Automatic Waste Segregation System and Environment Awareness Application

Abstract

Waste management is one aspect of Environmental Sustainability which is an increasing global challenge and maintaining waste on a global scale, Waste management is a key part in achieving Sustainable Development Goals. This paper proposes an Artificial Intelligence based Waste Classification System using Deep Learning Technologies in the derivation of an Interactive Waste Classification System with a purpose, to enhance users' awareness of their responsibilities regarding their own waste disposal practices through the use of gamification principles incorporated into this system. The Waste Classification System uses a Convolutional Neural Network in conjunction with MobileNetV2 architecture to classify and distinguish between 12 different categories of waste: plastic, paper, metal, glass, cardboard, biological waste, batteries, textiles, footwear, and general rubbish. Our proposed Intelligent Waste Classification System achieved 95.4% classification accuracy when assessed using the sample validation data set. All of these gamification components combined to create a platform capable of building long-term user engagement. In conjunction to the vast number of Eco-Points users can accumulate and accumulate progressively achieved Badge levels users can receive, Users gain virtual status when they compete on leaderboards, and track their progress visually using a user-friendly interface. The Intelligent Waste Classification System is accessible to all users through the use of the web browser, while the Intelligent Waste Classification System also provides Personalized and tailored recycling guidance via an Intelligent Conversational Chatbot. The Intelligent Waste Classification System contains an Administration Dashboard feature to monitor user behavior and to gather system usage statistics, and an Automated Email Notification System for community engagement. Our findings and extensive evaluation indicate that the application of artificial intelligence combined with principles of behavioral psychology will lead to a much more effective way of educating users about Waste Management Practices, and developing a practical method for implementing these practices.