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Wimplebin: an AI-based recycle bin for a better waste management

  • Jiacang Ho,
  • JongHyuk Lee,
  • HyoungSuk Kim

摘要

Advanced artificial intelligence (AI) technologies have bestowed numerous advantages upon our daily lives. Despite the ongoing efforts of various institutions urging responsible waste distribution for the preservation of our planet, completely resolving the waste problem remains a formidable challenge. This paper endeavors to present a solution through the integration of AI into waste distribution systems. We introduce WimpleBin, an AI-based recycle bin, designed to accurately classify waste streams following training with machine learning algorithms. Utilizing the YOLOv5 framework, we train WimpleBin with the collected data to accomplish our objectives. The 81% accuracy achieved in real-world scenarios demonstrates WimpleBin’s impressive ability to effectively categorize different types of waste.