and conductivity; the groundwater sampling unit is used to automatically collect groundwater samples at different depths through intelligent drilling equipment and detect water quality parameters, including dissolved oxygen, pH value, turbidity, and harmful substance content; the biological monitoring unit is used to monitor the microbial activity and plant growth status in the soil through biological sensors and evaluate the biological health status of the soil; The data preprocessing module is used to preprocess the soil environment data collected by the soil environment data collection module. The data preprocessing module includes a data cleaning unit and a data correction unit. The data cleaning unit is used to remove duplicate data and delete redundant data points. For missing data, a filling method is selected according to the nature of the data. The filling method includes a mean method, an interpolation method, or a method of deleting records containing missing values. The data correction unit is used to correct systematic errors caused by instrument errors or environmental interference. The systematic errors include the influence of temperature and humidity environmental parameters on soil data. The feature extraction and analysis module is used to extract and analyze the features of the soil environmental data processed by the data preprocessing module; the feature extraction and analysis module includes a physical feature extraction unit, a chemical feature extraction unit and a biological feature extraction unit, the physical feature extraction unit is used to extract the physical features of soil water holding capacity, soil water content and water holding curve, and use an advanced algorithm to enhance the features, and the advanced algorithm uses wavelet transform; Chemical feature extraction unit: used to extract the chemical features of soil pH, organic matter content, and nutrient content, and use chemometric methods to optimize the features; Biological feature extraction unit: used to extract biological features of soil microbial activity and plant growth conditions, using bioinformatics methods for feature extraction; The model training and prediction module is used to perform model training on the feature data extracted by the feature extraction and analysis module. The model training and prediction module includes a data preprocessing unit, a model training unit and a model evaluation unit; the data preprocessing unit is used to perform normalization and standardization preprocessing on the extracted feature data to ensure the consistency and comparability of the data; Model training unit: used to train soil environment analysis models through deep learning algorithms to predict or classify different characteristics of soil environment. The deep learning algorithms are convolutional neural networks or long short-term memory networks. Model evaluation unit: used to evaluate the trained model to ensure the accuracy and robustness of the model. Cross-validation and AUC indicators are used for evaluation. The data sharing and collaborative management module is used to realize the information sharing of the soil environmental data processed and analyzed by the above-mentioned model training and prediction modules. The data sharing and collaborative management module includes a data interface unit, a data link management unit, and a collaborative management unit; the data interface unit is used to connect with the official platform and the existing information systems of the Ecological Environment Bureau and the Natural Resources and Planning Bureau; the data link management unit is used to open up the data link with the superior department, effectively support the interconnection and sharing of soil pollution prevention and control related data with horizontal departments, and communicate with vertical departments; the collaborative management unit is used to provide multi-user and multi-role collaborative management functions, and support the management process of task allocation, progress tracking, and results review; the soil environment archive management module includes a data management unit and an archive query unit. The data management unit is used to uniformly manage the electronic and / or paper data generated in the process of soil environmental pollution prevention and control, including reference data, process data and result data; the archive query unit is used to provide an archive query function to facilitate users to find and manage relevant data.

2. The soil environment data collection and analysis monitoring system for preventing and controlling soil pollution according to claim 1 is characterized by: The soil environment data acquisition module also includes an atmospheric environment monitoring unit; the atmospheric environment monitoring unit: monitors the concentration of particulate matter and volatile organic compounds in the atmosphere through atmospheric sensors, and evaluates the impact of the atmosphere on the soil.

3. The soil environment data collection and analysis monitoring system for preventing and controlling soil pollution according to claim 1 is characterized by: The data preprocessing module also includes a fusion unit, which is used to fuse data from different sources to form a complete soil environment data set to support multi-dimensional analysis.

4. The soil environment data collection and analysis monitoring system for preventing and controlling soil pollution according to claim 1 is characterized by: The feature extraction and analysis module also includes a spatiotemporal feature extraction unit, which is used to extract the spatiotemporal features of soil data and use a spatiotemporal analysis method to extract features. The spatiotemporal analysis method is implemented using a spatiotemporal autoregressive model.

5. The soil environment data collection and analysis monitoring system for preventing and controlling soil pollution according to claim 1 is characterized by: The soil environment data collection and analysis monitoring system for preventing and controlling soil pollution also includes a visualization and decision support module, which is arranged between the model training and prediction module and the data sharing and collaborative management module.

6. The soil environment data collection and analysis monitoring system for preventing and controlling soil pollution according to claim 5 is characterized by: The visualization and decision support module includes a data visualization unit, which is used to visualize the soil environmental data and prediction results trained by the model training unit in the form of charts, including time series charts, heat maps, and three-dimensional maps, so as to facilitate users to perform data analysis and decision support.

7. The soil environment data collection and analysis monitoring system for preventing and controlling soil pollution according to claim 5 is characterized by: The visualization and decision support module also includes a decision support unit, which is used to provide decision support for soil pollution warning, soil remediation suggestions, and environmental management strategies to help users formulate scientific prevention and control measures.

8. The soil environment data collection and analysis monitoring system for preventing and controlling soil pollution according to claim 1 is characterized by: The soil environment data collection and analysis monitoring system for preventing and controlling soil pollution also includes a soil environment database, which includes a business database, a thematic database, and a geographic database; the business database is used to store soil survey data, analysis and evaluation data, soil remediation data, soil expert data, and archive data; the thematic database is used to store soil environment data in specific fields, such as agricultural soil and industrial soil; Geographic database: used to store soil environmental data related to geographical locations, such as soil distribution maps and pollution area maps.

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