SMARTSURI: A Mobile-Based Item Recycling Classifier Application Utilizing Convolutional Neural Network with Event Notification and Recommendation System

The significant ecological issues raised by inappropriate waste management highlight the need for technical solutions to support effective recycling practices. This project aims to create SMARTSURI, a mobile-based item recycling classifier application which utilizes Convolutional Neural Network (CNN) technology to accurately classify recyclable, biodegradable, and residual materials. The system will increase user awareness by sending real-time updates about local recycling events and advising sustainable actions depending on the scanned item through OpenAI. SMARTSURI addresses three significant gaps: the absence of item classification capabilities in existing recycling programs, the lack of event notifications for local recycling activities, and the user's poor understanding of recyclable materials. SMARTSURI uses CNN s to improve recycling precision and encourage active participation in environmental sustainability. Initial evaluations of the prototype have shown excellent levels of user involvement and accuracy in identifying recyclable objects, which contributes to environmental awareness and efficiency in operation.

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Published
2024-12-12
DOI
https://doi.org/10.1109/icses63760.2024.10910419
Primary Topic
Online Learning and Analytics
Type
article
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article

SMARTSURI: A Mobile-Based Item Recycling Classifier Application Utilizing Convolutional Neural Network with Event Notification and Recommendation System

Vivien A. Agustin, Ariel M. Sison, Ramiro Vélasquez, Erwin D. Marcelo et al.
Online Learning and Analytics
article

SMARTSURI: A Mobile-Based Item Recycling Classifier Application Utilizing Convolutional Neural Network with Event Notification and Recommendation System

Vivien A. Agustin, Ariel M. Sison, Ramiro Vélasquez, Erwin D. Marcelo, Glyns Erbi M. Guadalupe, Mervin Jeliel C. Zaguirre
article en

Abstract

The significant ecological issues raised by inappropriate waste management highlight the need for technical solutions to support effective recycling practices. This project aims to create SMARTSURI, a mobile-based item recycling classifier application which utilizes Convolutional Neural Network (CNN) technology to accurately classify recyclable, biodegradable, and residual materials. The system will increase user awareness by sending real-time updates about local recycling events and advising sustainable actions depending on the scanned item through OpenAI. SMARTSURI addresses three significant gaps: the absence of item classification capabilities in existing recycling programs, the lack of event notifications for local recycling activities, and the user's poor understanding of recyclable materials. SMARTSURI uses CNN s to improve recycling precision and encourage active participation in environmental sustainability. Initial evaluations of the prototype have shown excellent levels of user involvement and accuracy in identifying recyclable objects, which contributes to environmental awareness and efficiency in operation.

University of the City of Manila (PH)
Openalex Percentile: Top 70%
Online Learning and Analytics
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SMARTSURI: A Mobile-Based Item Recycling Classifier Application Utilizing Convolutional Neural Network with Event Notification and Recommendation System — Vivien A. Agustin, Ariel M. Sison, et al. · (2024) | TGRS Research Map | TGRS