Cognitive Air Quality Systems: Quantifying AQI Levels Through AI and Time Series Modelling

Abstract

Air, vital for life and Earth's climate regulation, faces escalating threats from pollution. Prioritizing air quality is imperative for human health, environmental protection, and climate change mitigation. Achieving cleaner air requires global collaboration and sustainable practices. India's diverse landscapes, from the Himalayas to beaches, influence air quality, with forests serving as crucial carbon sinks. Rapid urbanization and deforestation present challenges, harming nature and public health. Combating pollution is strengthened through conservation and afforestation initiatives. This study employs artificial intelligence, machine learning, and IoT, providing an enhanced Air Quality Index (AQI) via a user-friendly interface, ensuring a disease-free future for younger generations. Government policies, stringent emissions norms, and cleaner fuels significantly impact air quality. Public awareness campaigns are pivotal. Validating the model using Python tools, correlation analysis uncovers pollutant-meteorological links. Data visualization exposes trends, forecasting predicts air quality, and cluster analysis identifies spatial patterns. Drawing from credible sources like the CPCB and World AQI, the analysis spans 2015-2022. Findings guide sustainable strategies, celebrating reduced pollutants while emphasizing the ongoing need for concerted efforts. Global cooperation remains paramount for fostering cleaner, healthier communities.