IoT-Based Air Quality Monitoring System with Machine Learning for
  Accurate and Real-time Data Analysis
Hemanth Karnati
Air pollution in urban areas has severe consequences for both human health
and the environment, predominantly caused by exhaust emissions from vehicles.
To address the issue of air pollution awareness, Air Pollution Monitoring
systems are used to measure the concentration of gases like CO2, smoke,
alcohol, benzene, and NH3 present in the air. However, current mobile
applications are unable to provide users with real-time data specific to their
location. In this paper, we propose the development of a portable air quality
detection device that can be used anywhere. The data collected will be stored
and visualized using the cloud-based web app ThinkSpeak.
  The device utilizes two sensors, MQ135 and MQ3, to detect harmful gases and
measure air quality in parts per million (PPM). Additionally, machine learning
analysis will be employed on the collected data.