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Enabling Air Pollution Prediction through IoT and Machine Learning

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Enabling Air Pollution Prediction through IoT and Machine Learning


Suraj Kapse | Akshay Kurumkar | Vighnesh Manthapurwar | Prof. Rajesh Tak



Suraj Kapse | Akshay Kurumkar | Vighnesh Manthapurwar | Prof. Rajesh Tak "Enabling Air Pollution Prediction through IoT and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3, April 2020, pp.967-972, URL: https://www.ijtsrd.com/papers/ijtsrd30739.pdf

Large scale industrialization and the increase in the number of factories and industries across major cities in the world have been contributing to the decreasing air quality. This is since a rapid increase in the population across the world has prompted the majority of the companies across the globe to adopt mass-production activities to keep up with the increasing demand. This is evident in the fact that most of the big cities have an increasing number of cases of respiratory illnesses and asthmatic symptoms in the populous. Therefore, there is an urgent need to address these issues to provide a better environment and reduce such incidences. The Internet of Things or IoT platform is a quite a promising platform for this approach which has been getting increasingly affordable and approachable. Therefore, in the approach stipulated in this research, the IoT platform has been utilized in addition to the Machine Learning paradigms to achieve accurate air quality predictions. The proposed methodology utilizes K nearest neighbors and Linear Regression, along with the Hidden Markov Model for effective Pollution level estimation.

Prediction, Hidden Markov model, Regression Analysis, Shannon Information gain estimation, Root mean square error


IJTSRD30739
Volume-4 | Issue-3, April 2020
967-972
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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