EcoCycle: A Deep Learning-Based Waste Categorization and Management System for Sustainable Smart Cities

Abstract : Waste management is a critical environmental and economic issue worldwide. Existing waste segregation ac- tivities are inefficient, resulting in high landfill contributions and environmental contamination. In this paper, an artificial intelligence-based waste categorization and management system, EcoCycle, is proposed that utilizes deep learning models like VGG16, ResNet50, and DenseNet121 for automatic classification of waste materials. EcoCycle is equipped with a gamification system based on mobile, a marketplace for recyclables supported by blockchain, and an IoT-based network of intelligent bins for real-time monitoring. Experimental results show 92.36% classification accuracy with DenseNet121, which is improved compared to other implementation results. User survey with 500 users shows a 98% positive effect on user experience and increased awareness about sus- tainability issues. The proposed system contributes significantly towards processes related to circular economies and the goals of smart city initiatives, and it has high global applicability potential for urban waste management systems.