Revolutionizing Waste Management: A Cutting-edge pyTorch Model for Waste Classification and Prediction, Coupled with a User-friendly Recycling Recommendation Application Built with Tkinter

Waste management application with tkinter and deep learning

  • Biplov Paneru Dept.of Electronics & communication, Nepal Engineering College
  • Ramhari Poudyal Dept. of Electrical Engineering, Tribhuvan University Nepal
  • Bishwash Paneru Dept. of chemical Science Engineering, institute of Engineering Nepal
  • Krishna Bikram Shah Department of Computer Science and Engineering, Nepal Engineering College Pokhara University, Nepal
  • Khem Narayan Poudyal Department of Computer Science and Engineering, Nepal Engineering College Pokhara University, Nepal
DOI: https://doi.org/10.35882/ijeeemi.v6i1.344
Keywords: Tkinter, waste classification, pyTorch, recycle

Abstract

A major environmental concern is waste management, and encouraging recycling programs depends heavily on the accurate categorization and forecasting of waste kinds. We present an enhanced pytorch model in this work for waste prediction and classification. To promote sustainable waste disposal practices, we also present a Recycling Recommendation Application with an intuitive Tkinter interface. The goal of combining cutting-edge machine learning methods with user-centered design is to make waste management systems more effective. The model gained accuracy of 99% on training and approximately 96% on validation, and was successfully added in a tkinter app for making prediction on type of waste image, plus recommending of solution to such waste management is done by the application we develop.

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Published
2024-02-06
How to Cite
[1]
B. Paneru, R. Poudyal, B. Paneru, K. B. Shah, and K. N. Poudyal, “Revolutionizing Waste Management: A Cutting-edge pyTorch Model for Waste Classification and Prediction, Coupled with a User-friendly Recycling Recommendation Application Built with Tkinter: Waste management application with tkinter and deep learning”, Indones.J.electronic.electromed.med.inf, vol. 6, no. 1, Feb. 2024.
Issue
Vol. 6 No. 1 (2024): February
Section
Research Article

Copyright (c) 2024 Biplov Paneru, Ramhari Poudyal, Bishwash Paneru, Krishna Bikram Shah, Khem Narayan Poudyal

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