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SMART WASTE MANAGEMENT: AI-BASED TRASH CLASSIFICATION SYSTEM
Effective waste management is essential in India to ensure environmental sustainability and safeguard public health. With rapid urbanization and a growing population, the volume of waste generated has increased significantly, placing immense pressure on traditional disposal systems. This has led to environmental pollution, ecosystem damage, and various health risks. Conventional waste management methods—such as manual sorting, rule-based categorization, and exporting waste—are increasingly proving to be inadequate. Manual sorting is time-consuming, labor-intensive, and prone to human error, while rule-based systems lack the flexibility to adapt to varied and changing waste types. Exporting waste, on the other hand, raises serious environmental and ethical concerns due to potential mishandling. To address these issues, this research leverages a large-scale image dataset containing millions of waste item images to build and assess robust waste classification models. It utilizes MobileNetV2 and a lightweight convolutional neural network (CNN) to develop an AI-driven system capable of accurately classifying different types of waste. This intelligent classification system can be integrated into smart bins and recycling infrastructures to automate the sorting process, ultimately improving recycling efficiency and minimizing environmental impact.
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