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Development of Machine Learning-Based Predictive Models for Air Quality Analysis and Prediction

Ashok Shah1 , Prayash Rimal2 , Dev Bhasker Singh3 , Jagadeesh B N4

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-15 , Page no. 32-35, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si15.3235

Online published on May 16, 2019

Copyright © Ashok Shah, Prayash Rimal, Dev Bhasker Singh, Jagadeesh B N . 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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IEEE Style Citation: Ashok Shah, Prayash Rimal, Dev Bhasker Singh, Jagadeesh B N, “Development of Machine Learning-Based Predictive Models for Air Quality Analysis and Prediction,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.15, pp.32-35, 2019.

MLA Style Citation: Ashok Shah, Prayash Rimal, Dev Bhasker Singh, Jagadeesh B N "Development of Machine Learning-Based Predictive Models for Air Quality Analysis and Prediction." International Journal of Computer Sciences and Engineering 07.15 (2019): 32-35.

APA Style Citation: Ashok Shah, Prayash Rimal, Dev Bhasker Singh, Jagadeesh B N, (2019). Development of Machine Learning-Based Predictive Models for Air Quality Analysis and Prediction. International Journal of Computer Sciences and Engineering, 07(15), 32-35.

BibTex Style Citation:
@article{Shah_2019,
author = {Ashok Shah, Prayash Rimal, Dev Bhasker Singh, Jagadeesh B N},
title = {Development of Machine Learning-Based Predictive Models for Air Quality Analysis and Prediction},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {15},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {32-35},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1196},
doi = {https://doi.org/10.26438/ijcse/v7i15.3235}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i15.3235}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1196
TI - Development of Machine Learning-Based Predictive Models for Air Quality Analysis and Prediction
T2 - International Journal of Computer Sciences and Engineering
AU - Ashok Shah, Prayash Rimal, Dev Bhasker Singh, Jagadeesh B N
PY - 2019
DA - 2019/05/16
PB - IJCSE, Indore, INDIA
SP - 32-35
IS - 15
VL - 07
SN - 2347-2693
ER -

           

Abstract

One of the biggest environmental problems right now is air pollution. Air quality is needed to be consistently monitored and assessed to ensure better living conditions. The U.S. Environmental Protection Agency (EPA) uses the air quality index (AQI) to standardize the air quality. However, AQI requires precise and accurate sensor readings and complex calculations, making it not feasible for portable air quality monitoring devices. The aim of this paper is to find an alternative way of monitoring and characterizing air quality through the use of integrated gas sensors and building predictive models using machine learning algorithms that can be used to obtain data-driven solutions to mitigate the risk of air pollution.

Key-Words / Index Term

AQI(Air Quality Index),Data Cleaning, Softmax Function

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