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

  • Paneru B
  • Poudyal R
  • Paneru B
  • et al.
N/ACitations
Citations of this article
10Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Paneru, B., Poudyal, R., Paneru, B., Shah, K. B., & Poudyal, K. N. (2024). Revolutionizing Waste Management: A Cutting-edge pyTorch Model for Waste Classification and Prediction, Coupled with a User-friendly Recycling Recommendation Application Built with Tkinter. Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics, 6(1), 43–51. https://doi.org/10.35882/ijeeemi.v6i1.344

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free