A Smart System for Segregating Solid Waste using Machine Learning Model

Authors

  • Cahyo Ihtifazhuddin Albukhary International University
  • Aditya Muhammad Reza Albukhary International University

Keywords:

waste segregation, solid waste, machine learning, YOLO, ORB, algorithm

Abstract

Waste management has problems consisting of the large quantity, variety of waste produced and the nature of the material is very complex and complicated. Recycling is one of the most typical approaches that can be taken. The proposed model involves Convolutional Neural Network (CNN), utilizing YOLO for object detection, and ORB for object tracking. This system can solve problems on a large scale such as districts hence the management becomes centralized and cost-effective. There will be more waste that can be recycled and benefit society. The future framework will have a complete system to become a complete garbage group for reuse, reduce, recycle (3R) use.

 

Author Biographies

  • Cahyo Ihtifazhuddin, Albukhary International University

     

     

  • Aditya Muhammad Reza, Albukhary International University

     

     

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Published

24-01-2023

How to Cite

Ihtifazhuddin, C. ., & Muhammad Reza, A. . (2023). A Smart System for Segregating Solid Waste using Machine Learning Model. Multidisciplinary Applied Research and Innovation, 4(1), 40-47. https://penerbit.uthm.edu.my/periodicals/index.php/mari/article/view/9901