Smart air pollution management in Smart Indian Cities: a narrative review
TL;DR
It is suggested that coordinated AI-enabled governance and targeted technologies can substantially reduce air pollutant levels, enhance regulatory efficiency and support healthier, climate-resilient urban environments in India.
Abstract
Rapid urbanization, industrialization and motorization have intensified air pollution challenges in Indian cities, posing significant risks to public health and sustainable development. Conventional air quality management approaches, largely reactive and static, are insufficient to address the complex and dynamic nature of urban air pollution. This manuscript reviews the role of artificial intelligence (AI) and environmental technologies in advancing air pollution management within the framework of India’s Smart Cities Mission and the National Clean Air Programme (NCAP). AI-driven techniques, including machine learning and deep learning, enable improved air quality forecasting, source apportionment, hotspot identification and decision-support systems through integration of multi-source data from sensors, satellite observations and meteorology. The study further examines environmental technologies targeting pollution reduction across transport, industrial, construction, indoor and outdoor environments, including electric mobility, advanced emission controls, carbon capture, dust mitigation, outdoor air purification and nature-based solutions. An integrated smart city framework is proposed linking data, AI analytics, interventions, monitoring and health-focused outcomes. The findings suggest that coordinated AI-enabled governance and targeted technologies can substantially reduce air pollutant levels, enhance regulatory efficiency and support healthier, climate-resilient urban environments in India.