A Survey on Pollution Monitoring Using Sensor Networks in Environment Protection

Luo, Xu; Yang, Jun

doi:10.1155/2019/6271206

Cited by 30 publications

(9 citation statements)

References 59 publications

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“…By monitoring the electricity consumption during six production processes of typical sewage discharge factories in the jurisdiction, it was found that the major production periods of large sewage discharge enterprises in November 2018 were concentrated in the following four sections: [4][5][6][7][8][9][10][11][12], [15][16][17][18][19][20][21][22][23], [24][25] and [27][28][29][30]. This performance was consistent with the time section when the concentration of pollution factors was increased in our urban environmental information monitoring analysis.…”

Section: Resultssupporting

confidence: 71%

“…Past research has established the negative health effects originating from the exposure to these pollutants. Consequently, there is an urgent need to monitor and control the concentrations of these gaseous pollutants in factories and for large-scale deployment of sensor technologies to enable monitoring factory environmental quality (FEQ) with high temporal and spatial resolution in factories [4]. However, currently available solutions are scarce and too costly for large installations [5].…”

Section: Introductionmentioning

confidence: 99%

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A Wireless Sensor Network for Monitoring Environmental Quality in the Manufacturing Industry

et al. 2019

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Urban industrial plant areas are highly concentrated, and air pollution is increasingly serious. The quantity of outdoor air quality monitoring sites is insufficient. Aiming at the above questions, related studies propose solutions that use relatively cheap equipment networking to collect pollution data and accurately analyze local monitoring information. In this paper, a new type of outdoor air quality monitoring system is studied and preliminarily practiced and has proven certain feasibility and applicability. The main contributions of this paper are: first, we improve the network layout by employing the Zigbee network, which is combined with factory characteristics, and collected data on carbonic oxide, nitrogen dioxide, sulfur dioxide, ozone, particulate matter, temperature, and humidity. And then, to establish the dilution coefficient and diffusion coefficient of pollution diffusion, we adopt air movement as the energy model and, by utilizing the method of pollution traceability, achieve the complete coverage pollution monitoring of the whole city by local monitoring sites. Finally, we propose an improved long short-term memory (LSTM) method to predict the pollution period of urban air quality. The experimental results show that the improved LSTM prediction model has strong applicability and high accuracy in the period prediction of pollution weather. Meanwhile, by analyzing the specific case in detail, we prove that air pollution in the city is mainly caused by the manufacturing industry. We conclude that it will make a great contribution to the atmospheric environment protection of cities by using weather quality prediction to dynamically adjust the production.

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Section: Resultssupporting

confidence: 71%

Section: Introductionmentioning

confidence: 99%

A Wireless Sensor Network for Monitoring Environmental Quality in the Manufacturing Industry

et al. 2019

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“…We know that the precise determination of trace gases in the air is a pioneering requirement on the measurement technology to improve the quality of diagnosis and treatment. Possible fields of application are developed for this work alongside the sensor to the respiratory gas and pollutant analysis [3], [4]. Often the substance to be tested has concentrations in such a small amount that they can be determined only qualitatively with advanced technical equipment which is quite costly in terms of expense and complexity [5], [6].…”

Section: Introductionmentioning

confidence: 99%

“…In this manner, they are specifically valuable for various purposes in organic analysis [11], [12]. Explicit methods in optics empower confocal laser input Tomography that empowers doctors to comprehend the dynamics of their sick persons using portraits and pictures [3], [5]. One of the fundamental system to diagnose has been the parameter of noise in optics which enables multivarious analysis [13].…”

Section: Introductionmentioning

confidence: 99%

Highly Sensitive Microsensor Based on Absorption Spectroscopy: Design Considerations for Optical Receiver

et al. 2020

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The development of a biomedical sensor involves an extremely sensitive optoelectronics system whose foundations lie on intracavity absoprtion spectroscopy. In order to make it convenient for technical reasons to use this application based utility, we implement dual mode competition. All of the components in this system must be investigated in detail. This work concerns with the design of the optical receiver which is mandatory to understand and analyze the received signal. This has been effectively done by designing an inexpensive system which replaces the existing Agilent based setup. Next, the performance of the system has been investigated by using an important parameter Relative Intensity Noise (RIN). The variation of injection current and temperature and their subsequent effect on RIN has been comprehensively examined. This has been enhanced by an investigation of RIN as subject to the mode positions (values of wavelengths) at which the framework is being operated. Through these considerations, the system's behaviour is understood in a much better way as they lead to an improvement in the sensor's realization with high sensitivity and stability.

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“…The energy was maintained by the hierarchical routing protocol in WAPMS. Luo, X et al, [16] surveyed on pollution monitoring using sensor network in protection of the environment. In addition, the sensor and pollution method was studied.…”

Section: Fig 3 Occupancy Characteristics [3]mentioning

confidence: 99%

An Effective Energy and Robust Routing Methods for Air Pollution Data Monitoring in WSN

2020

IJRTE

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The world is facing major challenges due to the progress in technology. Usually, science has also both advantages and disadvantages. The emerged technology creates environment monitoring systems that assisted for the detection and verification of harmful objects. The automatic system is also being cause of pollution in several ways. So, the requirements have been increased to introduce a system to control the pollution. AP (Air pollution) is one of the most pivotal issues that is affecting the living souls. The wireless sensor networks have found a great application in the area of air quality monitoring. In simple terms, a WN (wireless network) is a collection of sensor nodes that communicate by radio signals or waves and detects crucial data which is used to detect the pollutants from the air. WSN routing protocols are specifically accessed for this purpose, such as EEUC, LEACH, DESCA and so on. In this paper, the focus is to bring forth the basic concepts of air pollution detection and some relevant data mining techniques that helped to make a successful air pollution detection system. In this paper, define an artificial intelligence field-based energy-efficient and novel protocol method for the network called Energy-Efficient and Robust Routing Method for air pollution monitoring in WSNs. In this method, sensor network is trained a large database comprising almost all scenes to create the system more efficient, reliable and effective in the atmosphere. In this method, works to increase the lifespan of the network and improve the energy consumption parameter. In experimental result shows that it output ELDC and some other routing protocols such as LEACH and E-LEACH etc.

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A Survey on Pollution Monitoring Using Sensor Networks in Environment Protection

Cited by 30 publications

References 59 publications

A Wireless Sensor Network for Monitoring Environmental Quality in the Manufacturing Industry

A Wireless Sensor Network for Monitoring Environmental Quality in the Manufacturing Industry

Highly Sensitive Microsensor Based on Absorption Spectroscopy: Design Considerations for Optical Receiver

An Effective Energy and Robust Routing Methods for Air Pollution Data Monitoring in WSN

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