Prediction of Area Climate and Air Pollutants Using Deep Learning

Abstract

In this paper we propose a Iot-based Sensor Network (IOTSN)- based air quality
framework (IOTSN-AQMS) for urban population. The structure includes a lot of gas sensors
(SO2, CO2, and NO2) that are conveyed on stacks and foundation of a IOT module SN and a
central server to support both short-term real-time incident management and a long-term
efficient planning. The build would utilize open-equipment open programming gas
detecting proficient bits made by us.
These bits would use the ZigBee correspondence convention and give a working ease
observing framework using least effort, low information rate, and low
power remote correspondence innovation. The proposed checking framework can be
exchanged to or shared by different applications. We likewise present a basic however
proficient bunching convention named from now on " Regression Protocol for Air Sensor
arrange" (RPAS) for the energy consumption, network lifetime, and the rate at which data
is communicated