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Reseach Article

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

by Ranjit Kaur, Pankaj Deep Kaur
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 169 - Number 2
Year of Publication: 2017
Authors: Ranjit Kaur, Pankaj Deep Kaur
10.5120/ijca2017914588

Ranjit Kaur, Pankaj Deep Kaur . A Review on Various IOT Analytics Techniques for Air Pollution Detection in Fog Computing. International Journal of Computer Applications. 169, 2 ( Jul 2017), 1-4. DOI=10.5120/ijca2017914588

@article{ 10.5120/ijca2017914588,
author = { Ranjit Kaur, 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 = { Jul 2017 },
volume = { 169 },
number = { 2 },
month = { Jul },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume169/number2/27954-2017914588/ },
doi = { 10.5120/ijca2017914588 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:16:14.838281+05:30
%A Ranjit Kaur
%A Pankaj Deep Kaur
%T A Review on Various IOT Analytics Techniques for Air Pollution Detection in Fog Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 169
%N 2
%P 1-4
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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.

References
  1. Atzori, Luigi, Antonio Iera, and Giacomo Morabito. 2010The internet of things: A survey.
  2. Bostock, Michael, Vadim Ogievetsky, and Jeffrey Heer. 2011D³ data-driven documents. IEEE transactions on visualization and computer graphics.
  3. Buyya, Rajkumar, et al. 2009Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility.
  4. Castronova, Anthony M., Jonathan L. Goodall, and Mostafa M. Elag.2013 Models as web services using the open geospatial consortium (ogc) web processing service (wps) standard.
  5. Christin, D., Reinhardt, A., Mogre, P.S., Steinmetz, R. 2009 Wireless sensor networks and the internet of things: selected challenges.
  6. Christodoulou, S., et al. 2010Wireless sensor networks for water loss detection.
  7. Wong, Brandon P., and Branko Kerkez. 2016Real-time environmental sensor data: An application to water quality using web services.
  8. Diamond, Dermot, et al. 2008 Wireless sensor networks and chemo-/biosensing.
  9. Díaz, Laura, et al. 2013 Publishing sensor observations into Geospatial Information Infrastructures: A use case in fire danger assessment. Environmental modelling & software.
  10. Gall, Heather E., Chad T. Jafvert, and Byron Jenkinson. 2010 Integrating hydrograph modeling with real-time flow monitoring to generate hydrograph-specific sampling schemes.Journal of hydrology .
  11. Gartia, Manas Ranjan, et al. 2012 The microelectronic wireless nitrate sensor network for environmental water monitoring. Journal of Environmental Monitoring.
  12. Gronewold, Andrew D., et al. 2013 A dynamic graphical interface for visualizing projected, measured, and reconstructed surface water elevations on the earth's largest lakes. Environmental modelling & software.
  13. Gubbi, Jayavardhana, et al. 2013 Internet of Things (IoT): A vision, architectural elements, and future directions.Future generation computer systems.
  14. Jin, Ning, et al. 2010 A novel design of water environment monitoring system based on wsn. Computer Design and Applications (ICCDA).
Index Terms

Computer Science
Information Sciences

Keywords

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