Image-Based Recognition for Recyclable Materials Using Convolutional Neural Network

Dane Bryan Taglay, John Cedrick Ramos, Jerome Rigor, Ryan Floyd Royo and Ronald Fernandez
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Dane Bryan Taglay: College of Computing Studies, Universidad De Manila, Philippines
John Cedrick Ramos: College of Computing Studies, Universidad De Manila, Philippines
Jerome Rigor: College of Computing Studies, Universidad De Manila, Philippines
Ryan Floyd Royo: College of Computing Studies, Universidad De Manila, Philippines
Ronald Fernandez: College of Computing Studies, Universidad De Manila, Philippines

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 9, 606-617

Abstract: This document presents the development of an intelligent mobile application that uses an Image-Based Recognition System that runs on a Convolutional Neural Network (CNN) to foster sustainable behaviors and promote environmental consciousness. The system will identify and sort different materials that can be recycled such as wood, plastic, fabric, cardboard, and metal using deep learning-based image recognition. The application allows users to take or post pictures of objects after which they are processed and analyzed to determine the type of material in real-time. After this identification, the system creates rule-based suggestions, which offer curated video tutorials and step-by-step instructions on potential upcycling projects. Such customized recommendations do not only prolong the life of materials, but also encourage users to implement creative, environmentally friendly solutions in their everyday life.

Date: 2025
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