Development and Comparison of YOLOV8 Models for Plastic Classification via Digital Image Processing
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Abstract
Currently plastic problem has caused a lot of problems and has a lot of effected to Thailand and tends to have more plastic waste every year. Researcher points that having effective plastic waste management is essential by reusing plastic which can help the environment. Now Thailand still uses the legacy management to manage the plastic waste by using human which leads to inefficient result plastic is include with local waste which were burned, buried or leak to the sea. This research proposes the solution of plastic management to recycle plastic by using image using Deep learning with the data of PET, HDPE, PVC, LDPE, PP, PS and Other then training the model using YOLO. I use YOLOv8 so AI can separate type of plastic precisely and speedy. From the experiment’s result each YOLO version has potential to separate the type of plastic this research tested the performance of YOLOv8 with different version founded that YOLOv8n has given the best result. This research shows that the potential of AI can help with plastic waste management and can lead to innovation for environment.
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