Online Monitoring of Ecoenvironmental Pollution Data in Internet Environment

Han, Bo

doi:https://doi.org/10.1155/2022/1105282

Wireless Communications and Mobile Computing

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Advanced Information Security in Next Generation Wireless Communication-Enabled Internet of Things

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Research Article | Open Access

Volume 2022 | Article ID 1105282 | https://doi.org/10.1155/2022/1105282

Online Monitoring of Ecoenvironmental Pollution Data in Internet Environment

Bo Han¹

Academic Editor: Zhiguo Qu

Received15 Mar 2022

Revised01 Apr 2022

Accepted12 Apr 2022

Published09 May 2022

Abstract

In view of the problems of poor air quality and serious soil pollution in the current ecological environment, an online monitoring of ecological environment pollution data in the Internet environment is proposed. The concentration of pollution sources that may appear in the atmospheric environment is analyzed through the analysis coefficient of ecological environment pollutants, and the specific grade data corresponding to the air quality index is determined. Observation and mapping are carried out for the area to be monitored, and then, the monitoring points are determined, the monitoring equipment is arranged, and the soil profile of the area is sampled in the monitoring area. The self-organizing neural network model is used to conduct spatial cluster analysis on the pollution of ecological environment pollution areas, evaluate the sensitivity of soil pollution, and build a land ecological pollution monitoring information model. Based on the Internet of Things technology and the comprehensive use of GPS, sensors, and other technologies and equipment, the framework of monitoring technology is constructed, and the online monitoring of ecological environment pollution data is completed. The experimental results show that the proposed method has high data accuracy in different locations and different seasons, which is consistent with the actual situation; because of the maturity of the Internet of Things technology, compared with the literature method, the method in this paper can provide a cost-effective data foundation, which is more cost-effective, and save time and energy.

1. Introduction

The rapid development of the world economy, the increasing pollution of the ecological environment, the continuous growth of the population, the continuous loss of natural resources, and the increasingly serious environmental problems are the issues faced by the country [1, 2]. The government-based environmental supervision work aims to effectively manage a series of current environmental problems, effectively supervise and punish various environmental damage behaviors, and effectively prevent future environmental problems [3, 4]. In recent years, China’s environmental supervision work has been advancing rapidly, and the degree of environmental pollution has been controlled to a certain extent [5]. However, in recent years, frequent outbreaks of haze weather, acid rain, oil pipeline explosions, and other pollution incidents have aroused strong concern, and the current environment still cannot reach the comfortable state people need for life [6, 7]. Although China has gradually strengthened the supervision of environmental ecology in recent years, and the ecological environment has tended to be stable as a whole, considering that China’s current ecological environment is still not optimistic, it will continue to face rapid economic development and population in the future [8]. How to effectively participate in the supervision of the ecological environment through various subjects? It will become an issue worthy of study in China’s current ecological and environmental protection supervision issues.

Reference [9] proposes specialized ecological polygons as one of the tools to reduce the pollution of medicines to the environment and discusses the pollution of natural objects in the environment by medicines. The main sources of drug wastes, their causes, the way drugs penetrate, and the results of drug metabolism in the patient’s body into environmental systems are all characteristic. Some data on the emergence of drugs in the natural environment were analyzed. This describes the composition of recommendations and measures required to reduce the level of environmental risk associated with pollution. Particular attention is paid to the environmental monitoring service, which provides laboratory support for environmental monitoring of environmental facilities, including hydrological and geochemical analysis of water, soil, and air environments. Given the extent to which controlled substances affect the natural environment, it is recommended that the effectiveness of environmental monitoring services be improved by deploying specialized ecosystems. Research shows that the main suppliers of pharmaceutical waste are medical institutions, chemical and pharmaceutical companies, and the general public. Reference [10] pointed out the difficulties and achievements of China’s ecological environment construction from 1949 to 2019. China’s ecological environment construction has gone through three stages, namely, the low-productivity development stage based on agriculture shortly after the founding of New China and the postreform and opening-up stage. Each of the stages of industrial development and ecological civilization has its own characteristics, challenges, countermeasures, and achievements. From 1949 to reform and opening up, Chinese society as a whole was characterized by a farming culture and faced problems such as frequent natural disasters, insufficient food production, and low level of urbanization. In order to jump out of the Malthusian trap, the founders of the People’s Republic of China led the people to prevent floods through water conservancy, water conservancy projects, and reclamation of wasteland, which alleviated the problem, but did not solve it, because China was still in poverty and backwardness and failed to escape the Malthusian curse. After the reform and opening up, the process of industrialization and urbanization accelerated, farmers were liberated from the land, and labor productivity was greatly improved. Although rapid industrialization and urbanization have greatly promoted the development of productive forces and accumulated huge material wealth, since the beginning of the 21st century, China’s development has approached the ecological red line, environmental threshold, and resource limit of industrial development and has been continuously affected by sustainable development challenge. After 2010, China began to transform into an ecological civilization, featuring ecological protection, pollution control, and resource conservation, aiming to promote the harmonious development of man and nature.

Although some progress has been made in the above research, the research in the Internet environment is insufficient. Therefore, online monitoring of ecoenvironmental pollution data in the Internet environment is proposed. The Internet is the crystallization of human wisdom, a major scientific and technological invention in the 20th century and an important symbol of contemporary advanced productive forces. The Internet has a profound impact on the development of the world economy, politics, culture, and society and has promoted the transformation of social production and life and information dissemination. Vigorously advocate and actively promote the development and wide application of the Internet in online monitoring of ecological and environmental pollution data. With the rapid development and popularization of the Internet, people’s production, work, study, and lifestyle have begun and will continue to undergo profound changes. This paper analyzes the concentration of possible pollution sources in the atmospheric environment through the analysis coefficient of ecoenvironmental pollutants and determines the specific grade data corresponding to the air quality index. Observe and map the areas to be monitored, then determine the monitoring points, arrange the monitoring equipment, and sample the soil profile in the monitoring area. The self-organizing neural network model is used to carry out spatial cluster analysis on the pollution of ecoenvironmental pollution areas, evaluate the sensitivity of soil pollution, and construct the land ecological pollution monitoring information model. Combined with the Internet of Things technology, comprehensively utilize GPS, sensors and other technologies and equipment, construct the monitoring technology framework, and online monitor the ecological environment pollution data. The experimental results show that the accuracy of the monitoring data in different places and seasons is high, which is consistent with the actual situation. It can provide a cost-effective data base, save time and labor, and has good results.

2. Establish the Analysis Coefficient of Ecoenvironmental Pollutants

At present, AQI (air quality index) evaluation method is often used to specifically define the change of air quality in ecological environment [11]. This index can convert single or multiple atmospheric variation concentrations into linear data results and make the comprehensive index evaluation results present an exponential expression relationship. It can also establish corresponding index evaluation models according to the atmospheric distribution of different environments, which can effectively reflect the excellence of large gas quality and make the monitoring and judgment process more simple and intuitive [12].

Use the above method to analyze the specific concentration index of pollutants that may appear in the ecological atmospheric environment. Firstly, set table to show the average expressed concentration of a gas sample , and use to represent the defined standard value of the pollutant sample . According to the index evaluation method, the calculation formula is obtained:

In formula (1), and represent constant values of atmospheric concentration. Due to the wide range of application of index evaluation method, the description and expression of things are more detailed, which can accurately express the importance of each air pollutant. In the actual index evaluation, after accurate calculation of air pollutants, the monitoring results can be divided into six index levels. The lower the level and the higher the value, the more serious the air pollution and the worse the environmental quality [13, 14]. Among them, the pollutants contained are PM10 and PM2 5, CO, NO₂, SO₂, and O₂. Based on this, the accurate expression of pollution index judgment can be realized, and the detailed parameters are shown in Table 1.

According to the contents shown in Table 1, the index evaluation method needs to establish corresponding evaluation standards and environmental background values according to the situation of the monitoring area and calculate the required constant coefficient values and of the monitoring area according to these two standards. The main determination methods of coefficient values and are as follows: when the pollutant concentration in the monitoring area is equal to the original background concentration in the area, it can be expressed as . When the pollutant concentration in the monitoring area is equal to the average pollutant concentration in the area, it can be expressed as . By analogy, the calculation method of residual value in grade division is obtained. Therefore, the determination equations of constant coefficients and are as follows:

According to this equation group, the constant coefficient values of all monitoring samples can be calculated to facilitate the subsequent determination of specific concentration. With the support of the Internet of Things environment, the monitoring tools are placed in the atmosphere, and the air quality exposed to the atmosphere is evaluated by Monte Carlo method. The specific formula is

In formula (3), represents the exposure level, represents the average concentration for a fixed time, represents the sampling concentration when the time interval is , and represents the sampling interval. By obtaining the hourly average concentration value of pollutants monitored in the atmospheric environment, the change of pollution in a certain area is recorded at any time as the daily concentration value of pollutants.

The atmospheric monitoring station is placed in the atmosphere. By evaluating the time period data monitored by the atmospheric monitoring station and the atmospheric monitoring vehicle, the average value of relative error in four time periods of “spring, summer, autumn, and winter” is selected [15]. The specific formula is

In formula (4), represents the corresponding error of the time period mean value of monitoring factor, represents the time period mean value of monitoring factor of monitoring vehicle , and represents the time period mean value of monitoring factor of atmospheric monitoring station . To sum up, the analysis coefficient of ecoenvironmental pollutants is established to pave the way for the online monitoring of ecoenvironmental pollution data in the Internet environment.

3. Realize Online Monitoring of Ecoenvironmental Pollution Data in the Internet Environment

3.1. Collection and Extraction of Online Monitoring Information of Ecological Environment Pollution Data

On the premise of completing the above-mentioned monitoring of changes in the air quality of the ecological environment, the information collection and extraction of the types of soil pollution in the ecological environment are carried out. Observe and map the areas that need to be monitored, and then determine the monitoring points [16]. With reference to the topography, geographic location, and soil type of the area, select appropriate monitoring equipment to conduct field surveys on the land environment. For different types of land environments, consider the factors such as soil moisture, stability, vegetation type, and slope, record the land ecological environment in the area in detail, and formulate an appropriate online monitoring plan for land ecological environment pollution data after systematic analysis and calculation [17].

Different monitoring methods are selected for different soil types, and basic data monitoring is performed on the land in the uncontaminated area to obtain the soil environmental parameters in the original state of the area. For areas that have been polluted, soil sampling is performed directly to obtain initial land ecological pollution information data [18]. The monitoring equipment is arranged, and the soil profile is sampled in the monitoring area. Set different profile levels according to the plan, and sample the soil at different levels from top to bottom. Determine the position of the same depth for each profile, and sample 500 g^-1 kg of soil at a fixed point, and then pack the collected soil samples. Put the samples into the sample bag, paste the corresponding labels, and place them in specific sample areas. The distribution of sampling points is shown in Figure 1.

According to the distribution of sampling points in Figure 1, after soil sample collection is completed, the corresponding ecological pollution monitoring indicators are selected and formulated according to the type of pollution in the area [19, 20]. The monitoring equipment is used to monitor and collect relevant information and data on the ecological pollution of the land. According to the type of pollution, the monitoring indicators can be roughly divided into two categories. One is for the monitoring of organic pollutants and volatile pollutants, and the other is for monitoring of heavy metal pollutants.

For organic pollutants, soil samples can be monitored directly. Disinfect the soil samples to be monitored, and then dry the water in the soil through the heating plate to obtain the dry loose soil. Then, add the digestive solution prepared by mixed acid to test and digest the soil to obtain the content of organic pollutants in the soil [21, 22]. For heavy metal pollutants, it is necessary to use the sensing monitor of remote sensing equipment to conduct field inspection at the monitoring points in the land ecological pollution area, collect the information data about heavy metal elements in soil pollution, and obtain the infrared spectrum remote sensing image of the monitoring area through the monitoring equipment. The monitoring process is shown in Figure 2.

It can be seen from Figure 2 that during the monitoring process, due to the formation of remote sensing imaging through satellite observation and the influence of many additional environmental factors, there is a large deviation in the imaging results. Therefore, the image needs to be converted through computer image processing program. In this link, factors such as soil reflectance, pixel value of spectral image, spectral brightness, solar radiance outside the atmosphere, and solar terrestrial distance need to be considered to further eliminate the impact of factors such as atmosphere, solar angle, and solar terrestrial distance on spectral imaging results, so as to ensure a more accurate remote sensing image [23].

Adjust the distribution of remote sensing images according to the position of surface monitoring points and correct the image distortion caused by angular deviation [24]. Through the image processing program, improve the resolution and clarity of the image, import the spectral information of different kinds of heavy metal elements, extract the parameter information such as the distribution and content of heavy metal pollutants in the image, set the spectral index, adjust the radiance of different spectra, and distinguish the distribution of different heavy metal elements.

Through the above operation process, identify, extract, and record the category, content, and distribution of heavy metal elements obtained from monitoring [25]. Get the spectral image data of each heavy metal element, calculate the content of corresponding heavy metal pollutants in the soil according to the soil reflectance, and further calculate the information data of various pollutants. Import the statistically sorted sample information data into the pollutant information database to complete the collection of land ecological environment pollution information.

3.2. Monitoring of Ecoenvironmental Pollution Information Based on Self-Organizing Neural Network in the Internet Environment

According to the collected and extracted information data of land ecological environment pollution, the self-organizing neural network method is used to monitor the land ecological environment pollution information. The self-organizing neural network model is used to conduct spatial cluster analysis on the pollution of ecological environment polluted areas. The self-organizing neural network model has powerful data mining and processing functions, can comprehensively process multidimensional data information and identify and process the correlation and difference of large-scale interval data, and has the advantages of objectivity and efficiency. It can reduce the information monitoring deviation caused by subjective factors and calculation errors [26, 27]. The self-organizing neural network model is shown in Figure 3.

According to Figure 3, the main structure of the self-organizing neural network model is divided into input layer and output layer. The data information to be processed is input into the model input layer. According to the type and distribution of data information, it is input into each neuron of the model. The neural network is interconnected, and the input neural node is connected with an output neural node. The neural plane matrix network is composed in two-dimensional space [28, 29]. The computer operation program repeatedly learns the input data through the weighting vector to make the data weighting vector consistent with the spatial distribution density. After calculation, the input neuron data will find the neuron closest to its own carrying vector as the optimal neuron and select it as the best matching unit [30]. The neurons selected as the best matching unit and their adjacent neurons will be adjusted again through the weighting vector to make the neural network consistent with the current sample distribution. This process will continue to repeat the above operations and iteratively obtain the self-organizing neural network map of land ecological environment pollution.

According to the self-organizing neural network diagram, the degree of land pollution is evaluated through pollution monitoring indicators. The evaluation method of soil pollution sensitivity is as follows:

In formula (5), represents the erosion sensitivity index of contaminated soil in the unit area, and represents the sensitivity level of pollution sensitivity factors. There are four reference indicators in total, namely, precipitation erosion factor, slope factor, vegetation cover factor, and soil pollution factor, from which the soil pollution sensitivity can be calculated [31, 32].

The ecological environment pollution information monitoring process of self-organizing neural network in the Internet environment is shown in Figure 4.

It can be seen from Figure 4 that the monitoring process needs to monitor the pollution of land ecological environment according to the sensitivity of soil pollution, and the data collected and extracted by the sensor are successively imported into the self-organizing neural network model to calculate the relevant data of soil pollution in each part [33]. Import all the calculated data categories into the database to build the land ecological pollution monitoring information model. The formula is as follows:

In formula (6), represents the soil pollution monitoring index, and , , and represent the grade standard value of soil pollution degree, respectively. Grade the monitoring data through the model, clarify the degree and level of pollution in each region, and form a relatively complete monitoring information of land ecological environment pollution [34]. For the pollution of ecological environment, first use advanced monitoring equipment to collect soil pollution information, and then carry out targeted data processing on the soil information.

Based on the application of Internet of Things, intelligent monitoring technology connects people, things and people through expansion and extension, and comprehensively utilizes technologies and equipment such as GPS and sensors to realize online monitoring of ecological environment pollution data [35]. In order to realize the standardization of data acquisition, visualization of video monitoring, intelligent automatic alarm, and structured data analysis, the following main business processes are adopted to complete the online monitoring of ecological environment pollution data.

Step 1. Collect the emission concentration data of environmental pollution gases and carry out standardized processing.

Step 2. Determine the gas concentration. If the concentration is normal, store the data in the database server and directly enter the data analysis stage. On the contrary, video capture is implemented to record the current gas concentration. After giving an alarm, the current gas concentration data is stored and analyzed [36].

Step 3. The architecture system in the monitoring system is a B/s multilayer architecture system based on the three-layer architecture mode. In order to better meet the business needs, after dividing the application service layer, the application layer is divided at multiple levels according to the actual business needs. The obtained multilayer structure can improve the efficiency of development stage and code execution efficiency to a certain extent.

Step 4. Web-based application architecture Net technology features. The application service layer is divided into business layer, data layer, logic layer, and presentation layer, as shown in Figure 5.

According to Figure 5, the network topology of intelligent monitoring technology is mainly composed of the following components: (1)Monitoring server: the function of this component is to analyze the data collected by the monitoring equipment(2)Database server: the main function of the server is to store and generate, store the transmission data of monitoring equipment, and generate various information such as report, operation program source code, and data dictionary(3)Early warning server: when monitoring the operation status of each server and each equipment substation, once abnormal conditions are found, the warning report will be uploaded(4)Front end server: used to display port data such as web end and mobile end(5)Central server: as an important component of monitoring technology, the function of central server is to complete the processing and analysis of all data, the connection between interface and server, and the operation of environmental numerical model

4. Experimental Analysis

In order to verify the effect and feasibility of online monitoring of ecoenvironmental pollution data in the Internet environment, taking the five kinds of pollution data of nickel, chromium, lead, zinc, and mercury in the ecoenvironmental pollution monitoring data of a certain area as an example, this method sets it as the factor set of ecoenvironmental pollution degree evaluation. The classification information of pollution degree is shown in Table 2.

According to Table 2, when evaluating the degree of ecological environment pollution by this method, the evaluation set is , in which is no pollution, is light pollution, is medium pollution, and is heavy pollution. See Table 3 for the frequency of occurrence of statistical evaluation factors in the classification standard interval.

The above information data in Table 3 is used as the basic data for monitoring the degree of ecological environment pollution in this method to evaluate the degree of ecological environment pollution in this area.

In order to ensure the referential and authenticity of the experimental data, the following places will be set for experimental preparation: set the data sampling nodes: set the monitoring nodes in the teaching building, near the factory, in the residential room, and above the lake in an urban area of Fujian Province. Among them, the interior of the residence needs to ensure that there is no obvious pollution source, and it must be a nonnewly decorated house. The collected pollutants shall be treated according to the national safety supervision regulations, and the influence of external conditions such as wind speed, air temperature, air pressure, and humidity shall be considered. Before the actual sampling, check the air tightness of the monitoring node and calibrate it with the flow statistics method. If the error is greater than 5%, it needs to be replaced or repaired immediately to ensure the accuracy of the experimental data.

PM2 is given in the teaching building, near the factory, in the house, and above the lake in summer and winter 5. For the monitoring of concentration, the experimental results are shown in Figures 6 and 7, respectively.

It can be seen from Figure 6 that the concentration distribution of the four monitoring points based on the monitoring concentration in summer increased in the first 36 hours and remained stable in the follow-up. Among them, the concentration change of the overall monitoring nodes in the teaching building and residential room is distributed within the national standard, and the change is relatively stable. The pollution concentration near the factory and above the lake is quite different from the national standard. Under normal circumstances, the waste generated by the work of the processing plant needs to be treated before it can be discharged into the air. However, due to its large pollution source and large quantity, it cannot be completely removed even after certain control treatment, so there is still a certain amount of residue in the air, which affects the environmental quality and destroys the acid-base balance of the air.

Based on the monitoring results in Figure 7 in winter, the variation of concentration curve has a wide fluctuation range and a large gap between values compared with summer. This is because the decrease of temperature in winter makes the use frequency of various heating tools required by people’s life rise sharply, and its emissions gradually increase. With the gradual reduction of light, the photosynthesis of trees also weakens, and the absorption capacity of pollutants gradually decreases.

From the above monitoring results, it can be found that the monitoring effect of this paper is relatively excellent in summer, winter, or any place, which is consistent with the actual situation. The monitoring node has maintained a relatively stable monitoring rate and no abnormalities, and the overall working state is stable.

The correlation coefficients of regression equations were obtained by this method; reference [9] method and reference [10] method are compared. The specific results are shown in Figure 8.

After the above analysis, the comparison method of PM2.5 is specified for the first time, and it is adjusted appropriately. Therefore, the qualified index is set as follows: the correlation coefficient is ≥0.96. By observing Figure 8, it can be seen that all data based on the correlation coefficient meet the index requirements in Table 2 (≥0.94), and all are greater than 0.96. This method is close to the methods of reference [9] and reference [10], all within the standard deviation, which can show that the monitoring results of this method are in line with the actual data, are true and effective, and can provide 20-hour continuous monitoring results for the environmental pollution monitoring department and reduce the consumption of human and material resources.

5. Conclusions and Prospects

5.1. Conclusions

Through the effective participation of all parties in the supervision of the ecological environment, it is of great significance to the current online monitoring of ecological environmental pollution data. On the basis of previous research, the online monitoring of ecological environment pollution data in this paper has achieved more significant results. The specific conclusions are as follows: (1)The four monitoring points in teaching buildings and residences, near factories, and above the lake surface increased in the first 36 hours based on the distribution of monitoring concentrations in summer and maintained a stable trend thereafter(2)Compared with summer, the change of concentration curve has a wider fluctuation range and a larger gap between values. No matter it is summer, winter, or which location, the monitoring effect of this paper is relatively excellent, and it is in line with the actual situation. The monitoring node has maintained a relatively stable monitoring rate without abnormal conditions, and the overall working state is stable(3)The monitoring results of the method in this paper are in line with the actual data, are real and effective, and can provide monitoring results for the environmental pollution monitoring department, saving labor and time

5.2. Prospects

Ecoenvironmental pollution has become one of the most serious social problems in various regions. It not only directly restricts the sustainable development of the environment but also seriously hinders the healthy and sustainable development of the whole national economy. Ecological environmental pollution and its prevention and control will be one of the most important issues and urgent problems to be solved in the future environmental problems and economic development of the study area. Therefore, it is of great theoretical and practical significance to continuously carry out in-depth and comprehensive research on ecological environmental pollution.

The next work is mainly carried out from two aspects: theoretical research and empirical analysis. In terms of theory, we should focus on strengthening the basic theoretical research and then build a theoretical model and analysis framework that can effectively reflect the actual situation and law of pollution. In terms of empirical analysis, we should further start from four aspects: first, quantitatively consider the impact of relevant policies, regulations, market prices, and other socioeconomic factors on ecoenvironmental pollution and put forward relevant countermeasures and suggestions for the prevention and control of ecoenvironmental pollution; second, systematically study the relationship between production behavior, consumption behavior, and ecological environment pollution prevention and control; third, strengthen the horizontal comparison with other specific regions to improve the guiding significance of this study; and fourth, in the analysis of pollution regional differentiation, we should further strengthen the collection and sorting of cross-sectional data and focus on the temporal changes of pollution characteristics in each pollution type area. Finally, the following suggestions are put forward for the online monitoring of ecoenvironmental pollution data in the Internet environment: (1)Strengthen the development of circular economy and advocate a green lifestyle

The core of modern economic development is to save resources. Industrial economy and agricultural economy are closely related to natural resources. Therefore, we must scientifically optimize and improve the ecological environment governance model. The industrial structure must achieve coordinated development among regions, industries, urban and rural areas, and enterprises. Green technology must be used to reasonably integrate modern agricultural production with nature, make rational use of natural resources in the production chain, and make sustainable use of natural resources, so as to achieve circular development with social economy. (2)Enhance the level of supervision and management

In the construction of ecological civilization, the development of ecological environment is inseparable from the protection of natural environment. We must establish a three-dimensional governance model according to local conditions. Targeted laws and regulations need to be established to crack down on the behavior of polluting the ecological environment.

Data Availability

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Conflicts of Interest

The author declared no conflicts of interest regarding this work.

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Copyright © 2022 Bo Han. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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