Smart city environment monitoring method, terminal and environment monitoring system

Abstract

The invention discloses a smart city environment monitoring method, a terminal and an environment monitoring system, relates to the technical field of city environment monitoring, and solves the technical problems that different areas in a smart city cannot be analyzed systematically, and targeted monitoring and control strategies cannot be formed for the different areas. According to the method, region division is carried out on a city, different information of the region is collected to realize accurate monitoring, related factors of each element are comprehensively considered to obtain a comprehensive index, the limitation of single element evaluation is overcome, environment quality evaluation is more scientific and comprehensive, the city is assisted to formulate an effective treatment plan, and the management efficiency is improved for a normal region. The comprehensive index change trend is tracked through deep excavation historical data, and analysis and early warning signals are generated in time to capture potential risks; and for an abnormal area, pollutant distribution is calculated by using a monitoring point network, concentration change is predicted, and early warning is performed by comparing historical concentration, so that the urban environment emergency and prevention and control capability is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of urban environment monitoring, and in particular to an environment monitoring method, terminal and environment monitoring system for a smart city. Background Art

[0002] With the accelerated urbanization process, the construction of smart cities has become the mainstream trend of urban development today.

[0003] According to the publication number CN117370785A, a smart city environmental monitoring method, terminal and environmental monitoring system are provided, wherein the method comprises: extracting characteristic information of environmental data of each monitoring area respectively to obtain environmental characteristics of each monitoring area, classifying the environmental characteristics of each monitoring area respectively by using K-means clustering algorithm to obtain classified data, calculating the numerical difference of the same kind of classified data between each monitoring area, constructing an empirical semivariogram according to the numerical difference, performing interpolation calculation using the classified data of each monitoring area and the empirical semivariogram, estimating environmental data of unknown monitoring areas, and calculating the prediction error of environmental data of unknown monitoring areas, and when it is determined that the prediction error is less than a preset threshold, extracting the environmental characteristics of the environmental data of the unknown monitoring areas, so as to accurately and effectively determine the environmental data of unknown monitoring areas where no monitoring equipment is set.

[0004] Some existing environmental monitoring technologies do not fully integrate the complex and diverse regional characteristics of smart cities, and do not make detailed decompositions of cities according to their autonomous divisions (such as administrative regions, functional zoning, etc.), making it difficult to locate environmental shortcomings and hidden dangers in each region, and unable to form targeted monitoring and control strategies for different regions;

[0005] Traditional methods mostly analyze the atmosphere, water, and soil environments in isolation, without establishing an organic connection and coordinated evaluation system among the three. This cannot fully reflect the true environmental quality of the region, leading to deviations in the assessment of the comprehensive pollution status, affecting the overall control and precise governance of the urban environment.

[0006] In the long-term environmental monitoring process, there is a lack of efficient dynamic tracking mechanism based on historical data mining for normal areas, making it difficult to detect the gradual change trend of environmental quality in a timely manner; for abnormal areas, there is also a lack of effective means to rely on monitoring points to finely analyze the distribution of pollutants and predict pollution trends, resulting in delayed warnings and missed opportunities for prevention and control. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention provides an environmental monitoring method, terminal and environmental monitoring system for a smart city, which solves the problem that there is no systematic analysis of different areas within the smart city and it is impossible to form targeted monitoring and control strategies for different areas.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for environmental monitoring of a smart city, the method specifically comprising the following steps:

[0009] Step S1, obtaining a target smart city, and dividing the target smart city into different areas to obtain analysis areas;

[0010] Step S2, analyzing the environmental state of the analysis area based on the regional information of the analysis area, and classifying the analysis area according to the environmental state to obtain a regional classification result;

[0011] Step S3, analyzing the obtained normal area, analyzing the historical data, and generating monitoring results by monitoring and analyzing the normal area according to the changes of the regional comprehensive index;

[0012] Step S4, analyzing the abnormal area obtained, analyzing the monitoring points in the abnormal area, and determining the distribution of pollutants in the abnormal area according to the monitoring points, and performing pollution prediction based on the pollutant distribution to generate a prediction result.

[0013] As a further solution of the present invention, the specific method of obtaining the analysis area in step S1 is:

[0014] Obtain the target smart city, divide the target smart city into analysis areas according to the subordinate areas, and label the analysis areas as i, where i=1, 2, ..., j, where j represents the number of analysis areas, and obtain the area information corresponding to the analysis area i.

[0015] As a further solution of the present invention, the specific method of analyzing the environmental state of the analysis area in step S2 is:

[0016] The regional information of the analysis area i is obtained, and the regional information includes atmospheric information, water environment information and soil information. At the same time, the regional atmospheric index value, the regional water environment index value and the regional soil index value are calculated respectively, and are recorded as Qi, Ei and Gi respectively.

[0017] As a further solution of the present invention, the specific method of calculating the regional atmospheric index value, the regional water environment index value and the regional soil index value in step S2 is:

[0018] The pollutant concentration corresponding to the analysis area i is obtained and recorded as Ci. At the same time, according to the formula The air quality index IAQ I corresponding to the analysis area i is calculated, and BP low and BPup are the lower and upper limits of the limit range of the pollutant concentration (PM2.5) (μg / m 3), IAQ I l ow and IAQ I up are the lower and upper limits of the air quality sub-index corresponding to the concentration limit interval, and the air quality sub-indexes corresponding to all pollutants are calculated in this way, and the average value of all air quality sub-indices is calculated to obtain the regional atmospheric index value Qi;

[0019] Obtain the pH value, DO (dissolved oxygen), and COD (chemical oxygen demand) corresponding to the analysis area i, standardize the obtained parameters, determine the parameter weights, and substitute the obtained parameters into the formula The regional water environment index Ei is calculated, where w n is the weight of the nth indicator, y nm The data after standardization of the mth indicator of the nth sample;

[0020] The soil texture, pH value, soil nutrient content, and microbial activity corresponding to the analysis area i are obtained, and the obtained data are standardized. The corresponding weights are determined, and the regional soil index value Gi is calculated in the same way as the regional water environment index value.

[0021] As a further solution of the present invention, the specific method of obtaining the regional classification result in step S2 is:

[0022] The calculated regional atmospheric index value Qi, regional water environment index value Ei and regional soil index value Gi are substituted into the formula Ti=Qi×a1+Qi×a2+Qi×a3 to calculate the regional comprehensive index Ti corresponding to the analysis area i, and the obtained regional comprehensive index Ti is compared with the preset value Ty. If the regional comprehensive index Ti is greater than the preset value Ty, the corresponding analysis area is classified as an abnormal area. Otherwise, if the regional comprehensive index Ti is less than the preset value Ty, the corresponding analysis area is classified as a normal area.

[0023] As a further solution of the present invention, the specific method of analyzing the obtained normal area in step S3 is:

[0024] Obtain the historical data corresponding to the normal area, calculate the regional comprehensive index corresponding to different periods based on the historical data, and sort the regional comprehensive index according to the period order, and then analyze the change trend of the sorted regional comprehensive index. If the regional comprehensive index increases, a secondary analysis signal is generated. On the contrary, if the regional comprehensive index is stable, a continuous monitoring result is generated, and the generated secondary analysis signal is specifically processed;

[0025] Get the current regional comprehensive index, and at the same time get the regional comprehensive index of the previous set of adjacent periods, and calculate the difference between the two. Then compare the calculated difference with the judgment threshold. If the difference is greater than the judgment threshold, generate an early warning result. Otherwise, if the difference is less than the judgment threshold, generate a continuous monitoring result.

[0026] As a further solution of the present invention, the specific method of analyzing the abnormal area obtained in step S4 is:

[0027] Obtain an abnormal area and label it as o, where o=1, 2, ..., p. At the same time, obtain any group of abnormal areas o as the target area, and obtain the abnormal parameters corresponding to the target area. Then obtain the monitoring points corresponding to the abnormal parameters, and determine the monitoring area with the monitoring points as the center. At the same time, obtain all the monitoring points in the monitoring area and label them as k, where k=1, 2, ..., u, where u represents the number of monitoring points, and obtain any point in the monitoring area as a point to be analyzed. Then, respectively obtain the distance between the monitoring point k and the point to be analyzed and record it as Dk. At the same time, obtain the abnormal parameter concentration corresponding to the monitoring point k and record it as Fk.

[0028] And substitute the obtained parameters into the formula The concentration value S of the point to be analyzed in the target area is calculated, where u is the number of monitoring points and p is the power of the distance. It is generally determined by the operator based on experience. Then, the change of the concentration value S of the point to be analyzed is analyzed.

[0029] Obtain the historical concentration value S1 of the adjacent weekly point to be analyzed and compare the two. If the concentration value S1 is less than S, it means that the concentration of the point to be analyzed has increased, and an early warning result is generated. Otherwise, if the concentration value S1 is equal to S, it means that the concentration of the point to be analyzed is stable, and a monitoring result is generated.

[0030] An environmental monitoring terminal for a smart city specifically includes: at least one processor, a memory, and a computer program stored in the memory and executable on at least one processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned environmental monitoring methods are implemented.

[0031] An environmental monitoring system for a smart city, comprising an information collection unit, an information processing unit, a normal monitoring unit, an abnormal monitoring unit and an information output unit;

[0032] An information collection unit, which is used to determine the target smart city, obtain the city information of the target city, and transmit the city information to the information processing unit;

[0033] An information processing unit, which is used to divide the target smart city into different areas according to the acquired city information to obtain analysis areas, and analyze the environmental status of the analysis area based on the regional information of the analysis area, and classify the analysis area according to the environmental status to obtain a regional classification result, the regional classification result includes a normal area and an abnormal area, and then transmit the normal area to a normal monitoring unit, and transmit the abnormal area to an abnormal monitoring unit;

[0034] Normal monitoring unit, which analyzes the obtained normal area, analyzes historical data, and generates monitoring results by monitoring and analyzing the normal area according to the changes of regional comprehensive index;

[0035] An abnormal monitoring unit, which analyzes the abnormal area obtained, analyzes the monitoring points in the abnormal area, determines the distribution of pollutants in the abnormal area according to the monitoring points, and predicts pollution based on the distribution of pollutants, generates prediction results, and transmits the prediction results to the information output unit;

[0036] An information output unit is used to display the acquired monitoring results and prediction results to the corresponding operators.

[0037] The present invention provides a smart city environment monitoring method, terminal and environment monitoring system. Compared with the prior art, it has the following beneficial effects:

[0038] The present invention divides the "analysis area" in detail according to the inherent affiliated areas of the city, labels and collects the corresponding air, water and soil information one by one, and conducts precise monitoring of the environment of different regions "tailored to the needs". It can accurately locate the weak links, and clearly divide the normal and abnormal areas according to the comparison of the comprehensive index with the preset value, which is convenient for classification and policy implementation, and enhances the accuracy of urban environmental control.

[0039] Integrate the calculation methods of regional atmospheric, water environment and soil environment indexes, comprehensively consider the indicators, weights and limits of each factor, and obtain a comprehensive index in a quantitative manner to truly restore the overall environmental appearance of the region, overcome the limitations of single factor evaluation, make environmental quality assessment more scientific and comprehensive, and assist cities in formulating balanced and effective governance plans;

[0040] At the normal regional level, we dig deep into historical data, track the cyclical changes of regional comprehensive indexes, generate secondary analysis and early warning signals in a timely manner based on trends, and keenly capture potential environmental risks; in abnormal areas, we use a network of monitoring points to accurately calculate the distribution of pollutants, predict concentration trends, compare historical concentrations, and issue early warnings of worsening pollution, thereby improving urban environmental emergency response and prevention and control capabilities and ensuring the ecological resilience and livability of smart cities. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a step method diagram of the present invention;

[0042] Figure 2 This is a block diagram of the system principle of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] For example, see Figure 1 The present application provides a method for environmental monitoring of a smart city, which specifically includes the following steps:

[0045] Step S1, acquiring a target smart city, and dividing the target smart city into different areas to obtain analysis areas.

[0046] First, the target smart city is obtained, and then the target smart city is divided into analysis areas according to the subordinate areas. The subordinate areas here represent the city's autonomous division method. For example, Beijing can be divided into multiple districts, such as Chaoyang District, Haidian District, Shunyi District, etc. The target smart city is divided in this way. At the same time, the analysis areas are labeled as i, and i=1, 2, ..., j, where j represents the number of analysis areas, and the area information corresponding to the analysis area i is obtained.

[0047] Step S2: analyzing the environmental status of the analysis area based on the area information of the analysis area, and classifying the analysis area according to the environmental status to obtain an area classification result.

[0048] Acquire regional information of analysis area i, and the regional information includes atmospheric information, water environment information and soil information, and calculate regional atmospheric index value, regional water environment index value and regional soil index value respectively, and record them as Qi, Ei and Gi respectively;

[0049] The specific method for calculating the regional atmospheric index value is: obtain the pollutant concentration corresponding to the analysis area i and record it as Ci, where the pollutant concentration here is the concentration of PM2.5, and according to the formula The air quality index IAQ I corresponding to the analysis area i is calculated, and BP low and BPup are the lower and upper limits of the limit range of the pollutant concentration (PM2.5) (μg / m 3), IAQ I l ow and IAQ I up are the lower and upper limits of the air quality sub-index corresponding to the concentration limit interval, and the air quality sub-indexes corresponding to all pollutants are calculated in this way, and the average value of all air quality sub-indices is calculated to obtain the regional atmospheric index value Qi;

[0050] The specific method for calculating the regional water environment index value is to obtain the pH value, DO (dissolved oxygen), and COD (chemical oxygen demand) corresponding to the analysis area i, standardize the obtained parameters, determine the weights of the parameters, and substitute the obtained parameters into the formula The regional water environment index Ei is calculated, where w n is the weight of the nth indicator, y nm The data of the mth index of the nth sample after standardization, for example, there are three indexes (pH value, DO, COD), after standardization and weight determination (assuming pH weight w1 = 0.2, DO weight w2 = 0.4, COD weight w3 = 0.4), for a certain water sample, the standardized pH value y1 = 0.6, DOy2 = 0.5, CODy3 = 0.3, then the comprehensive water environment quality index Ei = 0.2x0.6 + 0.4x0.5 + 0.4x0.3 = 0.44;

[0051] The specific method for calculating the regional soil index value is: obtain the soil texture, pH value, soil nutrient content, and microbial activity corresponding to the analysis area i, standardize the obtained data, determine the corresponding weights, and calculate the regional soil index value Gi in the same way as the calculation method of the regional water environment index value; for example, there are four indicators (soil texture, pH value, soil nutrient content, and microbial activity). After standardization and weight determination (assuming that the soil texture weight w1=0.2, the pH value weight w2=0.3, the soil nutrient content weight w3=0.3, and the microbial activity weight w4=0.2), for a certain soil sample, the standardized soil texture y==0.6, the pH value y2=0.7, the soil nutrient content y3=0.5, and the microbial activity y4=0.4, then the soil quality comprehensive index Gi=0.2x0.6+0.3x0.7+0.3x0.5+0.2x0.4=0.56;

[0052] Substitute the calculated regional atmospheric index value Qi, regional water environment index value Ei and regional soil index value Gi into the formula Ti=Qi×a1+Qi×a2+Qi×a3 to calculate the regional comprehensive index Ti corresponding to the analysis area i, and compare the obtained regional comprehensive index Ti with the preset value Ty, and the specific value of the preset value Ty is set by the operator. If the regional comprehensive index Ti is greater than the preset value Ty, the corresponding analysis area is classified as an abnormal area. On the contrary, if the regional comprehensive index Ti is less than the preset value Ty, the corresponding analysis area is classified as a normal area.

[0053] Step S3, analyzing the obtained normal area, analyzing the historical data, and monitoring and analyzing the normal area according to the changes of the regional comprehensive index to generate monitoring results.

[0054] Obtain historical data corresponding to normal areas, and calculate regional comprehensive indexes corresponding to different periods based on historical data, and here is the regional comprehensive index of normal areas, and sort the regional comprehensive indexes according to the periodic sequence, and here specifically sort according to the timeline of the time period, and then analyze the change trend of the sorted regional comprehensive index. If the regional comprehensive index increases, a secondary analysis signal is generated. On the contrary, if the regional comprehensive index is stable, a continuous monitoring result is generated. The specific change trend is judged by calculating the difference between the regional comprehensive indexes of adjacent periods, and the generated secondary analysis signal is specifically processed;

[0055] The current regional comprehensive index is obtained, and the regional comprehensive index of the previous set of adjacent cycles is obtained at the same time, and the difference between the two is calculated. The difference is calculated by subtracting the regional comprehensive index of the previous set of cycles from the current regional comprehensive index. Then the calculated difference is compared with the judgment threshold, and the value of the judgment threshold is set by the operator. If the difference is greater than the judgment threshold, an early warning result is generated. Otherwise, if the difference is less than the judgment threshold, a continuous monitoring result is generated.

[0056] Step S4, analyzing the abnormal area obtained, analyzing the monitoring points in the abnormal area, and determining the distribution of pollutants in the abnormal area according to the monitoring points, and performing pollution prediction based on the pollutant distribution to generate a prediction result.

[0057] Obtain the abnormal area and label it as o, where o=1, 2, ..., p. At the same time, obtain any group of abnormal areas o as the target area, and obtain the abnormal parameters corresponding to the target area. Then obtain the monitoring points corresponding to the abnormal parameters, and determine the monitoring area with the monitoring points as the center. Here, the monitoring area is a range area with a radius of R and the monitoring points as the center. At the same time, obtain all the monitoring points in the monitoring area and label them as k, where k=1, 2, ..., u, where u represents the number of monitoring points. Obtain any point in the monitoring area as a point to be analyzed. Then obtain the distance between the monitoring point k and the point to be analyzed and record it as Dk. At the same time, obtain the abnormal parameter concentration corresponding to the monitoring point k and record it as Fk.

[0058] And substitute the obtained parameters into the formula The concentration value S of the point to be analyzed in the target area is calculated, where u is the number of monitoring points and p is the power of the distance. It is generally determined by the operator based on experience. Then, the change of the concentration value S of the point to be analyzed is analyzed.

[0059] Obtain the historical concentration value S1 of the adjacent weekly point to be analyzed and compare the two. If the concentration value S1 is less than S, it means that the concentration of the point to be analyzed has increased, and an early warning result is generated. Otherwise, if the concentration value S1 is equal to S, it means that the concentration of the point to be analyzed is stable, and a monitoring result is generated.

[0060] Embodiment 2, the present application provides an environment monitoring terminal for a smart city, specifically comprising: at least one processor, a memory, and a computer program stored in the memory and executable on at least one processor, wherein when the processor executes the computer program, the steps in any one of the above-mentioned environment monitoring method embodiments are implemented. The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The terminal device may include, but is not limited to, a processor and a memory.

[0061] For example 3, please refer to Figure 2 The present application provides an environment monitoring system for a smart city, including: an information collection unit, an information processing unit, a normal monitoring unit, an abnormal monitoring unit and an information output unit, and in combination with the attached Figure 2 As shown, the functional units are unidirectionally electrically connected to each other.

[0062] An information collection unit, which is used to determine the target smart city, obtain the city information of the target city, and transmit the city information to the information processing unit;

[0063] An information processing unit, which is used to divide the target smart city into different areas according to the acquired city information to obtain analysis areas, and analyze the environmental state of the analysis area based on the regional information of the analysis area, and classify the analysis area according to the environmental state to obtain a regional classification result, and the processing method here is the same as the processing method of step S2 in embodiment 1, and the regional classification result includes a normal area and an abnormal area, and then the normal area is transmitted to the normal monitoring unit, and the abnormal area is transmitted to the abnormal monitoring unit;

[0064] A normal monitoring unit, which analyzes the obtained normal area, monitors and analyzes the normal area according to the change of the regional comprehensive index by analyzing the historical data, and generates a monitoring result. The processing method here is the same as the processing method of step S3 in the first embodiment, and transmits the monitoring result to the information output unit;

[0065] An abnormal monitoring unit, which analyzes the abnormal area obtained, analyzes the monitoring points of the abnormal area, and determines the distribution of pollutants in the abnormal area according to the monitoring points, and performs pollution prediction based on the distribution of pollutants to generate prediction results. The processing method here is the same as the processing method of step S4 in embodiment 1, and the prediction results are transmitted to the information output unit;

[0066] An information output unit is used to display the acquired monitoring results and prediction results to the corresponding operators.

[0067] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0068] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for environmental monitoring of a smart city, characterized in that: The method specifically comprises the following steps: Step S1, obtaining a target smart city, and dividing the target smart city into different areas to obtain analysis areas; Step S2, analyzing the environmental state of the analysis area based on the regional information of the analysis area, and classifying the analysis area according to the environmental state to obtain a regional classification result; Step S3, analyzing the obtained normal area, analyzing the historical data, and generating monitoring results by monitoring and analyzing the normal area according to the changes of the regional comprehensive index; Step S4, analyzing the abnormal area obtained, analyzing the monitoring points in the abnormal area, and determining the distribution of pollutants in the abnormal area according to the monitoring points, and performing pollution prediction based on the pollutant distribution to generate a prediction result.

2. The method for environmental monitoring of a smart city according to claim 1, characterized in that: The specific method of obtaining the analysis area in step S1 is: Obtain the target smart city, divide the target smart city into analysis areas according to the subordinate areas, and label the analysis areas as i, where i=1, 2, ..., j, where j represents the number of analysis areas, and obtain the area information corresponding to the analysis area i.

3. The method for environmental monitoring of a smart city according to claim 1, characterized in that: The specific method of analyzing the environmental status of the analysis area in step S2 is: The regional information of the analysis area i is obtained, and the regional information includes atmospheric information, water environment information and soil information. At the same time, the regional atmospheric index value, the regional water environment index value and the regional soil index value are calculated respectively, and are recorded as Qi, Ei and Gi respectively.

4. The method for environmental monitoring of a smart city according to claim 3, characterized in that: The specific method for calculating the regional atmospheric index value, the regional water environment index value and the regional soil index value in step S2 is: The pollutant concentration corresponding to the analysis area i is obtained and recorded as Ci. At the same time, according to the formula The air quality index IAQI corresponding to the analysis area i is calculated, and BPlow and BPup are the lower and upper limits of the limit range of the pollutant concentration (PM2.5) (μg / m 3 ), IAQIlow and IAQIup are the lower and upper limits of the air quality sub-index corresponding to the concentration limit interval. The air quality sub-indexes corresponding to all pollutants are calculated in this way, and the average value of all air quality sub-indexes is calculated to obtain the regional atmospheric index value Qi; Obtain the pH value, DO (dissolved oxygen), and COD (chemical oxygen demand) corresponding to the analysis area i, standardize the obtained parameters, determine the parameter weights, and substitute the obtained parameters into the formula The regional water environment index Ei is calculated, where w n is the weight of the nth indicator, y nm The data after standardization of the mth indicator of the nth sample; The soil texture, pH value, soil nutrient content, and microbial activity corresponding to the analysis area i are obtained, and the obtained data are standardized. The corresponding weights are determined, and the regional soil index value Gi is calculated in the same way as the regional water environment index value.

5. The method for environmental monitoring of a smart city according to claim 1, characterized in that: The specific method for obtaining the regional classification result in step S2 is: The calculated regional atmospheric index value Qi, regional water environment index value Ei and regional soil index value Gi are substituted into the formula Ti=Qi×a1+Qi×a2+Qi×a3 to calculate the regional comprehensive index Ti corresponding to the analysis area i, and the obtained regional comprehensive index Ti is compared with the preset value Ty. If the regional comprehensive index Ti is greater than the preset value Ty, the corresponding analysis area is classified as an abnormal area. Otherwise, if the regional comprehensive index Ti is less than the preset value Ty, the corresponding analysis area is classified as a normal area.

6. The method for environmental monitoring of a smart city according to claim 1, characterized in that: The specific method of analyzing the obtained normal area in step S3 is: Obtain the historical data corresponding to the normal area, calculate the regional comprehensive index corresponding to different periods based on the historical data, and sort the regional comprehensive index according to the period order, and then analyze the change trend of the sorted regional comprehensive index. If the regional comprehensive index increases, a secondary analysis signal is generated. On the contrary, if the regional comprehensive index is stable, a continuous monitoring result is generated, and the generated secondary analysis signal is specifically processed; Get the current regional comprehensive index, and at the same time get the regional comprehensive index of the previous set of adjacent periods, and calculate the difference between the two. Then compare the calculated difference with the judgment threshold. If the difference is greater than the judgment threshold, generate an early warning result. Otherwise, if the difference is less than the judgment threshold, generate a continuous monitoring result.

7. The method for environmental monitoring of a smart city according to claim 1, characterized in that: The specific method of analyzing the abnormal area obtained in step S4 is: Obtain an abnormal area and label it as o, where o=1, 2, ..., p. At the same time, obtain any group of abnormal areas o as the target area, and obtain the abnormal parameters corresponding to the target area. Then obtain the monitoring points corresponding to the abnormal parameters, and determine the monitoring area with the monitoring points as the center. At the same time, obtain all the monitoring points in the monitoring area and label them as k, where k=1, 2, ..., u, where u represents the number of monitoring points, and obtain any point in the monitoring area as a point to be analyzed. Then, respectively obtain the distance between the monitoring point k and the point to be analyzed and record it as Dk. At the same time, obtain the abnormal parameter concentration corresponding to the monitoring point k and record it as Fk. And substitute the obtained parameters into the formula The concentration value S of the point to be analyzed in the target area is calculated, where u is the number of monitoring points and p is the power of the distance. It is generally determined by the operator based on experience. Then, the change of the concentration value S of the point to be analyzed is analyzed. Obtain the historical concentration value S1 of the adjacent weekly point to be analyzed and compare the two. If the concentration value S1 is less than S, it means that the concentration of the point to be analyzed has increased, and an early warning result is generated. Otherwise, if the concentration value S1 is equal to S, it means that the concentration of the point to be analyzed is stable, and a monitoring result is generated.

8. An environmental monitoring terminal for a smart city, characterized in that: Specifically include: At least one processor, a memory, and a computer program stored in the memory and executable on at least one processor, wherein when the processor executes the computer program, the steps of any one of the environmental monitoring methods of claims 1-7 are implemented.

9. An environmental monitoring system for a smart city, used to execute the environmental monitoring method according to any one of claims 1 to 7, characterized in that: It includes an information collection unit, an information processing unit, a normal monitoring unit, an abnormal monitoring unit and an information output unit; An information collection unit, which is used to determine the target smart city, obtain the city information of the target city, and transmit the city information to the information processing unit; An information processing unit, which is used to divide the target smart city into different areas according to the acquired city information to obtain analysis areas, and analyze the environmental status of the analysis area based on the regional information of the analysis area, and classify the analysis area according to the environmental status to obtain a regional classification result, the regional classification result includes a normal area and an abnormal area, and then transmit the normal area to a normal monitoring unit, and transmit the abnormal area to an abnormal monitoring unit; Normal monitoring unit, which analyzes the obtained normal area, analyzes historical data, and generates monitoring results by monitoring and analyzing the normal area according to the changes of regional comprehensive index; An abnormal monitoring unit, which analyzes the abnormal area obtained, analyzes the monitoring points in the abnormal area, determines the distribution of pollutants in the abnormal area according to the monitoring points, and predicts pollution based on the distribution of pollutants, generates prediction results, and transmits the prediction results to the information output unit; An information output unit is used to display the acquired monitoring results and prediction results to the corresponding operators.

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