Intelligent supervision platform for regional water environment quality

Abstract

The invention belongs to the technical field of surface water monitoring and environment management, and particularly relates to a regional water environment quality intelligent supervision platform comprising a monitoring data acquisition and anti-interference module used for acquiring data information related to a water environment, the module comprising an electronic fence setting and monitoring unit, a double-layer yellow fence is arranged at a surface water national test section water collecting port, the inner layer prevents man-made interference monitoring data, the outer layer monitors displacement of water collecting facilities, and the surrounding environment is managed in combination with video monitoring, positioning and electronic map technologies; the artificial intelligence identification and alarm module is responsible for identifying abnormal conditions occurring in the monitoring process and sending out alarm information; according to the invention, by constructing the intelligent supervision system comprising a data acquisition module, an intelligent identification module, a three-dimensional supervision module and the like, the problems of much man-made interference, non-visual data application, difficulty in tracing and the like in surface water national examination section monitoring are solved, and accurate and efficient supervision is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of surface water monitoring and environmental management, and specifically is a regional water environment quality intelligent supervision platform. Background Art

[0002] Water quality monitoring of national surface water sections is crucial for assessing water environment quality and formulating pollution prevention and control strategies. With the improvement of environmental management requirements and the development of technology, innovative supervision systems and methods are urgently needed to improve the accuracy, timeliness and management effectiveness of national surface water section monitoring.

[0003] In the prior art, traditional monitoring and management methods have many limitations, such as monitoring data is susceptible to human interference, the supervision means are single, there is a lack of an efficient collaborative management system, data application and display are not intuitive and comprehensive enough, and abnormal situations cannot be traced back in a timely and effective manner. For this reason, the present invention provides a regional water environment quality intelligent supervision platform. Summary of the invention

[0004] In order to make up for the shortcomings of existing technologies and solve the many limitations of traditional monitoring and management methods, such as the monitoring data being easily affected by human interference, the single means of supervision, the lack of an efficient collaborative management system, the data application and display being not intuitive and comprehensive enough, and the inability to trace abnormal situations in a timely and effective manner.

[0005] 1. The technical solution adopted by the present invention to solve its technical problem is: a regional water environment quality intelligent supervision platform described in the present invention includes: Monitoring data collection and anti-interference module: used to collect data information related to the water environment. This module includes an electronic fence setting and monitoring unit. A double-layer yellow fence is set at the water intake of the national surface water examination section. The inner layer prevents human interference in the monitoring data, and the outer layer monitors the displacement of the water collection facilities. It combines video monitoring, positioning and electronic map technology to manage the surrounding environment.

[0006] Artificial intelligence identification and alarm module: responsible for identifying abnormal situations that occur during the monitoring process and issuing alarm information; Three-dimensional supervision and collaborative management module: Through the integrated air-ground monitoring linkage, the water environment in the region is supervised in an all-round and three-dimensional manner, and a three-level collaborative management platform is established to coordinate the management work among different entities; Data linkage analysis and traceability module: Analyze the collected data and trace the source of abnormal water quality; Smart supervision one-picture display module: displays water environment supervision information in an intuitive way; Platform operation and maintenance and exception management module: ensure the stable operation of the platform and manage any abnormal situations that arise.

[0007] Preferably, the monitoring data acquisition and anti-interference module includes: Outlet data monitoring and collection unit: specially for data monitoring and collection of outlet in water environment; Water quality sensor unit: Equipped with various types of water quality sensors including dissolved oxygen sensor, chemical oxygen demand sensor, and pH sensor.

[0008] Preferably, the artificial intelligence recognition and alarm module includes: Dissolved oxygen content warning unit: set the warning threshold of dissolved oxygen content. When the monitored dissolved oxygen content is lower than or higher than the preset threshold, the alarm mechanism is automatically triggered; Abnormal behavior and event recognition unit: A variety of abnormal behaviors and events are recognized through trained algorithms. These abnormal behaviors and events include but are not limited to human interference with monitoring equipment, illegal discharge of pollutants, abnormal floating objects on the water surface, and sudden changes in water quality parameters.

[0009] Preferably, the three-dimensional supervision and collaborative management module includes: Drone secondary inspection mechanism unit: When an abnormal situation is found, a drone equipped with a high-definition camera and related monitoring equipment will conduct a secondary inspection of the corresponding area to enhance the ability to judge and handle abnormal situations; Functional units of the three-level management entity: the first-level management entity is responsible for formulating overall supervision strategies and standards, the second-level management entity is responsible for managing the standards and rules for monitoring data, and the third-level management entity is responsible for formulating inspection plans, preliminarily screening and analyzing data, and providing data support to the superior management entity. Entities at all levels collaborate through an information sharing platform.

[0010] Preferably, the data linkage analysis and traceability module includes: Abnormal water quality source determination unit: Through comprehensive analysis of water quality data, combined with time, space and environmental factors, and using data analysis algorithms and models, the source of abnormal water quality can be traced.

[0011] Preferably, the smart supervision one-picture display module includes: Information labeling unit of the smart supervision one-picture platform: label water environment supervision information on the platform and associate it with real-time data, and use GIS technology to achieve real-time information update and visualization.

[0012] Preferably, the platform operation and maintenance and exception management module includes: System automatic detection unit: automatically monitors the platform operation status, including the operation status of hardware equipment and the performance of software systems.

[0013] Exception handling process unit: Establish a complete processing process for abnormal situations such as equipment failure, data anomalies, network interruptions, etc. to form a closed-loop management.

[0014] The beneficial effects of the present invention are as follows: 1. The regional water environment quality intelligent supervision platform described in the present invention effectively prevents human interference through measures such as electronic fences, intelligent identification and alarm, and abnormal operation monitoring, so as to ensure the authenticity and reliability of monitoring data and provide an accurate basis for water environment assessment and decision-making.

[0015] 2. The regional water environment quality intelligent supervision platform described in the present invention has artificial intelligence to identify anomalies in real time, integrated air-ground monitoring linkage and a three-level collaborative management system, which can quickly discover and deal with problems, improve supervision efficiency, and respond to various water environment risks in a timely manner.

[0016] 3. The regional water environment quality intelligent supervision platform described in the present invention integrates multiple factors of information in one picture for intelligent supervision, realizes intuitive and comprehensive visual supervision, facilitates managers to quickly grasp the situation, and improves the scientificity and timeliness of decision-making.

[0017] 4. The data linkage analysis and traceability functions of the regional water environment quality intelligent supervision platform described in the present invention help to accurately find the root cause of abnormal water quality, provide strong support for the formulation of targeted governance measures, and improve the accuracy and effectiveness of water environment governance.

[0018] 5. The regional water environment quality intelligent supervision platform described in the present invention, the platform operation and maintenance and abnormal management mechanism enable the entire intelligent supervision system to operate continuously and stably, reduce the risk of system failure, and improve the continuity and reliability of supervision work. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention will be further described below in conjunction with the accompanying drawings.

[0020] Figure 1 It is a flow chart of platform operation and maintenance management in the present invention. DETAILED DESCRIPTION

[0021] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0022] like Figure 1 As shown, this embodiment provides a regional water environment quality intelligent supervision platform, and its specific steps are as follows: 1. Monitoring data collection and anti-interference High-definition video surveillance cameras are installed around the water intake of a national surface water monitoring section, with the inner yellow electronic fence radius set to 10 meters and the outer yellow electronic fence radius set to 15 meters; the surveillance cameras are connected to the positioning system and electronic map so that the surveillance images can be accurately displayed at the corresponding location on the electronic map.

[0023] Deploy high-precision water quality monitoring sensors, such as dissolved oxygen sensors and chemical oxygen demand sensors, and connect them to data acquisition instruments; the data acquisition instruments transmit the data collected by the sensors to the data management center in real time according to the HJ / T212 communication protocol; At the same time, Internet of Things monitoring equipment is installed at the sewage outlets of centralized sewage treatment plants and key enterprises to collect operating condition monitoring data and online monitoring data of wastewater pollution sources, and transmit them to the corresponding management modules.

[0024] 2. Artificial intelligence identification and warning 1,000 video clips of surface water monitoring areas in different scenarios were collected, including normal situations and various abnormal situations (such as human dumping of pollutants, equipment damage, etc.). These video clips were cleaned to remove blurry and repeated images, and then image annotation was performed to mark the type, location and other information of abnormal behaviors and events.

[0025] Using a deep learning framework, combined with convolutional neural networks, back-propagation learning and the YoloV5 target detection algorithm, the model was trained using labeled video materials. After multiple iterations of training, an algorithm model was obtained that can accurately identify abnormal behaviors and events such as human interference with monitoring equipment, illegal discharge of pollutants, and abnormal floating objects on the water surface.

[0026] The trained algorithm model is deployed into the artificial intelligence recognition system and connected to the video surveillance equipment. When the video surveillance image is transmitted to the recognition system, the model analyzes the image in real time. Once abnormal behavior or events are identified, the system immediately issues a sound alarm and sends text message notifications to relevant managers. At the same time, detailed information of the alarm event is recorded in the monitoring system, including time, location, type of abnormal behavior, etc.

[0027] Establish a big data analysis platform, access multi-source data such as surface water quality monitoring data, video surveillance data, meteorological data, and pollution discharge data of surrounding enterprises; conduct real-time analysis of water quality monitoring data, and use algorithms such as the moving average method to establish an abnormal warning model. Set the dissolved oxygen content below 4mg / L or the chemical oxygen demand above 60mg / L as abnormal thresholds, and trigger a warning when the data exceeds the threshold.

[0028] 3. Three-dimensional supervision and collaborative management Select appropriate high points around the monitoring section to install "mid-high point" monitoring equipment so that it can cover the entire monitoring area; at the same time, equip it with drones and corresponding flight control systems and shooting equipment.

[0029] A three-level collaborative management platform consisting of primary, secondary and tertiary management entities will be established. The primary management entity will be responsible for formulating overall regulatory strategies and standards, and clarifying the responsibilities and work processes at all levels; the secondary management entity will be responsible for managing the standards and rules for monitoring data, such as setting thresholds for water quality data; the tertiary management entity will formulate daily inspection plans on the platform, arrange inspection personnel and routes, perform preliminary data screening, and provide data support to the superior management entity. Entities at all levels will collaborate through an information sharing platform.

[0030] When the "mid-high point" monitoring equipment finds suspected abnormal conditions in the monitoring area, such as large areas of oil on the water surface, it immediately sends an alarm message to the platform and starts the drone for secondary inspection; the drone takes off from the parking point and flies to the target area according to the preset route, shooting high-definition video and sending it back to the monitoring center in real time; the management personnel of the secondary management entity organize personnel to go to the scene for verification and processing based on the alarm information and drone video; after receiving the notification, the operation and maintenance organization checks whether the monitoring equipment is operating normally and whether there are any abnormalities in the data. After the processing is completed, the secondary management entity uploads the processing results to the platform, and the primary management entity reviews them, forming a closed-loop management of the entire process from alarm to processing.

[0031] 4. Data linkage analysis and traceability When water quality data is warned of abnormal changes, the system automatically searches the big data platform for relevant information such as video surveillance data of the same period and the same area, pollution data of surrounding enterprises, etc.; through data mining and correlation analysis technology, compare the video images before and after the water quality abnormality, the changes in the enterprise's pollution discharge, etc., to determine the possible causes of the water quality abnormality. For example, if it is found in the video that a large amount of sewage is discharged from the sewage outlet of a certain enterprise before the water quality is abnormal, and the water quality characteristics of the discharged sewage are consistent with the abnormal water quality of the monitoring section, it is preliminarily judged that the enterprise's pollution discharge is the source of the water quality abnormality; further combined with meteorological data, water flow speed, wind direction and other factors are analyzed to determine the spread and impact of the pollution, and provide a decision-making basis for subsequent governance.

[0032] 5. Smart supervision with one picture A smart supervision map platform is built based on GIS technology, and the geographical location, distribution of monitoring sites, location of monitoring points and other information of the national surface water monitoring sections are marked on the electronic map; real-time water quality monitoring data, video surveillance images, alarm information, etc. are associated with the corresponding locations on the map through interfaces.

[0033] After logging into the platform, managers at the first-level management entity level can view the overall distribution of national surface water sections in the entire region, including the water quality compliance of each section (marked with different colors, such as green for compliance and red for exceeding the standard), the number of alarm messages, etc.; clicking on a specific section can view the detailed monitoring data, real-time video footage, recent alarm event lists, etc. of that section; after logging in, managers at the second-level management entity level can view section information within the region, and their authority is limited to the management and operation of relevant data in this region; at the section level, managers can view more detailed historical data, equipment operating status and other information of the section, to achieve hierarchical and all-round supervision of national surface water sections.

[0034] 6. Platform operation and maintenance and exception management The operation and maintenance personnel formulate regular inspection plans and conduct on-site inspections of monitoring equipment once a week, including cleaning and calibration of sensors, and checking the power supply of equipment. The data transmission equipment is inspected monthly to ensure stable network connections and normal operation of communication protocols. The software system is updated and upgraded every quarter to fix vulnerabilities and optimize performance.

[0035] An operation behavior monitoring module is set up in the platform to record and analyze the time and frequency of manual lookout activation. If it is found that manual lookout is activated abnormally frequently within a certain period of time, such as more than 5 times within 10 minutes, the system will automatically issue an alarm message to prompt the management personnel to verify. The management personnel will analyze and judge the alarm event. If it is found that the staff operated it incorrectly, they will be trained and reminded; if it is judged to be malicious interference, timely measures will be taken to stop it, such as suspending the relevant account permissions, and recording the processing results to ensure the normal operation of the platform and the security and reliability of monitoring data.

[0036] The above embodiments are only some of the implementation methods of the present invention, and can be adjusted and optimized according to specific needs and environment in actual application. The surface water national examination section intelligent supervision system and method of the present invention can effectively improve the level of surface water monitoring and management, and provide strong support for water environment quality improvement and ecological protection.

Claims

1. A regional water environment quality intelligent supervision platform, characterized by: include: Monitoring data collection and anti-interference module: used to collect data information related to the water environment. This module includes an electronic fence setting and monitoring unit. A double-layer yellow fence is set at the water intake of the surface water national examination section. The inner layer prevents human interference with the monitoring data, and the outer layer monitors the displacement of the water collection facilities. It combines video monitoring, positioning and electronic map technology to manage the surrounding environment; Artificial intelligence identification and alarm module: responsible for identifying abnormal situations that occur during the monitoring process and issuing alarm information; Three-dimensional supervision and collaborative management module: Through the integrated air-ground monitoring linkage, the water environment in the region is supervised in an all-round and three-dimensional manner, and a three-level collaborative management platform is established to coordinate the management work among different entities; Data linkage analysis and traceability module: Analyze the collected data and trace the source of abnormal water quality; Smart supervision one-picture display module: displays water environment supervision information in an intuitive way; Platform operation and maintenance and exception management module: ensure the stable operation of the platform and manage any abnormal situations that arise.

2. According to a regional water environment quality intelligent supervision platform as claimed in claim 1, it is characterized by: The monitoring data acquisition and anti-interference module includes: Outlet data monitoring and collection unit: specially for data monitoring and collection of outlet in water environment; Water quality sensor unit: Equipped with various types of water quality sensors including dissolved oxygen sensor, chemical oxygen demand sensor, and pH sensor.

3. According to a regional water environment quality intelligent supervision platform as claimed in claim 1, it is characterized by: The artificial intelligence recognition and alarm module includes: Dissolved oxygen content warning unit: set the warning threshold of dissolved oxygen content. When the monitored dissolved oxygen content is lower than or higher than the preset threshold, the alarm mechanism is automatically triggered; Abnormal behavior and event recognition unit: A variety of abnormal behaviors and events are recognized through trained algorithms. These abnormal behaviors and events include but are not limited to human interference with monitoring equipment, illegal discharge of pollutants, abnormal floating objects on the water surface, and sudden changes in water quality parameters.

4. According to a regional water environment quality intelligent supervision platform as claimed in claim 1, it is characterized by: The three-dimensional supervision and collaborative management module includes: Drone secondary inspection mechanism unit: When an abnormal situation is found, a drone equipped with a high-definition camera and related monitoring equipment will conduct a secondary inspection of the corresponding area to enhance the ability to judge and handle abnormal situations; Functional units of the three-level management entity: the first-level management entity is responsible for formulating overall supervision strategies and standards, the second-level management entity is responsible for managing the standards and rules for monitoring data, and the third-level management entity is responsible for formulating inspection plans, preliminarily screening and analyzing data, and providing data support to the superior management entity. Entities at all levels collaborate through an information sharing platform.

5. According to a regional water environment quality intelligent supervision platform as claimed in claim 1, it is characterized by: The data linkage analysis and traceability module includes: Abnormal water quality source determination unit: Through comprehensive analysis of water quality data, combined with time, space and environmental factors, and using data analysis algorithms and models, the source of abnormal water quality can be traced.

6. According to a regional water environment quality intelligent supervision platform as claimed in claim 1, it is characterized by: The smart supervision one-picture display module includes: Information labeling unit of the smart supervision one-picture platform: label water environment supervision information on the platform and associate it with real-time data, and use GIS technology to achieve real-time information update and visualization.

7. According to a regional water environment quality intelligent supervision platform as claimed in claim 1, it is characterized by: The platform operation and maintenance and exception management module includes: System automatic detection unit: automatically monitors the platform operation status, including the operation status of hardware equipment and the performance of software system; Exception handling process unit: Establish a complete processing process for abnormal situations such as equipment failure, data anomalies, network interruptions, etc. to form a closed-loop management.

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