Optimal selection and challenges of municipal waste management system using an integrated approach: a case study

Efficient waste management is crucial for maintaining a clean and sustainable environment in Indian cities. Patna faces significant waste management challenges due to rapid population growth and urbanization. This has resulted in increased waste generation, straining the current waste management system. The state of Bihar ranks poorly in waste-management-based Environmental Performance, highlighting the need for improvement. Although around 4281.27 TPD of garbage is generated, only 4013.55 TPD is collected. Insufficient information regarding waste processing, landfilling, and technology adoption exposes critical gaps in solid waste management, including limited landfill facilities, inadequate technology implementation, and inadequate monitoring. Effective waste management is crucial for ensuring the sustainability and quality of life in Patna. To address these challenges, the implementation of Information and Communication Technologies (ICTs) and the Internet of Things (IoT) in waste management is proposed. This study focuses on evaluating the most suitable smart waste management system for Patna Municipal Corporation. By employing an MCDM model with fuzzy logic-based TFN, the authors identified the optimal MWM alternative based on economic, technical, environmental, and social criteria. Findings unequivocally establish the IoT-based Door-to-Door system (Ʌ1) as the most effective and economical solution for MWM in urban settings like Patna, characterized by a proximity coefficient (PCi) = 0.942809. Furthermore, Social acceptance (ӄ2) emerged as the most influential criterion with a weight of 0.19375. This system not only promises enhanced operational efficiency for municipalities but also offers significant environmental and social benefits, including waste reduction, improved public health, and heightened community engagement. A sensitivity analysis was conducted to validate the robustness of the proposed method. Notably, the IoT-based system demonstrated a higher sensitivity to cost changes, affirming its superiority in adapting to economic considerations. This insight is pivotal for decision-makers prioritizing cost efficiency in waste management solutions.