Air Pollution Monitoring and Prediction System for Sustainable Metropolitan Cities using Iot
Nagaraja G S1, Shreyas Srinath2, Reshma Jakabal3
1Nagaraja G.S*, Professor & Associate Dean, Dept of Computer Science & Engineering,R. V College of Engineering, ,Mysore Road, Bengaluru, Karnataka, India.
2Shreyas Srinath, Research Scholar, Dept of Computer Science & Engineering,R. V College of Engineering, Mysore Road,Bengaluru, Karnataka, India.
3Reshma Jakabal, Assistant Professor, Dept of Computer Science & Engineering, RNS Institute of Technology, Bengaluru, Karnataka, India, reshma
Manuscript received on January 26, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 3308-3312 | Volume-9 Issue-3, February 2020. | Retrieval Number: C6215029320/2020©BEIESP | DOI: 10.35940/ijeat.C6215.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In today’s world, the temperature of the environment is gradually rising. One of the main reasons for it is decreasing the quality of air mainly caused due to air pollution. There are many harmful substances present in the environment that is the cause of the declining quality of air. These pollutants get mixed along with the air and pollute the environment. The two air pollutants are considered here, CO2 and NO, to reduce air pollution, there is a need to know the number of pollutants, with the help of sensors in this experiment the level of pollutants are to be monitored and based on that a prediction mechanism is developed to determine the level of pollutants in the future. There are some machine learning concepts involved, K means clustering for classification of pollutants along with the S.V.M. (Support Vector Machine). With the successful prediction of the level of pollutants, the necessary counter measures can be adaopted.
Keywords: Air Monitoring, IoT, Machine Learning, Predictive Analysis, Support Vector Machine.