AI-Driven E-Waste Disassembly System
Abstract
With the global population steadily increasing, the use of electronic devices is also rising, resulting in a significant accumulation of electronic waste (e-waste). This paper presents an intelligent robotic system designed to autonomously disassemble electronic devices and identify ewaste using a machine learning (ML) model trained entirely from scratch.
Unlike previous disassembly robots that relied on static linebased or rule-based methods—limiting flexibility— our robot leverages a flexible ML-based model trained on diverse device types, allowing it to adapt to various forms of e-waste. Inspired by Apple’s “Daisy” robot, which disassembles iPhones and other Mac devices, our system enhances automation and sustainability in e-waste management.
By deploying our robotic system, we aim to improve recycling efficiency, reduce hazardous impacts on human health, and minimize environmental damage.
References
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