Smart Garbage Classifier

Authors

  • Prof. M. Premalatha  School of Computing Science and Engineering Vellore Institute of Technology, Chennai, Tamil Nadu, India
  • Syeda Zainab  School of Computing Science and Engineering Vellore Institute of Technology, Chennai, Tamil Nadu, India
  • Arpita Sahu  School of Computing Science and Engineering Vellore Institute of Technology, Chennai, Tamil Nadu, India
  • Anushka Bohara  School of Computing Science and Engineering Vellore Institute of Technology, Chennai, Tamil Nadu, India
  • Vijaya Lakshmi  School of Computing Science and Engineering Vellore Institute of Technology, Chennai, Tamil Nadu, India

Keywords:

Garbage classification, computer vision, shape descriptor ,object classification, k nearest neighbour.

Abstract

Smart garbage classifier classifies the given solid garbage into paper, metal, trash, glass and cardboard. It analyses the image using a camera and preprocesses the images using image processing algorithms followed by machine learning algorithm to do the classification. So that it will be easier for further recycling.

References

  1. Adam Garcia, Tom Jacobson, “Smart waste disposal in Guam”, Journal of Waste Disposal and management (2017)
  2. Wang, F., Kuehr, R., Huisman, J. “The Global E-waste Monitor” Institute of Advanced Study of Sustainability (2014)
  3. Bhavik Gupta, Shakti Kumar Arora “A study on management of municipal solid waste in Delhi” Journal of Environment and Waste Management 3 (2016)
  4. Chao Li, Shuheng Zhang, et al, “Using the K- Nearest Neighbor Algorithm for the Classification of Lymph Node Metastasis in Gastric Cancer” Computational and Mathematical Methods in Medicine, Volume 2012 (2012), Article ID 876545
  5. US EPA website: World Bank Report on Solid Waste Management

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Published

2021-06-30

Issue

Section

Research Articles

How to Cite

[1]
Prof. M. Premalatha, Syeda Zainab, Arpita Sahu, Anushka Bohara, Vijaya Lakshmi, " Smart Garbage Classifier, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 8, Issue 3, pp.555-560, May-June-2021.