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ECO BRAIN

NH M Faizal¹, AB Saad², NFA Abdullah³,

QI M Latifi⁴, NS M Tajul⁵, NJ Mahazir^6,*

^1,2,3,4,5,6SMK Sri Kurau, Jalan Siakap, 34300 Bagan Serai, Perak, Malaysia

*  [email protected]

ABSTRACT

Recycling plays a crucial role in environmental sustainability, yet many individuals lack awareness of its importance and often sort recyclable waste incorrectly. This improper waste classification leads to increased pollution, inefficiencies in the recycling process, and contamination of recyclable materials. To address this issue, this research aims to develop an AI-based model capable of accurately classifying recyclable waste, specifically glass, plastic, and paper. The model utilizes machine learning techniques trained on a dataset of various waste materials to enhance classification accuracy. The principal results demonstrate that the AI model significantly reduces sorting errors and improves efficiency in waste management. By implementing this technology, recycling facilities can process waste more effectively, reducing environmental impact and promoting better recycling habits within communities. This research highlights the potential of artificial intelligence in solving real-world environmental problems and encourages wider adoption of technology-driven solutions for sustainability.

Keywords:Enviroment, Garbage can, Artificial Intelligence, Cleanliness, Image Recognition