Abstract: The rapid growth of electronic devices has led to an alarming rise in electronic waste (e-waste), posing significant environmental and health hazards while also resulting in the loss of recoverable valuable materials. To address this challenge, SmartBinX introduces an intelligent, AI-driven framework that integrates Internet of Things (IoT) sensing, computer vision, and Generative Artificial Intelligence (GenAI) for efficient e-waste assessment, classification, and reuse optimization. The proposed system employs smart sensors and machine learning algorithms to measure and evaluate the material composition of discarded electronic products such as laptops, smartphones, and circuit boards. Generative AI models are further utilized to generate disassembly instructions, predict potential reuse pathways, and optimize recycling processes based on material recovery value.

Keywords: Electronic Waste (E-waste), Smart Waste Management, SmartBinX, Internet of Things (IoT), Computer Vision, Generative Artificial Intelligence (GenAI), Machine Learning, Material Composition Analysis, E-waste Classification.

Downloads: | DOI: 10.17148/IARJSET.2025.121236