Abstract
Abstract- Efficient waste management is crucial for sustainable urban living. However, challenges such as improper segregation, low recycling rates, and reliance on manual systems hinder progress toward environmental goals. This paper introduces EcoSort AI, an AI-driven waste management solution that combines computer vision, IoT technologies, and machine learning to automate and optimize waste segregation. Leveraging convolutional neural networks (CNNs), the system identifies, classifies, and sorts waste materials into appropriate categories, ensuring improved recycling rates and reduced landfill burden. EcoSort AI features IoT-enabled smart bins for real-time classification and integrates seamlessly into existing urban infrastructures. Experimental results demonstrate significant improvements in sorting accuracy, efficiency, and public engagement. Index Terms- Waste segregation, artificial intelligence, IoT-enabled bins, CNNs, smart cities, recycling optimization, sustainable development.
Published Version
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