Applications of Artifical Intelligence for Municipal Solid Waste Management in India: Another Look

The Municipal Solid Waste (MSW) generation rate is exponentially expanding in India with the urban areas contributing significantly due to rapid population growth and changing living styles. The real extent of waste recycling is only 13-20% despite efforts under various initiatives such as the Swachh Bharat Mission, leaving millions of tons end up in landfills. There are many initiatives in the community-level as well as Urban Local Body (ULB)-level, but their efforts lack efficiency and preparedness for handling the huge variability in the whole cocktail of wastes. Viewing the growth and transformative potential of Artificial Intelligence (AI) in various fields of decision-making, this review explores the managerial perspectives of AI in effectively managing MSW management apart from the technological purview. The application of AI technologies, including machine learning, computer vision, and IoT integration have demonstrated success in waste characterization, route optimization, recycling, and waste-to-energy conversion. Several case studies from the Indian cities, such as Pune and Bengaluru highlight the implications of AI-driven innovations, while comparisons with global practices in cities such as Tokyo, underscore the opportunities for improvement. The study categorically identifies the challenges, such as inconsistent data collection, high implementation costs, and policy gaps that hinder widespread adoption. Considering the goal of achieving sustainability through circular economy, this review emphasizes the role of AI in reducing landfill dependency, optimizing resource recovery, and minimizing environmental impact. We propose that it is possible to revolutionize India?s waste management systems by aligning AI solutions with policy frameworks and fostering public-private partnerships for providing strategic insights for the stakeholders.