A Review on Smart Waste Segregation Systems for Sustainable Urban Environments

Abstract: With the escalating crisis of urban waste management, traditional methods of manual waste sorting are proving to be unsustainable, inefficient, and hazardous. This review paper explores the evolution and current state of smart waste segregation systems, which leverage automation, sensor technology, and the Internet of Things (IoT) to revolutionize how municipal solid waste is processed. These intelligent systems aim to autonomously classify and separate waste at the source into distinct categories such as wet, dry, and metallic, thereby enhancing the efficiency of recycling and resource recovery. This paper surveys various technological approaches, from basic sensor-based mechanisms controlled by microcontrollers like Arduino to advanced systems employing computer vision and Artificial Intelligence (AI) for more granular classification. By analyzing the methodologies, advantages, and limitations of existing models, this review highlights the critical role of automation in creating cleaner, healthier, and more sustainable urban ecosystems. The findings indicate that while significant progress has been made, future research should focus on improving accuracy, scalability, and cost-effectiveness to facilitate widespread adoption.