Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1326
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dc.contributor.authorAbeygunawardhana, A. G. D. T.-
dc.contributor.authorShalinda, R. M. M. M.-
dc.contributor.authorBandara, W. H. M. D.-
dc.contributor.authorW. D. S. Anesta, D.-
dc.contributor.authorKasthurirathna-
dc.contributor.authorAbeysiri, L.-
dc.date.accessioned2022-02-21T11:12:19Z-
dc.date.available2022-02-21T11:12:19Z-
dc.date.issued2020-12-10-
dc.identifier.issn978-1-7281-8412-8-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1326-
dc.description.abstractWith increasing urbanization, waste has become a major problem in the present world. Therefore, proper waste management is a must for a healthy and clean environment. Though government authorities in most countries provide various solutions for waste management, solid waste tends to make a significant impact on the environment as they do not decompose easily. This research focuses on AI (Artificial Intelligence)-driven smart waste bin that can classify the most widely available solid waste materials namely Metal, Glass, and Plastic. The smart waste bin performs the separation of waste using image processing and machine learning algorithms. The system also performs the continuous monitoring of the collected waste level by using ultrasonic sensors. A dedicated mobile application will generate the optimal routes for the available waste collectors to collect the filled bins. Moreover, with this smart bin, the challenge of recognizing each waste item is overcome by using visual data as the source. Therefore, the usage of expensive sensor devices and filtration techniques to determine the category is disregarded. The smart bin can recognize the category of solid waste, collect it to the specified container, and notify the garbage level in each container. So, it is a portable waste management system.en_US
dc.language.isoenen_US
dc.publisher2020 2nd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.subjectImage processingen_US
dc.subjectMachine Learningen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectNeural Networks (NN)en_US
dc.subjectInternet of Things(IoT)en_US
dc.titleAI - Driven Smart Bin for Waste Managementen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC51239.2020.9357151en_US
Appears in Collections:2nd International Conference on Advancements in Computing (ICAC) | 2020
Department of Computer Science and Software Engineering-Scopes

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