Air Quality Monitoring Using IoT and Machine Learning

Air pollution is a significant environmental concern that affects human health and well- being. To address this datasets to establish accurate models for air quality prediction and pollution classification. issue, an air quality monitoring system using IoT (Internet of Things) and ML (Machine Learning) techniques is proposed. The system aims to continuously monitor and analyze air pollutant levels in real- time, providing valuable insights for environmental management and public health.The system consists of air quality sensors deployed in various locations, collecting data on pollutants such as particulate matter, Gas/Smoke, carbon monoxide, metal oxide Benzene, and more. These sensors are connected to a central hub through wireless communication protocols, enabling data transmission to a cloud- based platform. The cloud platform serves as a repository for storing and processing the collected data.ML algorithms are employed to analyze the air quality data and develop predictive models.