Towards Building a Scalable IoT based System for Carbon Monoxide Monitoring and Forecasting

Abstract

Air pollution, indoor and outdoor is one of the major issues in smart cities, which cannot be ignored. Carbon monoxide (CO) is the severe contributor in in-house air pollution and reason behind many health hazards. Monitoring of CO is very urgent need in smart cities. Internet of Things is emerging area and provides economic solution to air quality pollution parameter monitoring compared to fixed expensive monitoring stations. In the proposed system, Electro chemical sensor is used to measure the in-house carbon monoxide level. The periodically sensed data is published to the mosquito MQTT broker. The observed CO parameter data fetched are visualised in graph form at server and logged in CSV file for analytics. Deep learning (RNN) based model is implemented for forecasting of CO level.