A Review on Various IOT Analytics Techniques for Air Pollution Detection in Fog Computing

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Ranjit Kaur, Pankaj Deep Kaur

Ranjit Kaur and Pankaj Deep Kaur. A Review on Various IOT Analytics Techniques for Air Pollution Detection in Fog Computing. International Journal of Computer Applications 169(2):1-4, July 2017. BibTeX

	author = {Ranjit Kaur and Pankaj Deep Kaur},
	title = {A Review on Various IOT Analytics Techniques for Air Pollution Detection in Fog Computing},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {169},
	number = {2},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {1-4},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume169/number2/27954-2017914588},
	doi = {10.5120/ijca2017914588},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Atmospheric contamination has deteriorated the health of plants and animals all over the globe. In particular, pollutants such as benzene(C6H6) has accelerated the rate of cancer among human beings. Therefore, accurate evaluation of the pollutant in the atmosphere is necessary by traffic supervision in urban areas. To reduce atmospheric contamination, an effective mobile strategy planning must be developed. Currently, the atmospheric contamination is measured using spatially scattered networks with limited sensors. Although, these networks and sensors can evaluate the air pollution accurately, however the sensor expenses and size might limit the operational efficiency. In this paper we discuss about the various techniques of IOT and also discuss the detection of air pollution in fog computing. The overall objective of this paper is to detect the air pollution in IOT and we analyze IOT performs better than other techniques.


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Foggy or haze images; visibility restoration; air light; dark channel prior.