Internet of Things Based PM2.5(SMOG) Forecasting

computer engineering

Poor visibility due to SMOG(PM2.5) has triggered 30Percent increase in road accidents in INDIA in just last two days. According to MH-100, police emergency response centre, the number jumped from average 500 daily (since November 1) to 650 on November 7 and 8, 2019. In work, we propose to measure and monitor the fine dust (PM2.5) in outdoor environment to avoid road accidents and health hazards. Also, using the app of the smart phone which is the monitoring device users are not constrained to time and place, IoT (Internet of Things) technology, which is one of the most trending industrial technologies is used to measure outdoor PM2.5 Particles and airborne fine dusts using IoT devices (Fine dust sensors) and microcontroller, which is an embedded system are configured in hardware to precisely measure and collect data on fine dusts. Atmospheric particulate matter, such as PM2.5, contributes to air pollution negatively affecting human health and road accidents on highways. Many factors determine the change of PM2.5 concentration levels, which can be very sudden, nonlinear, and uncertain. Hence, traditional methods are not always suitable for predicting the exact amount of PM2.5 in the air. Effective forecasting of PM2.5 levels can tell people the air condition and support country’s sustainable development; hence, forecasting PM2.5 values has an important social and long-term economic significance. This study proposes a system for detecting the amount of PM2.5 and other pollutants in the air using Internet of Things technology and a cloud-based system model.

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