IOT Based Air Quality Prediction System Using...

IOT Based Air Quality Prediction System Using Machine Learning

Author Name : Mr. J. Jerin Jose, M. Surendra, S. Mahammed Salauddin, P. Sai Dileep, B. Sri Ramya

ABSTRACT

In recent years, air pollution has reached catastrophic levels and is rapidly getting worse. We suggest a solution to this issue that combines IoT and Machine Learning (ML), which will reliably identify current levels of air pollution as well as forecast future levels. The proposed solution consists of two components: a software model and an IoT device with four sensors connected to a processing unit. By detecting Particulate Matter, Carbon Monoxide, Ammonia, and sound the sensors can monitor the condition of the air around us. The data from the correctly calibrated sensors is processed by a microcontroller and sent to real-time cloud storage via a Wi-Fi module.The data is then retrieved and examined by a distant server. We then use the data to identify Particulate Matter as the main contaminant. Then, with excellent accuracy, we anticipate the pollution levels from dangerous gases and the Air Quality Index (AQI) of the following day using the Autoregressive Integrated Moving Average (ARIMA) model.

KEYWORDS: Air Pollution, Quality Index, Micro controller, Processing, Monitor