Intelligent Air Pollution Prediction System using Internet of Things (Iot)
R. Udaya Bharathi1, M.Seshashayee2

1R.Udaya Bharathi*,  Research Scholar, Department of Computer Science, GITAM (Deemed to be University), Visakhapatnam, (Andhra Pradesh), India.
2Dr. M. Seshashayee, Assistant Professor, Department of Computer Science, GITAM (Deemed to be University), Visakhapatnam, (Andhra Pradesh), India.
Manuscript received on September 20, 2019. | Revised Manuscript received on October 05, 2019. | Manuscript published on October 30, 2019. | PP: 402-412 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9394109119/2019©BEIESP | DOI: 10.35940/ijeat.A9394.109119
Open Access | Ethics and Policies | Cite | Mendeley
© 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: The internet of Things (IoT) is a path of action interconnected computes multiple procedures, mechanical along with sophisticated machines, things, and individuals to facilitate be certain remarkable identifiers and the ability of trade data over a framework lacking foreseeing human to human and human to machine correspondence, in these paper, an Internet of Things base framework is proposed, in favor of observing natural air contamination and forecast. This framework is able to exist used for observing air contaminations of specific zone and toward Air Quality examination just as gauging the air quality. We Proposed new framework resolve concentrate scheduled the observing of air contaminations, using the blend of IoT with Artificial Intelligence called Artificial Neural Network, and additional explicitly Long Short Term Memory (LSTM). The point in this paper is to discover the best expectation and prediction model for rise or fall of the specific air poisons like O3 , NO2 , SO2 , and CO which are altogether viewed as destructive as indicated by WHO guidelines.
Keywords: Air pollution, Weather, Internet of Things, ANN, Weather Forecasting.