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Smart Plastic Classification System Using Python
Subject area: Science,Engineering and Technology · Area of research: Machine Learning
Abstract
This project presents a Smart Plastic Classification System that automatically detects and classifies plastic waste using a YOLO-based deep learning model. Images of plastics are captured and processed to identify types such as PET, HDPE, PVC, LDPE, PP, and PS. The system improves recycling efficiency by reducing manual sorting and increasing accuracy. Results show fast and reliable plastic identification, making the solution useful for waste management and environmental sustainability.
References
[1] J. Redmon and A. Farhadi, “YOLO: Real-Time Object Detection,” arXiv preprint arXiv:1506.02640, 2016.
[2] G. Jocher et al., “Ultralytics YOLO Models and Documentation,” Ultralytics, 2023. Available: https://ultralytics.com
[3] OpenCV Developers, “OpenCV: Open Source Computer Vision Library,” https://opencv.org
[4] NumPy Developers, “NumPy: Scientific Computing with Python,” https://numpy.org
[5] cvzone Library, “Computer Vision Utilities for Python,” https://github.com/cvzone/cvzone
[6] Tkinter Documentation, “Python Tk GUI Toolkit,” https://docs.python.org/3/library/tkinter.html
[7] Microsoft Documentation, “winsound Module,” https://learn.microsoft.com
[8] Kaggle, “Plastic Waste / Garbage Image Dataset,” Kaggle Datasets, https://www.kaggle.com
How to cite this paper
@article{1712515,
author = {Aishwarya S, Esther Ck, Varadaraju Kn, Kushal Gowda Sp, Abdul Rahaman},
title = {Smart Plastic Classification System Using Python},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {6},
pages = {58-61},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712515.pdf},
abstract = {This project presents a Smart Plastic Classification System that automatically detects and classifies plastic waste using a YOLO-based deep learning model. Images of plastics are captured and processed to identify types such as PET, HDPE, PVC, LDPE, PP, and PS. The system improves recycling efficiency by reducing manual sorting and increasing accuracy. Results show fast and reliable plastic identification, making the solution useful for waste management and environmental sustainability.},
month = {December},
doi = {https://doi.org/10.64388/IREV9I6-1712515}
}