Revolutionizing Waste Management: A Cutting-edge pyTorch Model for Waste Classification and Prediction, Coupled with a User-friendly Recycling Recommendation Application Built with Tkinter
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 practi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Jurusan Teknik Elektromedik Politeknik Kesehatan Kemenkes Surabaya
2024-02-01
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| Series: | Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics |
| Subjects: | |
| Online Access: | https://ijeeemi.poltekkesdepkes-sby.ac.id/index.php/ijeeemi/article/view/344 |
| Summary: | 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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| ISSN: | 2656-8624 |