An internet of things based for smart recycle waste classification / Akmal Md Nasir

Innovative solutions utilising modern technologies have been created in response to the growing global concern for effective waste management and recycling practises. This thesis introduces a smart recycle waste categorization system built on the Internet of Things (IoT) with the goal of automating...

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Main Author:	Md Nasir, Akmal
Format:	Thesis
Language:	English
Published:	2023
Subjects:	TD Environmental technology Sanitary engineering
Online Access:	https://ir.uitm.edu.my/id/eprint/88978/1/88978.pdf
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id	my-uitm-ir.88978
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spelling	my-uitm-ir.889782024-03-19T07:07:21Z An internet of things based for smart recycle waste classification / Akmal Md Nasir 2023 Md Nasir, Akmal TD Environmental technology. Sanitary engineering Innovative solutions utilising modern technologies have been created in response to the growing global concern for effective waste management and recycling practises. This thesis introduces a smart recycle waste categorization system built on the Internet of Things (IoT) with the goal of automating and improving waste sorting procedures. To accurately categorise waste into the categories of metal, paper, plastic, and maybe other waste types, the system uses an image classification model based on the ResNet algorithm. A large dataset that included a range of waste images was aquired in order to train the classifiction model. With a high accuracy rate for waste classification, the ResNet algorithm proved to be effective. Real-time monitoring of the smart bin's capacity is made possible by the integration of IoT capabilities, and users of the Blynk app receive notifications through email as a result. The suggested system provides a dependable, automated, and flexible alternative to the drawbacks of traditional waste sorting techniques. The approach improves waste sorting accuracy by extending the classification model to incorporate additional waste types and adding a "reject" class for unclassifiable or irrelevant images. As a result, recycling procedures are enhanced, and sustainable waste management is promoted. The results of this study show how the Internet of Things and image classification algorithms have the potential to rerevolutionizearbage classification and management. An effective way to streamline waste sorting procedures and enable effective recycling techniques is to deploy the smart recycle waste classification system. This technology is expected to significantly influence waste management initiatives, fostering sustainability and environmental protection. 2023 Thesis https://ir.uitm.edu.my/id/eprint/88978/ https://ir.uitm.edu.my/id/eprint/88978/1/88978.pdf text en public degree Universiti Teknologi MARA, Melaka College of Computing, Informatics and Mathematics
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	TD Environmental technology Sanitary engineering
spellingShingle	TD Environmental technology Sanitary engineering Md Nasir, Akmal An internet of things based for smart recycle waste classification / Akmal Md Nasir
description	Innovative solutions utilising modern technologies have been created in response to the growing global concern for effective waste management and recycling practises. This thesis introduces a smart recycle waste categorization system built on the Internet of Things (IoT) with the goal of automating and improving waste sorting procedures. To accurately categorise waste into the categories of metal, paper, plastic, and maybe other waste types, the system uses an image classification model based on the ResNet algorithm. A large dataset that included a range of waste images was aquired in order to train the classifiction model. With a high accuracy rate for waste classification, the ResNet algorithm proved to be effective. Real-time monitoring of the smart bin's capacity is made possible by the integration of IoT capabilities, and users of the Blynk app receive notifications through email as a result. The suggested system provides a dependable, automated, and flexible alternative to the drawbacks of traditional waste sorting techniques. The approach improves waste sorting accuracy by extending the classification model to incorporate additional waste types and adding a "reject" class for unclassifiable or irrelevant images. As a result, recycling procedures are enhanced, and sustainable waste management is promoted. The results of this study show how the Internet of Things and image classification algorithms have the potential to rerevolutionizearbage classification and management. An effective way to streamline waste sorting procedures and enable effective recycling techniques is to deploy the smart recycle waste classification system. This technology is expected to significantly influence waste management initiatives, fostering sustainability and environmental protection.
format	Thesis
qualification_level	Bachelor degree
author	Md Nasir, Akmal
author_facet	Md Nasir, Akmal
author_sort	Md Nasir, Akmal
title	An internet of things based for smart recycle waste classification / Akmal Md Nasir
title_short	An internet of things based for smart recycle waste classification / Akmal Md Nasir
title_full	An internet of things based for smart recycle waste classification / Akmal Md Nasir
title_fullStr	An internet of things based for smart recycle waste classification / Akmal Md Nasir
title_full_unstemmed	An internet of things based for smart recycle waste classification / Akmal Md Nasir
title_sort	internet of things based for smart recycle waste classification / akmal md nasir
granting_institution	Universiti Teknologi MARA, Melaka
granting_department	College of Computing, Informatics and Mathematics
publishDate	2023
url	https://ir.uitm.edu.my/id/eprint/88978/1/88978.pdf
_version_	1794192182462119936

An internet of things based for smart recycle waste classification / Akmal Md Nasir

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