Open AccessApplying data mining technique to predict trends in air pollution in Mumbai
Author(s) -
Jayakumar Sadhasivam,
V. Muthukumaran,
J. Thimmia Raja,
V. Vinothkumar,
R Deepa,
V. Nivedita
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1964/4/042055
Subject(s) - air pollution , air quality index , residual , particulates , pollution , environmental science , software , meteorology , pollutant , air pollutants , air monitoring , data mining , computer science , statistics , geography , mathematics , environmental engineering , algorithm , ecology , chemistry , organic chemistry , biology , programming language
Prediction of air quality is a topic of great interest in air quality research due to direct association with health effect. The prediction provides pre-information to the overall population of the area about the status of pollution on which they can take precautionary measures and can protect their health. The problem arises when the level of SO2, NO2 and residual suspended particulate matters in the air increases than that of theirs restricted level. In this paper, the Prophet Algorithm, open source software, is applied to predict the trend of air pollution in the city of Mumbai, Maharashtra. The Prophet is machine learning algorithm to forecast and also to predict time series data. It is based on additive model where non-linear trends are fit with yearly and weekly seasonality. The graphical results are generated after using this algorithm which shows the trending pattern of the pollutants in the air of Mumbai.