Predictive Analysis and Data-Driven Approaches for Developing Sustainable Municipal Solid Waste Management Strategies in Smart Cities: A Case Study of Madurai

This study predicts the handling of trash in Madurai Smart City and proposes rules to improve the environment and health. A mixed-methods analysis was conducted using qualitative and quantitative data, including interviews with stakeholders, policy reviews, garbage pickup, processing metrics, and population growth estimates. Predictive analytics tools such as time series forecasting and machine learning models have been used to determine the long-term effectiveness of waste management strategies. Key findings include the placement of trash trucks, encouraging recycling through community involvement programs, and the utilization of creative waste-to-energy systems. This study emphasizes the need for government, people, and technology support for effective waste management. Predictive analysis can aid in strategic planning and dynamic policy decisions, enhance living conditions and make Madurai Smart City more environmentally friendly. This study highlights the importance of the government, people, and technology in implementing effective waste management strategies.