Monitoring system for ecological environment and environmental pollution

Abstract

The invention belongs to the technical field of ecological environment monitoring, and provides an ecological environment and environmental pollution monitoring system, which comprises a multifunctional sensing array; an intelligent analysis platform; a remote monitoring and early warning system; an adaptive energy management system; a public participation module; according to the system, a multifunctional sensing array, an intelligent analysis platform, a remote monitoring and early warning system, a self-adaptive energy management system and a public participation module are integrated; real-time high-precision monitoring of multi-dimensional environmental parameters, automatic identification and early warning of environmental pollution events, accurate prediction of environmental change trends, timely evaluation of ecological system health conditions, automatic adjustment of energy supply and promotion of public participation in environmental protection activities are realized; the efficiency and accuracy of ecological environment monitoring are remarkably improved, making and implementation of environment protection decisions are effectively supported, meanwhile, the environmental awareness of the public is enhanced, and public participation of environment protection is promoted.

Description

Technical Field

[0001] The invention belongs to the technical field of ecological environment monitoring, in particular to a monitoring system for ecological environment and environmental pollution. Background Art

[0002] At present, with the acceleration of industrialization and urbanization, the ecological environment is facing unprecedented pressure and the problem of environmental pollution is becoming increasingly serious.

[0003] Traditional environmental monitoring methods often rely on manual sampling and laboratory analysis, which is not only time-consuming and labor-intensive, but also difficult to achieve large-scale, real-time, and high-precision monitoring. In addition, the processing and analysis of environmental data lack intelligence, making it difficult to quickly respond to environmental pollution incidents and effectively prevent and control the spread of pollution.

[0004] Therefore, those skilled in the art have proposed a monitoring system for ecological environment and environmental pollution to solve the problems raised by the background technology. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides an ecological environment and environmental pollution monitoring system to solve the problems that the environmental monitoring methods in the prior art often rely on manual sampling and laboratory analysis, which is not only time-consuming and labor-intensive, but also difficult to achieve large-scale, real-time, and high-precision monitoring; and the processing and analysis of environmental data lack intelligence, making it difficult to quickly respond to environmental pollution incidents and effectively prevent and control the spread of pollution.

[0006] A monitoring system for ecological environment and environmental pollution, comprising:

[0007] Multifunctional sensor arrays are deployed in the monitoring area to collect multi-dimensional environmental parameters of air, water quality, soil and biodiversity in real time;

[0008] Intelligent analysis platform, which integrates big data analysis algorithms and machine learning models to receive and process data from multifunctional sensor arrays, automatically identify environmental pollution events, predict environmental change trends, and assess ecosystem health;

[0009] The remote monitoring and early warning system is connected to the intelligent analysis platform to issue environmental pollution early warning information in real time based on the analysis results. It also provides a remote control interface, allowing managers to remotely adjust monitoring parameters or activate emergency response mechanisms;

[0010] Adaptive energy management system, which automatically adjusts energy supply, such as solar energy, wind energy and energy storage equipment, according to the energy consumption demand of the monitoring system and local environmental conditions, to ensure long-term stable operation of the system;

[0011] The public participation module releases environmental quality reports to the public through mobile applications or web platforms, collects public feedback, and promotes the improvement of environmental protection awareness and public participation in environmental protection activities.

[0012] Preferably, in the multifunctional sensor array, a data denoising algorithm is introduced into the collected data to improve the accuracy and reliability of the sensor data.

[0013] Preferably, the multifunctional sensor array also includes sensors mounted on micro-drones for regular inspections and data collection in inaccessible or vast areas.

[0014] Preferably, in the intelligent analysis platform, a time series prediction algorithm is introduced for predicting environmental change trends.

[0015] Preferably, the intelligent analysis platform further includes an artificial intelligence recognition module, which can learn and identify the characteristic patterns of specific pollution sources based on historical data, thereby improving the accuracy and speed of pollution event identification. The artificial intelligence recognition module introduces a feature extraction algorithm to extract key features from multidimensional data and identify the characteristic patterns of specific pollution sources.

[0016] Preferably, the remote monitoring and early warning system also includes geographic information system (GIS) integration, which can intuitively display the distribution and diffusion of pollution on a map to provide support for decision-making, that is, by introducing a spatial interpolation algorithm to display the distribution and diffusion of pollution on a map.

[0017] Preferably, the adaptive energy management system also has an energy recovery mechanism, including: utilizing waste heat or light changes during the environmental monitoring process to supplement energy for the system.

[0018] A processor is configured to execute the above-mentioned ecological environment and environmental pollution monitoring system.

[0019] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned ecological environment and environmental pollution monitoring system.

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

[0021] The present invention realizes real-time and high-precision monitoring of multi-dimensional environmental parameters of air, water quality, soil and biodiversity through a multifunctional sensor array, greatly improving the monitoring scope and efficiency; through the big data analysis and machine learning model of the intelligent analysis platform, it can automatically identify environmental pollution events, accurately predict environmental change trends, and timely evaluate the health of the ecosystem, providing strong support for environmental protection; in addition, the real-time warning and remote control functions of the remote monitoring and early warning system enable managers to quickly respond to environmental pollution events and effectively prevent and control the spread of pollution; the adaptive energy management system automatically adjusts the energy supply according to the system energy consumption requirements and local environmental conditions to ensure the long-term stable operation of the system; the introduction of the public participation module further enhances the public's environmental awareness and promotes public participation in environmental protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a framework diagram of the ecological environment and environmental pollution monitoring system of the present invention. DETAILED DESCRIPTION

[0023] The following embodiments of the present invention are described in further detail in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0024] Embodiment: The present invention provides a monitoring system for ecological environment and environmental pollution, such as Figure 1 As shown, including:

[0025] Multifunctional sensor arrays are deployed in the monitoring area to collect multi-dimensional environmental parameters of air, water quality, soil and biodiversity in real time, including but not limited to PM2.5 concentration, harmful gas concentration, water pH, heavy metal content, soil moisture, temperature, and biodiversity index;

[0026] Intelligent analysis platform, which integrates big data analysis algorithms and machine learning models to receive and process data from multifunctional sensor arrays, automatically identify environmental pollution events, predict environmental change trends, and assess ecosystem health;

[0027] The remote monitoring and early warning system is connected to the intelligent analysis platform to issue environmental pollution early warning information in real time based on the analysis results. It also provides a remote control interface, allowing managers to remotely adjust monitoring parameters or activate emergency response mechanisms;

[0028] Adaptive energy management system, which automatically adjusts energy supply, such as solar energy, wind energy and energy storage equipment, according to the energy consumption demand of the monitoring system and local environmental conditions, to ensure long-term stable operation of the system;

[0029] The public participation module releases environmental quality reports to the public through mobile applications or web platforms, collects public feedback, and promotes the improvement of environmental protection awareness and public participation in environmental protection activities.

[0030] Furthermore, the multifunctional sensor array, intelligent analysis platform, remote monitoring and early warning system and adaptive energy management system are electrically connected in sequence.

[0031] From the above, we can see that the system realizes real-time and high-precision monitoring of multi-dimensional environmental parameters, automatic identification and early warning of environmental pollution events, accurate prediction of environmental change trends, timely assessment of ecosystem health, automatic adjustment of energy supply and promotion of public participation in environmental protection activities by integrating multi-functional sensor arrays, intelligent analysis platforms, remote monitoring and early warning systems, adaptive energy management systems and public participation modules. It not only significantly improves the efficiency and accuracy of ecological environment monitoring, but also effectively supports the formulation and implementation of environmental protection decisions, while enhancing the public's environmental awareness and promoting public participation in environmental protection.

[0032] Furthermore, in the multifunctional sensor array, a data denoising algorithm is introduced into the collected data to improve the accuracy and reliability of the sensor data. The formula of the data denoising algorithm is as follows:

[0033]

[0034] Among them, f(t) is the original signal, ψ(t) is the wavelet function, a is the scale factor, and b is the translation factor.

[0035] From the above, it can be seen that by using wavelet function to transform the original signal, the noise interference in the sensor data is effectively removed, and the accuracy and reliability of the data are significantly improved; the application of this data denoising algorithm further enhances the monitoring system's ability to accurately perceive multi-dimensional environmental parameters, and provides more reliable data support for subsequent environmental data analysis and pollution warning.

[0036] Furthermore, the multifunctional sensor array also includes sensors mounted on micro-drones for regular inspections and data collection in inaccessible or vast areas.

[0037] From the above, it can be seen that the added micro-UAV-mounted sensors in the multifunctional sensor array can conduct efficient and flexible regular inspections and data collection in inaccessible or vast areas, thereby greatly expanding the coverage and monitoring capabilities of the monitoring system; the application of the micro-UAV-mounted sensors not only improves the efficiency and accuracy of complex environmental monitoring, but also provides strong support for a comprehensive and detailed grasp of environmental quality conditions, which helps to promptly discover and resolve potential environmental pollution problems.

[0038] Furthermore, in the intelligent analysis platform, a time series prediction algorithm is introduced to predict the trend of environmental changes. The formula of the time series prediction algorithm is as follows:

[0039]

[0040] Among them, Y t is the value at the current time point, φ i and θ j is the model parameter, ∈ t It's white noise.

[0041] From the above, we can see that by using historical environmental data to establish a prediction model, we can accurately predict future environmental change trends and provide a scientific basis for environmental protection decision-making; it not only improves the foresight and pertinence of environmental monitoring, but also helps to formulate response measures in advance, effectively prevent and control the occurrence of environmental pollution problems, which is of great significance to protecting the ecological environment and promoting sustainable development.

[0042] Furthermore, the intelligent analysis platform further includes an artificial intelligence recognition module, which can learn and identify the characteristic patterns of specific pollution sources based on historical data to improve the accuracy and speed of pollution event identification. The artificial intelligence recognition module introduces a feature extraction algorithm to extract key features from multidimensional data and identify the characteristic patterns of specific pollution sources. The formula of the feature extraction algorithm is as follows:

[0043]

[0044] Among them, K(x,x i ) is the kernel function, α i is the Lagrange multiplier, y i is the label and b is the bias term.

[0045] From the above, we can see that the introduction of artificial intelligence recognition module and its feature extraction algorithm in the intelligent analysis platform can significantly improve the accuracy and speed of pollution event identification; the feature extraction algorithm maps the data to a high-dimensional feature space through the kernel function, and combines Lagrange multipliers and bias terms to extract key features from multidimensional data, thereby effectively identifying the characteristic patterns of specific pollution sources; enabling the monitoring system to locate pollution sources more quickly and accurately, providing strong support for environmental management and pollution control; at the same time, it also enhances the system's adaptive learning ability, and can continuously optimize the recognition model as data accumulates, thereby improving the overall monitoring efficiency.

[0046] Furthermore, the remote monitoring and early warning system also includes geographic information system (GIS) integration, which can intuitively display the pollution distribution and diffusion on the map to provide support for decision-making, that is, by introducing a spatial interpolation algorithm to display the pollution distribution and diffusion on the map. The formula of the spatial interpolation algorithm is as follows:

[0047]

[0048] Among them, Z is the estimated value, Z i is the value of the known point, d i is the distance, and p is the weight exponent.

[0049] From the above, we can see that by introducing the integration of spatial interpolation algorithms and geographic information systems (GIS), the distribution and diffusion of pollution can be displayed intuitively and accurately on the map, providing strong visualization support for environmental protection decision-making; based on the data of known pollution monitoring points, the pollution value of unknown points can be estimated by calculating the distance and weight index, thereby generating a continuous pollution distribution map; it not only helps decision makers quickly grasp the current status of pollution, but also predicts the trend of pollution diffusion and takes effective measures in time to prevent further spread of pollution; it greatly improves the efficiency and response speed of environmental protection work, which is of great significance to maintaining ecological balance and human health.

[0050] Furthermore, the adaptive energy management system also has an energy recovery mechanism, such as using waste heat or light changes during environmental monitoring to supplement energy for the system.

[0051] From the above, we can see that by effectively utilizing waste heat or light changes in the environmental monitoring process to supplement the system's energy, energy recycling and efficient management are achieved; not only does it reduce the system's energy consumption cost, it also reduces dependence on external energy sources and improves overall energy utilization efficiency; specifically, waste heat recovery can convert heat energy that might have been lost into electrical energy or other forms of usable energy, while light changes can be converted into electrical energy through photovoltaic technology, providing continuous and stable power support for the monitoring system. This energy management method is of great significance for promoting the development of green and sustainable environmental monitoring technologies.

[0052] Working principle: The system collects environmental parameters in real time through a multifunctional sensor array, and uses the big data analysis and machine learning models of the intelligent analysis platform to process data to identify pollution events, predict environmental changes and evaluate the health of the ecosystem. It then issues warnings and provides remote control through the remote monitoring and early warning system. At the same time, the adaptive energy management system adjusts energy supply according to demand to ensure stable operation of the system. Finally, the public's environmental awareness and participation are enhanced through the public participation module, realizing all-round, efficient and intelligent ecological environment and environmental pollution monitoring.

[0053] Furthermore, a monitoring system for ecological environment and environmental pollution of this embodiment is compared with a conventional environmental monitoring system (comparative example), and the following table is obtained:

[0054]

[0055]

[0056] It can be seen from the above table that the ecological environment and environmental pollution monitoring system of this embodiment is superior to traditional environmental monitoring systems in terms of data collection, data analysis and prediction, early warning and response, energy management, public participation and system scalability, and can better meet the needs of current environmental protection work.

[0057] A method for monitoring an ecological environment and environmental pollution, using the above-mentioned ecological environment and environmental pollution monitoring system, comprises: first, using a multifunctional sensor array deployed in a monitoring area to collect multi-dimensional environmental parameters of air, water quality, soil and biodiversity in real time; then, transmitting the collected data to an intelligent analysis platform, automatically identifying environmental pollution events through big data analysis algorithms and machine learning models, predicting environmental change trends, and evaluating the health status of the ecosystem; then, based on the analysis results of the intelligent analysis platform, a remote monitoring and early warning system releases environmental pollution early warning information in real time, and provides a remote control interface for managers to adjust monitoring parameters or initiate emergency responses; at the same time, an adaptive energy management system automatically adjusts energy supply according to energy consumption demand and local environmental conditions to ensure long-term stable operation of the system; finally, an environmental quality report is released to the public through a public participation module, public feedback is collected, and environmental protection awareness is enhanced.

[0058] The embodiment of the present application provides an electronic device, which is applicable to the above-mentioned ecological environment and environmental pollution monitoring system, including:

[0059] Memory, used to protect computer programs and data;

[0060] Processor, used to run system programs.

[0061] An embodiment of the present application provides a computer storage medium, which is applicable to the above-mentioned ecological environment and environmental pollution monitoring system, and performs hierarchical confidentiality management on the above-mentioned system and data in accordance with confidentiality management requirements.

[0062] Those skilled in the art will appreciate that the embodiments of the present application may be provided as a system or a computer program product. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0063] The present application is described with reference to the flowcharts and / or block diagrams of the devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0064] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0065] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0066] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0067] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0068] Computer readable media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0069] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, commodity or device including the elements.

[0070] The embodiments of the present invention are provided for the purpose of illustration and description. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present invention. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A monitoring system for ecological environment and environmental pollution, characterized in that: include: Multifunctional sensor arrays are deployed in the monitoring area to collect multi-dimensional environmental parameters of air, water quality, soil and biodiversity in real time, including but not limited to PM2.5 concentration, harmful gas concentration, water pH, heavy metal content, soil moisture, temperature, and biodiversity index; Intelligent analysis platform, which integrates big data analysis algorithms and machine learning models to receive and process data from multifunctional sensor arrays, automatically identify environmental pollution events, predict environmental change trends, and assess ecosystem health; The remote monitoring and early warning system is connected to the intelligent analysis platform to issue environmental pollution early warning information in real time based on the analysis results. It also provides a remote control interface, allowing managers to remotely adjust monitoring parameters or activate emergency response mechanisms; Adaptive energy management system, which automatically adjusts energy supply according to the energy consumption demand of the monitoring system and local environmental conditions, including the use of solar energy, wind energy and energy storage equipment, to ensure long-term stable operation of the system; The public participation module releases environmental quality reports to the public through mobile applications or web platforms, collects public feedback, and promotes the improvement of environmental protection awareness and public participation in environmental protection activities.

2. The ecological environment and environmental pollution monitoring system as claimed in claim 1, characterized in that: In the multifunctional sensor array, a data denoising algorithm is introduced into the collected data to improve the accuracy and reliability of the sensor data.

3. The ecological environment and environmental pollution monitoring system as claimed in claim 1, characterized in that: The multifunctional sensing array also includes sensors mounted on micro-drones for regular inspections and data collection in inaccessible or vast areas.

4. The ecological environment and environmental pollution monitoring system as claimed in claim 1, characterized in that: In the intelligent analysis platform, a time series prediction algorithm is introduced to predict environmental change trends.

5. The ecological environment and environmental pollution monitoring system as claimed in claim 1, characterized in that: The intelligent analysis platform further includes an artificial intelligence recognition module that can learn and identify characteristic patterns of specific pollution sources based on historical data. The artificial intelligence recognition module introduces a feature extraction algorithm to extract key features from multidimensional data and identify characteristic patterns of specific pollution sources.

6. The ecological environment and environmental pollution monitoring system as claimed in claim 1, characterized in that: The remote monitoring and early warning system also includes geographic information system integration, which can visually display the distribution and spread of pollution on a map to provide support for decision-making.

7. The ecological environment and environmental pollution monitoring system as claimed in claim 1, characterized in that: The adaptive energy management system also has an energy recovery mechanism, including: using waste heat or light changes during environmental monitoring to replenish energy for the system.

8. A processor, characterized in that: A system configured to implement an ecological environment and environmental pollution monitoring system according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, an ecological environment and environmental pollution monitoring system as described in any one of claims 1 to 7 is implemented.

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