Big data environmental protection management system and method based on smart park

Abstract

The invention provides a big data environmental protection management system and method based on a smart park, and relates to the technical field of environmental protection management, and the method comprises the steps: collecting air quality parameters, water quality parameters, meteorological parameters and noise levels of all representative places in the park; calculating an environmental health index, a water quality safety index and a noise influence index; each intermediate parameter is compared with a threshold value, and when the parameters exceed the threshold value, corresponding improvement measures are taken; constructing a comprehensive evaluation model according to the environmental health index, the water quality safety index and the noise influence index, generating a weight in the comprehensive evaluation model through an analytic hierarchy process, and generating a comprehensive environmental quality index by using the comprehensive evaluation model; and setting different environment quality grades according to the comprehensive environment quality index, and making corresponding improvement measures according to the grades. According to the systematic management mode, the precision and response speed of park environment monitoring are effectively improved, and the pertinence and effectiveness of environment treatment measures are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental protection management, and specifically provides a big data environmental protection management system and method based on a smart park. Background Art

[0002] With the continuous acceleration of the urbanization process, the construction of smart parks has not only promoted economic development but also exacerbated environmental pollution problems. The decline in air quality, water pollution, and noise interference have increasingly become major challenges faced by urban managers. Existing environmental monitoring technologies mainly collect data through scattered monitoring points. This traditional method often has problems such as limited monitoring range, lagging data update, and lack of real-time feedback. Due to the large differences in environmental parameters at different monitoring points, the reliability of environmental assessment results is reduced. In addition, traditional monitoring systems usually rely on manual data entry and processing, which are prone to human errors, and lack systematicness and scientificity in data analysis, making it impossible to comprehensively evaluate multiple environmental factors.

[0003] At the same time, when dealing with environmental data, existing technologies often lack effective correlation analysis methods, resulting in the inability to timely evaluate and control the impact of pollution sources. Existing monitoring systems respond slowly to sudden environmental pollution events and lack dynamic monitoring and early warning functions, making it difficult to implement environmental governance measures in a timely and effective manner. In addition, the mutual influence and relationship between environmental indicators have not been fully explored, resulting in the formulation of environmental management measures being often one-sided and partial. The comprehensive evaluation model considering various environmental factors such as air quality, water quality, and noise is not yet mature, which brings difficulties to scientific and reasonable environmental management. Therefore, there is an urgent need for an efficient, comprehensive, and real-time big data environmental protection management system to solve the deficiencies in current environmental monitoring and management.

[0004] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present disclosure, and therefore it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] The purpose of the present invention is to provide a big data environmental protection management system and method based on a smart park to solve the problems raised in the above background art.

[0006] To achieve the above purpose, the present invention provides a big data environmental protection management system based on a smart park, specifically including:

[0007] A data acquisition module for conducting on-site surveys within the park to collect air quality parameters, water quality parameters, meteorological parameters, and noise levels in the park; the air quality parameters include PM2.5 concentration, carbon dioxide concentration, and nitrogen dioxide concentration, the water quality parameters are water body pH value, turbidity index, and dissolved oxygen concentration, and the meteorological parameters are the atmospheric temperature, humidity, and wind speed of the park;

[0008] An index calculation module for generating an environmental health index based on the dimensionless PM2.5 concentration, CO 2 concentration, and NO 2 concentration, generating a water quality safety index based on the dimensionless water body pH value, turbidity index, and dissolved oxygen concentration, generating a noise impact index based on the dimensionless noise level, and comparing each intermediate parameter with a threshold value. When the intermediate parameter exceeds the threshold value, corresponding improvement measures are implemented. The intermediate parameters are the environmental health index, water quality safety index, and noise impact index;

[0009] A correlation analysis module for constructing a comprehensive evaluation model based on the environmental health index, water quality safety index, and noise impact index to generate a comprehensive environmental quality index;

[0010] A data analysis module for setting different environmental quality grades based on the comprehensive environmental quality index and formulating corresponding improvement measures according to the grades.

[0011] Furthermore, the logic for collecting air quality parameters, water quality parameters, meteorological parameters, and noise levels in the park is as follows:

[0012] Select multiple representative locations within the park, collect air quality parameters, water quality parameters, meteorological parameters, and noise levels at each representative location, and use their mean values as the air quality parameters, water quality parameters, meteorological parameters, and noise levels in the park;

[0013] The representative locations are commercial areas, parks, residential areas, schools and educational institutions, and transportation hubs existing in the park;

[0014] Use sensors to measure the turbidity values of water samples at each representative location in the park, and calculate the turbidity index of the representative location according to the following formula:

[0015]

[0016] where TI is the turbidity index of the representative location, Tur is the turbidity value of the water sample at the representative location, and Tur max is the maximum turbidity threshold of the water area at the representative location, which is determined based on historical data and regulatory standards;

[0017] Measure the sound pressure at each representative location in the park using a noise monitor, and calculate the noise level of the representative location according to the following formula:

[0018]

[0019] where Noi is the noise level of the representative location, P is the sound pressure measured at the representative location, and P 0 is the reference sound pressure, with a value of 20 μPa;

[0020] Use sensors to collect the PM2.5 concentration, carbon dioxide concentration, nitrogen dioxide concentration, water body pH value, dissolved oxygen concentration, atmospheric temperature, humidity, and wind speed at each representative location in the park;

[0021] Record the PM2.5 concentration in the park as C PM2.5 , the carbon dioxide concentration as the nitrogen dioxide concentration as the atmospheric temperature as T, the humidity as S, the wind speed as V, the turbidity index as TI, the water body pH value as pH, the dissolved oxygen concentration as DO, and the noise level as Noi.

[0022] Furthermore, calculate the environmental health index according to the following formula:

[0023]

[0024] where EHI is the environmental health index of the park to be managed, C PM2.5 is the PM2.5 concentration, is the carbon dioxide concentration, is the nitrogen dioxide concentration, PM2.5 ref , are the health thresholds of PM2.5 and CO 2 and NO 2 respectively, set according to national or international standards, and α, β, and γ are preset proportionality coefficients, and α > γ > β > 0;

[0025] Calculate the water quality safety index according to the following formula:

[0026]

[0027] where WSI is the water quality safety index, e is the natural constant, pH is the pH value of the water body in the park, TI is the turbidity index of the water body, and DO is the dissolved oxygen concentration; pH ref , DO ref are the health thresholds of the water body pH value and the water body dissolved oxygen concentration respectively, set according to national or international standards, and σ, δ, and τ are preset proportionality coefficients, and σ > τ > δ > 0;

[0028] The formula for calculating the noise impact index is as follows:

[0029]

[0030] Where NII is the noise impact index, Noi is the noise level, e is the natural constant, is the sensitivity coefficient of the noise impact, and

[0031] Furthermore, each intermediate parameter is compared with the threshold value. The intermediate parameters are the environmental health index, the water quality safety index, and the noise impact index;

[0032] If EHI < EY, it indicates that the current environmental health index of the park is less than the health threshold value. Air quality monitoring should be strengthened, industrial emissions should be reduced, and the greening area should be increased;

[0033] If WSI < WY, it indicates that the current water quality safety index of the park is less than the health threshold value. The water body monitoring frequency should be increased, water quality purifying agents should be put in, and water body treatment should be carried out;

[0034] If NII > NY, it indicates that the current noise impact index of the park exceeds the health threshold value. Noise sources should be restricted, sound insulation facilities should be increased, and traffic flow lines should be adjusted;

[0035] Where EHI is the environmental health index, WSI is the water quality safety index, NII is the noise impact index, and EY, WY, and NY are the environmental health threshold value, the water quality health threshold value, and the noise health threshold value respectively.

[0036] Furthermore, a comprehensive evaluation model is constructed based on the environmental health index, the water quality safety index, and the noise impact index. The model expression is as follows:

[0037]

[0038] Where CEQI is the comprehensive environmental quality index, EHI is the environmental health index, WSI is the water quality safety index, NII is the noise impact index, ω 1 、ω 2 and ω 3 are proportionality coefficients, and their values are determined according to the analytic hierarchy process.

[0039] Furthermore, the specific logic for determining the proportionality coefficients by the analytic hierarchy process is as follows:

[0040] Mark the three indicators of the environmental health index, water quality safety index, and noise impact index, determine the relative importance values between each pair through the nine-scale method, and construct a judgment matrix. Among them, mark the index of the environmental health index as 1, the index of the water quality safety index as 2, and the index of the noise impact index as 3. The constructed judgment matrix is:

[0041]

[0042] Among them, both f and v represent the indexes of the index, and f ∈ [1, 3], v ∈ [1, 3], b fv represents the importance degree of the index with index f relative to the index with index v. The importance degree adopts the 1-9 scale method, and b fv The larger the value, the greater the importance degree of the index with index f compared to the index with index v, and b ff = 1,

[0043] Divide each element value in the judgment matrix by the sum of its column to obtain the normalized judgment matrix. Calculate the mean value of each row element value in the normalized judgment matrix, take the mean value of the first row element value as the weight of the environmental health index, take the mean value of the second row element value as the weight of the water quality safety index, and take the mean value of the third row element value as the weight of the noise impact index. With the constraint that the sum of the scaled values is equal to 1, scale the three weights proportionally, and take the scaled weights as the proportional coefficients of the corresponding indexes.

[0044] Furthermore, set different environmental quality grades according to the comprehensive environmental quality index. The specific logic is as follows:

[0045] When CEQI ≤ 0.5CY, it is judged that the environmental condition of the current park to be managed is poor, immediately strengthen monitoring, evaluate pollution sources, and take control measures;

[0046] When 0.5CY < CEQI ≤ CY, it is judged that the environmental condition of the current park to be managed is average, increase the monitoring frequency, implement an environmental improvement plan, and reduce pollutant emissions;

[0047] When CEQI > CY, it is judged that the environmental condition of the current park to be managed is good, continue to maintain the existing monitoring and management measures to ensure the stability of environmental quality;

[0048] Among them, CEQI is the comprehensive environmental quality index, and CY is the preset evaluation threshold.

[0049] The present invention also further provides a big data environmental protection management method based on a smart park. The big data environmental protection management method based on a smart park is obtained by executing the above-mentioned big data environmental protection management system based on a smart park, and includes:

[0050] Step 1: Conduct on-site surveys within the park to collect air quality parameters, water quality parameters, meteorological parameters, and noise levels at various representative locations in the park; the air quality parameters include PM2.5 concentration, carbon dioxide concentration, and nitrogen dioxide concentration, the water quality parameters are water body pH value, turbidity index, and dissolved oxygen concentration, and the meteorological parameters are the atmospheric temperature, humidity, and wind speed of the park;

[0051] Step 2: Generate an environmental health index based on the dimensionless PM2.5 concentration, CO 2 concentration, and NO 2 concentration, generate a water quality safety index based on the dimensionless water body pH value, turbidity index, and dissolved oxygen concentration, and generate a noise impact index based on the dimensionless noise level; and compare each intermediate parameter with the threshold value, and implement corresponding improvement measures when the parameter exceeds the threshold value;

[0052] Step 3: Construct a comprehensive evaluation model based on the environmental health index, water quality safety index, and noise impact index, generate the weights within the comprehensive evaluation model through the analytic hierarchy process, and generate a comprehensive environmental quality index using the comprehensive evaluation model;

[0053] Step 4: Set different environmental quality grades according to the comprehensive environmental quality index, and formulate corresponding improvement measures according to the grades.

[0054] Compared with the prior art, the beneficial effects of the present invention are:

[0055] By establishing an environmental protection management system based on big data, this solution can comprehensively and real-time monitor and analyze various environmental parameters in the smart park, thereby providing a scientific basis to support environmental management decisions. This system can not only timely detect environmental quality problems, but also generate an environmental health index, a water quality safety index, and a noise impact index through the comprehensive evaluation model, providing a quantitative basis for environmental protection. This systematic management method effectively improves the accuracy and response speed of park environmental monitoring, ensuring the pertinence and effectiveness of environmental governance measures. In addition, through the dynamic assessment and grading of the comprehensive environmental quality index, park managers can quickly identify environmental risks and take corresponding improvement measures, thereby promoting the sustainable development of the park. Compared with traditional monitoring means, this system realizes the intelligentization and automation of data collection and processing, greatly improving the efficiency and scientific nature of environmental management, and making important contributions to improving the quality of residents' lives and protecting the ecological environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a schematic diagram of the system module of the present invention;

[0057] Figure 2This is a schematic diagram of the overall method flow of the present invention. Detailed implementation mode

[0058] To make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below in conjunction with specific embodiments.

[0059] It should be noted that unless otherwise defined, the technical terms or scientific terms used in the present invention should have the ordinary meanings understood by those with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar terms used in the present invention do not represent any order, quantity or importance, but are only used to distinguish different components. The terms such as "including" or "comprising" mean that the elements or objects appearing before this term cover the elements or objects listed after this term and their equivalents, without excluding other elements or objects. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative position relationships, and when the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0060] Embodiment:

[0061] Please refer to Figure 1 , the present invention provides a big data environmental protection management system based on an intelligent park, specifically including:

[0062] A data acquisition module, configured to perform on-site surveys in the park and collect air quality parameters, water quality parameters, meteorological parameters and noise levels at various representative locations in the park; the air quality parameters include PM2.5 concentration, carbon dioxide concentration and nitrogen dioxide concentration, the water quality parameters are the pH value of the water body, turbidity index and dissolved oxygen concentration, and the meteorological parameters are the atmospheric temperature, humidity and wind speed of the park;

[0063] In this embodiment,

[0064] The logic for collecting air quality parameters, water quality parameters, meteorological parameters and noise levels in the park is as follows:

[0065] Select multiple representative locations in the park, collect the air quality parameters, water quality parameters, meteorological parameters and noise levels at each representative location, and use their average values as the air quality parameters, water quality parameters, meteorological parameters and noise levels in the park;

[0066] The representative locations are commercial areas, parks, residential areas, schools and educational institutions, and transportation hubs existing in the park;

[0067] Use sensors to measure the turbidity values of water samples at representative locations in the park, and calculate the turbidity index of the representative location according to the following formula:

[0068]

[0069] where TI is the turbidity index of the representative location, Tur is the turbidity value of the water sample at the representative location, and Tur max is the maximum turbidity threshold of the water area at the representative location, which is determined according to historical data and regulatory standards;

[0070] Use a noise monitor to measure the sound pressure at representative locations in the park, and calculate the noise level of the representative location according to the following formula:

[0071]

[0072] where Noi is the noise level of the representative location, P is the sound pressure measured at the representative location, and P 0 is the reference sound pressure, with a value of 20 μPa;

[0073] Use sensors to collect the PM2.5 concentration, carbon dioxide concentration, nitrogen dioxide concentration, water body pH value, dissolved oxygen concentration, atmospheric temperature, humidity, and wind speed at each representative location in the park;

[0074] Record the PM2.5 concentration of the park as C PM2.5 and the carbon dioxide concentration as and the nitrogen dioxide concentration as Record the atmospheric temperature as T, the humidity as S, the wind speed as V, the turbidity index as TI, the water body pH value as pH, the dissolved oxygen concentration as DO, and the noise level as Noi.

[0075] The advantage of the data acquisition module lies in its efficient and accurate environmental parameter monitoring ability. By deploying high-precision sensors at multiple representative locations in the park to collect air quality, water quality, meteorological, and noise data in real time, it not only ensures the comprehensiveness and reliability of the data but also can timely reflect environmental changes. This multi-dimensional monitoring method significantly improves the flexibility and response speed of environmental monitoring compared with traditional single monitoring points or regular detections, providing a more solid foundation for subsequent data analysis and decision-making.

[0076] Compared with the existing technology, the beneficial effects of this module are reflected in its comprehensiveness and real-time nature. Traditional technologies often rely on manual sampling and offline analysis, which is not only time-consuming but also unable to reflect sudden environmental pollution situations in a timely manner. However, this patented solution can achieve real-time monitoring and immediate warning through automated data collection, providing park managers with a fast and reliable basis for decision-making, thereby effectively reducing environmental risks and improving environmental management levels. In this patented solution, the implementation of the data collection module provides key support for the successful operation of the overall solution. It not only lays the foundation for data analysis and index calculation, but also enhances the accuracy and scientificity of the comprehensive evaluation model through the integration of multi-dimensional data, enabling the park to implement corresponding measures more efficiently and accurately in terms of environmental governance and sustainable development, and ultimately improve the overall environmental quality of the park and the quality of life of residents.

[0077] Index calculation module, used to calculate PM2.5 concentration and CO 2 Concentration and NO 2 The environmental health index is generated based on the concentration, the water quality safety index is generated based on the dimensionless water pH value, turbidity index and dissolved oxygen concentration, and the noise impact index is generated based on the dimensionless noise level; and each intermediate parameter is compared with the threshold value. When the parameter exceeds the threshold value, the corresponding improvement measures are implemented;

[0078] In this embodiment, the environmental health index is calculated based on the following formula:

[0079]

[0080] Among them, EHI is the environmental health index of the park to be managed, C PM2.5 is the PM2.5 concentration, is the carbon dioxide concentration, is the concentration of nitrogen dioxide, PM2.5 ref , PM2.5, CO 2 and NO 2 The health threshold is set according to national or international standards, with α, β and γ as preset proportional coefficients, and α>γ>β>0. This is because PM2.5 particles can penetrate deep into the lungs and even enter the blood due to their tiny particle size, causing significant effects on the respiratory and cardiovascular systems. Therefore, they are given the highest weight in the EH calculation, reflecting the strong concern and attention paid to PM2.5. Nitrogen dioxide, as a major air pollutant, has a slightly weaker impact on health than PM2.5, although it can also cause respiratory irritation and other health problems. Although carbon dioxide is important in environmental monitoring, its short-term health impact is relatively low, so its weight is set to the minimum.

[0081] When CPM2.5 When it increases, it means that the PM2.5 concentration in the park increases, the pollution level increases, and the air quality deteriorates, so the EHI will decrease; when When it increases, it means that the CO 2 The concentration increases, high concentration of CO 2 The EHI may be reduced due to the oxygen content in the air, especially in closed or poorly ventilated environments, which may lead to breathing problems and other health problems. When it increases, it means that NO 2 The concentration increases, high concentration of NO 2 It will damage the respiratory system and increase the risk of asthma and other respiratory diseases, so EHI will decrease; that is, C PM2.5 , It is negatively correlated with the environmental health index (EHI).

[0082] The water quality safety index is calculated based on the following formula:

[0083]

[0084] Among them, WSI is the water safety index, e is the natural constant, pH is the pH value of the water in the park, TI is the turbidity index of the water, DO is the dissolved oxygen concentration; pH ref ,DO ref They are the healthy thresholds of water pH and dissolved oxygen concentration, respectively, which are set according to national or international standards. σ, δ and τ are preset proportional coefficients, and σ>τ>δ>0. This is because pH is an important indicator of the chemical properties of water and determines the conduct of various chemical reactions in water. Many aquatic organisms are very sensitive to changes in pH, and a suitable pH range is essential for their growth and survival, so it is given the highest weight. Although the turbidity index is important, its direct impact on water quality is slightly weaker than that of pH and dissolved oxygen, so it is given a relatively low weight.

[0085] When | pH-pH ref | increases, which means that the gap between the pH value of the water body and the reference pH value increases. Too high or too low pH values ​​may cause stress response, reproductive disorders or even death of aquatic organisms, so WSI will decrease accordingly. ref | increases, which means that the gap between the dissolved oxygen concentration value and the reference dissolved oxygen value increases. Insufficient or excessive dissolved oxygen will destroy the ecological balance of the water body, so WSI will decrease accordingly; when TI increases, it will reduce the light transmittance of the water body, thereby affecting the photosynthesis of underwater plants. The reduction of photosynthesis will cause the growth of aquatic plants to slow down or even die, thus affecting the balance of the entire ecosystem, and WSI will decrease accordingly; that is, |pH-pHref |, DO-DO ref |, TI is negatively correlated with WSI.

[0086] The formula for calculating the noise impact index is as follows:

[0087]

[0088] Where NII is the noise impact index, Noi is the noise level, e is the natural constant, is the sensitivity coefficient of the noise impact, and A high noise level may affect the ecological environment in the park, interfere with animal activities and plant growth, reduce biodiversity, and have a negative impact on the staff and the surrounding environment. Therefore, when Noi increases, the noise impact index NII will also increase; that is, it shows that Noi and NII are positively correlated.

[0089] Compare each intermediate parameter with the threshold value. The intermediate parameters are the environmental health index, the water quality safety index, and the noise impact index;

[0090] If EHI < EY, it means that the current environmental health index of the park is less than the health threshold value, and air quality monitoring should be strengthened, industrial emissions should be reduced, and the greening area should be increased;

[0091] If WSI < WY, it means that the current water quality safety index of the park is less than the health threshold value, and the water body monitoring frequency should be increased, water quality purifying agents should be put in, and water body treatment should be carried out;

[0092] If NII > NY, it means that the current noise impact index of the park exceeds the health threshold value, and the noise source should be restricted, sound insulation facilities should be increased, and the traffic flow line should be adjusted;

[0093] Where EHI is the environmental health index, WSI is the water quality safety index, NII is the noise impact index, and EY, WY, and NY are the environmental health threshold value, the water quality health threshold value, and the noise health threshold value respectively, and their specific values are determined according to relevant regulations and historical monitoring data.

[0094] The advantage of the index calculation module is that it can convert complex environmental data into environmental health index, water quality safety index, and noise impact index that are easy to understand and apply through dimensionless processing. This quantitative method enables park managers to quickly identify and evaluate the environmental situation, which helps to formulate scientific treatment measures and management strategies. Compared with traditional single-parameter monitoring, the index calculation module provides a multi-dimensional comprehensive evaluation, enhancing the accuracy and scientific nature of decision-making.

[0095] Compared with the prior art, the beneficial effects of this module are reflected in its systematicness and efficiency. Traditional environmental management often relies on isolated indicators and lacks a global perspective, leading to one-sided or even incorrect environmental governance measures. In contrast, the patent solution generates a comprehensive index by integrating multiple environmental indicators and applying advanced calculation methods. This not only improves the comparability of data but also enables park managers to conduct cross-indicator analysis and comparison within the same framework, thus more effectively addressing environmental challenges. In the patent solution, the implementation of the index calculation module provides crucial support for the effectiveness of the overall solution. By accurately generating various indexes, managers can make timely responses and adjustments based on real-time data, optimize environmental governance strategies, and enhance the sustainable development ability of the park. The introduction of this module makes the entire environmental management system more intelligent and lays a solid foundation for achieving higher environmental quality standards.

[0096] A correlation analysis module, which is used to construct a comprehensive evaluation model based on the environmental health index, water quality safety index, and noise impact index, generate weights within the comprehensive evaluation model through the analytic hierarchy process, and generate a comprehensive environmental quality index using the comprehensive evaluation model;

[0097] In this embodiment, a comprehensive evaluation model is constructed based on the environmental health index, water quality safety index, and noise impact index, and the model expression is as follows:

[0098]

[0099] where CEQI is the comprehensive environmental quality index, EHI is the environmental health index, WSI is the water quality safety index, NII is the noise impact index, and ω 1 、ω 2 and ω 3 are proportionality coefficients, and their values are determined according to the analytic hierarchy process.

[0100] The larger the value of CEQI, the better the comprehensive environmental quality, and factors such as environmental health status, ecological safety, and water quality are relatively ideal; EHI represents the degree of impact of the environment on human health, and a high value of EHI indicates a relatively good environmental health status. Therefore, when EHI increases, CEQI increases; WSI reflects the safety and suitability of water bodies, usually considering indicators such as pollutants and nutrients in the water. A high value of WSI means better water quality in the park. Therefore, when WSI increases, CEQI increases; NII represents the degree of impact of noise on the environment and the population. The greater the noise, the higher the value of NII. Therefore, when NII increases, CEQI will decrease; that is to say, EHI and WSI are positively correlated with CEQI, and NII is negatively correlated with CEQI.

[0101] The specific logic for determining the proportionality coefficient through the analytic hierarchy process is as follows:

[0102] Mark the three indicators of environmental health index, water quality safety index and noise impact index, determine the relative importance values between each pair through the nine-scale method, and construct a judgment matrix. Among them, mark the index of the environmental health index as 1, the index of the water quality safety index as 2, and the index of the noise impact index as 3. The constructed judgment matrix is:

[0103]

[0104] Among them, both f and v represent the indices of the indices, and f ∈ [1, 3], v ∈ [1, 3], b fv represents the importance degree of the index with index f relative to the index with index v. The importance degree adopts the 1-9 scale method, and b fv The larger the value, the greater the importance degree of the index with index f compared to the index with index v, and b ff = 1,

[0105] Divide each element value in the judgment matrix by the sum of its column to obtain the normalized judgment matrix. Calculate the mean value of each row element value in the normalized judgment matrix, take the mean value of the first row element value as the weight of the environmental health index, take the mean value of the second row element value as the weight of the water quality safety index, and take the mean value of the third row element value as the weight of the noise impact index. With the constraint that the sum of the scaled values is equal to 1, scale the three weights proportionally, and take the scaled weights as the proportional coefficients of the corresponding indices.

[0106] The advantage of the correlation analysis module is that it can systematically integrate and analyze the relationships between the environmental health index, water quality safety index and noise impact index to construct a comprehensive evaluation model. Through the analytic hierarchy process, the module not only assigns reasonable weights to each indicator, but also ensures the scientificity and accuracy of the evaluation results. This comprehensive analysis method enables managers to more comprehensively understand the environmental conditions of the park, thereby formulating more targeted governance strategies.

[0107] Compared with the prior art, the beneficial effects of this module are reflected in its comprehensiveness and forward-looking nature. Traditional technologies usually rely on single indicators for evaluation, which easily leads to one-sided decision-making. In contrast, the patent solution comprehensively considers multiple environmental indicators and uses data analysis methods to make the decision-making process more scientific. It can effectively identify and address potential environmental problems, avoiding governance blind spots caused by information silos. In the patent solution, the implementation of the correlation analysis module significantly promotes the overall solution. By providing multi-dimensional environmental quality assessments, it enables park managers to monitor and adjust environmental management measures in real time, enhancing the flexibility and effectiveness of management. This not only helps improve the environmental situation in the short term but also lays a scientific foundation for the sustainable development of the park, thereby improving the quality of life of residents and the overall level of environmental protection.

[0108] A data analysis module, which is used to set different environmental quality grades according to the comprehensive environmental quality index and formulate corresponding improvement measures according to the grades;

[0109] In this embodiment, the specific logic for setting different environmental quality grades according to the comprehensive environmental quality index is as follows:

[0110] When CEQI ≤ 0.5CY, it is determined that the environmental situation of the park to be managed currently is poor, and monitoring is immediately strengthened, pollution sources are evaluated, and control measures are taken;

[0111] When 0.5CY < CEQI ≤ CY, it is determined that the environmental situation of the park to be managed currently is average, the monitoring frequency is increased, an environmental improvement plan is implemented, and pollutant emissions are reduced;

[0112] When CEQI > CY, it is determined that the environmental situation of the park to be managed currently is good, and the existing monitoring and management measures are continued to ensure the stability of environmental quality;

[0113] Among them, CEQI is the comprehensive environmental quality index, and CY is the preset evaluation threshold.

[0114] The advantage of the data analysis module is that it can systematically evaluate the environmental quality of the park based on the comprehensive environmental quality index and formulate corresponding improvement measures according to different environmental quality grades. By converting complex environmental data into simple and understandable quality grades, this module enables managers to intuitively understand the environmental situation of the park, make decisions quickly, and thus improve the efficiency and scientific nature of management.

[0115] Compared with the prior art, the beneficial effects of this module are reflected in its dynamic monitoring and real-time feedback mechanism. Traditional environmental protection management systems usually rely on static data and periodic evaluations, lacking a sensitive response to environmental changes. However, the patent solution can timely identify environmental problems and make adjustments through real-time data analysis, ensuring the timeliness and effectiveness of management measures, thereby improving the overall environmental governance level of the park. In the patent solution, the implementation of the data analysis module plays an important promoting role in the overall solution. It not only provides the park managers with a clear environmental quality grade but also can guide them to formulate targeted improvement plans, enhancing the systematicness and scientific nature of environmental management. In addition, through continuous monitoring and adjustment, the sustainable development ability of the park is enhanced, thus creating a better living environment for residents.

[0116] Please refer to Figure 2 , a big data environmental protection management method based on an intelligent park, specifically including:

[0117] Step 1: Conduct on-site surveys within the park to collect air quality parameters, water quality parameters, meteorological parameters, and noise levels at representative locations within the park; the air quality parameters include PM2.5 concentration, carbon dioxide concentration, and nitrogen dioxide concentration, the water quality parameters are the pH value of the water body, turbidity index, and dissolved oxygen concentration, and the meteorological parameters are the atmospheric temperature, humidity, and wind speed of the park;

[0118] Step 2: Generate an environmental health index based on the dimensionless PM2.5 concentration, CO 2 concentration, and NO 2 concentration, generate a water quality safety index based on the dimensionless pH value of the water body, turbidity index, and dissolved oxygen concentration, and generate a noise impact index based on the dimensionless noise level; and compare each intermediate parameter with the threshold value, and implement corresponding improvement measures when the parameter exceeds the threshold value;

[0119] Step 3: Construct a comprehensive evaluation model based on the environmental health index, water quality safety index, and noise impact index, generate the weights within the comprehensive evaluation model through the analytic hierarchy process, and use the comprehensive evaluation model to generate a comprehensive environmental quality index;

[0120] Step 4: Set different environmental quality grades according to the comprehensive environmental quality index, and formulate corresponding improvement measures according to the grades.

[0121] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the real situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0122] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0123] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0124] As described above, the specific implementation manners of the present application are only described, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present application, and all of them should be covered by the protection scope of the present application.

Claims

1. A big data environmental management system based on a smart park, characterized in that: Specifically include: A data acquisition module is used to conduct on-site surveys in the park and collect air quality parameters, water quality parameters, meteorological parameters and noise levels in the park; the air quality parameters include PM2.5 concentration, carbon dioxide concentration and nitrogen dioxide concentration, the water quality parameters include water pH value, turbidity index and dissolved oxygen concentration, and the meteorological parameters include atmospheric temperature, humidity and wind speed in the park; An index calculation module is used to generate an environmental health index according to the PM2.5 concentration, CO2 concentration and NO2 concentration after dimensionless processing, generate a water quality safety index according to the pH value, turbidity index and dissolved oxygen concentration of the water body after dimensionless processing, generate a noise impact index according to the noise level after dimensionless processing, and compare each intermediate parameter with a threshold value. When the intermediate parameter exceeds the threshold value, implement corresponding improvement measures. The intermediate parameters are the environmental health index, the water quality safety index and the noise impact index; Correlation analysis module, used to construct a comprehensive evaluation model based on environmental health index, water quality safety index and noise impact index to generate a comprehensive environmental quality index; The data analysis module is used to set different environmental quality levels according to the comprehensive environmental quality index and formulate corresponding improvement measures according to the levels.

2. According to the big data environmental management system based on smart park according to claim 1, it is characterized by: The logic for collecting air quality parameters, water quality parameters, meteorological parameters and noise levels in the park is: Select multiple representative locations in the park, collect the air quality parameters, water quality parameters, meteorological parameters and noise levels at each representative location, and use their average values ​​as the air quality parameters, water quality parameters, meteorological parameters and noise levels in the park; The representative locations are commercial areas, parks, residential areas, schools and educational institutions, and transportation hubs in the park; Use sensors to measure the turbidity values ​​of water samples at each representative location in the park, and calculate the turbidity index of the representative location according to the following formula: Among them, TI is the turbidity index of the representative location, Tur is the turbidity value of the water sample at the representative location, and Tur max is the maximum turbidity threshold for waters at representative locations, determined based on historical data and regulatory standards; Use a noise monitor to measure the sound pressure at each representative location in the park, and calculate the noise level at the representative location according to the following formula: Where Noi is the noise level at a representative location, P is the sound pressure measured at a representative location, and P0 is the reference sound pressure, which is 20 μμPa; Use sensors to collect PM2.5 concentration, carbon dioxide concentration, nitrogen dioxide concentration, water pH, dissolved oxygen concentration, atmospheric temperature, humidity and wind speed at various representative locations in the park; The PM2.5 concentration in the park is recorded as C PM2.5 , the carbon dioxide concentration is recorded as The concentration of nitrogen dioxide is recorded as The atmospheric temperature is denoted as T, the humidity is denoted as S, the wind speed is denoted as V, the turbidity index is denoted as TI, the pH value of the water body is denoted as pH, the dissolved oxygen concentration is denoted as DO, and the noise level is denoted as Noi.

3. According to the big data environmental management system based on smart park according to claim 2, it is characterized by: The environmental health index is calculated based on the following formula: Among them, EHI is the environmental health index of the park to be managed, C PM2.5 is the PM2.5 concentration, is the carbon dioxide concentration, is the concentration of nitrogen dioxide, PM2.5 ref , The health thresholds for PM2.5, CO2 and NO2 are set according to national or international standards, α, β and γ are preset proportional coefficients, and α>γ>β>0; The water quality safety index is calculated based on the following formula: Among them, WSI is the water safety index, e is the natural constant, pH is the pH value of the water in the park, T is the turbidity index of the water, DO is the dissolved oxygen concentration; pH ref ,DO ref They are the healthy thresholds of water pH value and water dissolved oxygen concentration, respectively, which are set according to national or international standards. σ, δ and τ are preset proportional coefficients, and σ>τ>δ>0; The noise impact index is calculated based on the following formula: Among them, NII is the noise impact index, Noi is the noise level, e is a natural constant, is the sensitivity coefficient of noise influence, and 4. According to the big data environmental management system based on smart park according to claim 1, it is characterized by: Comparing each intermediate parameter with a threshold value, wherein the intermediate parameters are an environmental health index, a water quality safety index, and a noise impact index; If EHI < EY, it means that the current environmental health index of the park is less than the health threshold, and air quality monitoring should be strengthened, industrial emissions should be reduced, and green areas should be increased; If WSI < WY, it means that the current water quality safety index of the park is less than the health threshold, and the frequency of water body monitoring should be increased, water purifiers should be added, and water body treatment should be carried out; If NII>NY, it means that the current noise impact index of the park exceeds the health threshold, and the noise source should be restricted, sound insulation facilities should be added, and traffic flow lines should be adjusted; Among them, EHI is the environmental health index, WSI is the water quality safety index, NII is the noise impact index, EY, WY, and NY are the environmental health threshold, water quality health threshold, and noise health threshold, respectively.

5. According to the big data environmental management system based on smart park according to claim 1, it is characterized by: A comprehensive evaluation model is constructed based on the environmental health index, water quality safety index and noise impact index. The model expression is as follows: Among them, CEQI is the comprehensive environmental quality index, EHI is the environmental health index, WSI is the water quality safety index, NII is the noise impact index, ω1, ω2 and ω3 are proportional coefficients, and their values ​​are determined according to the hierarchical analysis method.

6. According to claim 5, a big data environmental management system based on a smart park is characterized in that: The specific logic of determining the proportional coefficient through the hierarchical analysis method is: The three indicators of environmental health index, water quality safety index and noise impact index are marked, and the relative importance of each other is determined by the nine-scale method to construct a judgment matrix, in which the index of environmental health index is marked as 1, the index of water quality safety index is marked as 2, and the index of noise impact index is marked as 3. The constructed judgment matrix is: Where f and v both represent indexes of the exponent, and f∈[1,3], v∈[1,3], b fv Indicates the importance of the index with index f relative to the index with index v. The importance is scaled from 1 to 9, and b fv The larger the value, the more important the index f is compared to the index v, and b ff =1, Each element value in the judgment matrix is ​​divided by the sum of its columns to obtain a normalized judgment matrix. The mean of the element values ​​in each row of the normalized judgment matrix is ​​calculated, and the mean of the element values ​​in the first row is used as the weight of the environmental health index, the mean of the element values ​​in the second row is used as the weight of the water quality safety index, and the mean of the element values ​​in the third row is used as the weight of the noise impact index. With the constraint that the sum of the scaled values ​​is equal to 1, the three weights are scaled in equal proportions, and the scaled weights are used as the proportional coefficients of the corresponding indexes.

7. The big data environmental management system based on smart park according to claim 1 is characterized by: Different environmental quality levels are set according to the comprehensive environmental quality index, and the specific logic is as follows: When CEQI≤0.5CY, the environmental condition of the park to be managed is judged to be poor, and monitoring should be strengthened immediately, pollution sources should be assessed, and control measures should be taken; When 0.5CY<CEQI≤CY, the environmental condition of the current park to be managed is judged to be general, the monitoring frequency is increased, the environmental improvement plan is implemented, and the pollutant emissions are reduced; When CEQI>CY, the environmental condition of the current park to be managed is judged to be good, and the existing monitoring and management measures should be maintained to ensure stable environmental quality; Among them, CEQI is the comprehensive environmental quality index and CY is the preset assessment threshold.

8. A big data environmental management method based on a smart park, characterized by: The big data environmental management method based on a smart park is obtained by executing the big data environmental management system based on a smart park according to any one of claims 1 to 7, and comprises: Step 1: Conduct on-site surveys in the park to collect air quality parameters, water quality parameters, meteorological parameters and noise levels in the park; the air quality parameters include PM2.5 concentration, carbon dioxide concentration and nitrogen dioxide concentration; the water quality parameters include water pH value, turbidity index and dissolved oxygen concentration; the meteorological parameters include the park's atmospheric temperature, humidity and wind speed; Step 2: Generate an environmental health index based on the dimensionless PM2.5 concentration, CO2 concentration and NO2 concentration, generate a water quality safety index based on the dimensionless water pH value, turbidity index and dissolved oxygen concentration, generate a noise impact index based on the dimensionless noise level, and compare each intermediate parameter with a threshold value. When the intermediate parameter exceeds the threshold value, implement corresponding improvement measures. The intermediate parameters are the environmental health index, water quality safety index and noise impact index. Step 3: Construct a comprehensive assessment model based on the environmental health index, water quality safety index and noise impact index to generate a comprehensive environmental quality index; Step 4: Set different environmental quality levels based on the comprehensive environmental quality index and formulate corresponding improvement measures according to the levels.

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