Real-time sorting of plastic waste for pre-cleaning recycle

Name: Kuljira Jaruprathai

Organization : King Mongkut's University of Technology Thonburi. Institute of Field Robotics

Email : kuljira.jaru@kmutt.ac.th

Name: Prakrankiat Youngkong

Organization : King Mongkut's University of Technology Thonburi. Institute of Field Robotics

Email : prakrankiat.you@mail.kmutt.ac.th

LCSH: Plastic waste -- Recycling

LCSH: Refuse and refuse disposal -- Recycling

LCSH: Real-time data processing

LCSH: Salvage (Waste, etc.)

Abstract: Despite Thailand’s longstanding efforts in plastic waste sorting, a substantial portion remains unrecycled. This paper introduces an innovative approach utilizing the YOLOv8s deep learning algorithm for real-time plastic waste sorting, specifically targeting five categories: bottles (left and right), glass (left and right), and food containers. The dataset comprises 408 images of everyday plastic waste, including grayscale variations. Our experimental results demonstrate an average F1-score of 85%, precision of 96.6%, precision-recall of 89%, and a confusion matrix showing classification confidence levels of 100% for bottle left and food containers, 87% for bottle right and 86% for glass right.

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2025

Modified: 2025-06-17

Issued: 2025-06-17

บทความ/Article

application/pdf

BibliograpyCitation : In Electrical Engineering Academic Association (Thailand) and King Mongkut's University of Technology North Bangkok. Department of Electrical and Computer Engineering. 13th International Electrical Engineering Congress (iEECON 2025) (P06205). Bangkok : Electrical Engineering Academic Association (Thailand), 2025

eng

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