Waste Revolution: A Web-Based Waste Classification and Disposal System using CNN

The advancement of technology and innovation in universities is essential for promoting sustainable development. At Universiti Sultan Zainal Abidin (UniSZA), this commitment is reflected in our efforts to integrate sustainability across research, education, campus practices, and policy advocacy. UniSZA serves as a hub for innovation and research, significantly contributing to sustainable development through the development of new technologies and solutions aimed at addressing environmental, social, and economic challenges. Our focus includes key areas such as waste management, where there is a growing need for innovative solutions to enhance efficiency and sustainability. In response, we propose the smart waste management project, which seeks to address current gaps in waste management practices. This initiative involves developing a web-based designed to improve waste collection efficiency, enhance recycling accuracy, and foster a culture of sustainability within the UniSZA community. The app will leverage real-time data to optimize waste collection routes and schedules, employ Convolutional Neural Network (CNN) for image classification to assist users in accurately identifying and sorting recyclables materials accurately, and engage the community through interactive challenges and incentive programs. Experimental results indicate that the CNN model achieved an image classification accuracy of 92%, leading to an estimated 30% improvement in recycling accuracy during initial testing. These findings demonstrate the potential of AI-driven tools in enhancing waste management operations. By integrating these advanced features, we aim to contribute to more effective waste management and a stronger commitment to sustainability. This project aligns with global sustainability goals and addresses the need for innovative, technology-driven solutions in waste management. The web's development will be supported by comprehensive research and user feedback, ensuring that it meets the needs of waste management operators and community members alike. The outcomes are expected to provide valuable insights into improving waste management practices and advancing sustainable development within the UniSZA community.