Authors :
Princess Angelica Jane D. Apellido; Charles David C. Arco; Eliza B. Ayo; Michael Joseph T. Collado; Crystalynne D. Cortez; Rowell D. Santos
Volume/Issue :
Volume 9 - 2024, Issue 3 - March
Google Scholar :
https://tinyurl.com/4b57ntus
Scribd :
https://tinyurl.com/456ww4kz
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAR794
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The United Nations (UN) has numerous goals
outlined in its charter and subsequent resolutions. One of
which is addressing environmental challenges such as
climate change, biodiversity loss, and pollution. As a
response to this call, Centro Escolar University(CEU)
lodged the KALINGA program. Part of this program is
to study ways the community could improve waste
management. This study is a concerted effort to promote
sustainable development practices, mitigate the impacts
of climate change, protect ecosystems, and promote
renewable energy. This developed prototype recognizes
and classifies non-biodegradable and biodegradable
materials with a 96% accuracy rate. The user-friendly
system uses an ultrasonic sensor and image processing.
Keywords :
Automatic WasteSegregation, Convolutional Neural Network, Waste Classification, Usability, Efficiency, Portability, Application, Accuracy.
The United Nations (UN) has numerous goals
outlined in its charter and subsequent resolutions. One of
which is addressing environmental challenges such as
climate change, biodiversity loss, and pollution. As a
response to this call, Centro Escolar University(CEU)
lodged the KALINGA program. Part of this program is
to study ways the community could improve waste
management. This study is a concerted effort to promote
sustainable development practices, mitigate the impacts
of climate change, protect ecosystems, and promote
renewable energy. This developed prototype recognizes
and classifies non-biodegradable and biodegradable
materials with a 96% accuracy rate. The user-friendly
system uses an ultrasonic sensor and image processing.
Keywords :
Automatic WasteSegregation, Convolutional Neural Network, Waste Classification, Usability, Efficiency, Portability, Application, Accuracy.
