Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1040
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dc.contributor.authorHandalage, U-
dc.contributor.authorNikapotha, N-
dc.contributor.authorSubasinghe, C-
dc.contributor.authorPrasanga, T-
dc.contributor.authorThilakarthna, T-
dc.contributor.authorKasthurirathna, D-
dc.date.accessioned2022-02-09T04:05:10Z-
dc.date.available2022-02-09T04:05:10Z-
dc.date.issued2021-12-09-
dc.identifier.citationU. Handalage, N. Nikapotha, C. Subasinghe, T. Prasanga, T. Thilakarthna and D. Kasthurirathna, "Computer Vision Enabled Drowning Detection System," 2021 3rd International Conference on Advancements in Computing (ICAC), 2021, pp. 240-245, doi: 10.1109/ICAC54203.2021.9671126.en_US
dc.identifier.isbn978-1-6654-0862-2-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1040-
dc.description.abstractSafety is paramount in all swimming pools. The current systems expected to address the problem of ensuring safety at swimming pools have significant problems due to their technical aspects, such as underwater cameras and methodological aspects such as the need for human intervention in the rescue mission. The use of an automated visual-based monitoring system can help to reduce drownings and assure pool safety effectively. This study introduces a revolutionary technology that identifies drowning victims in a minimum amount of time and dispatches an automated drone to save them. Using convolutional neural network (CNN) models, it can detect a drowning person in three stages. Whenever such a situation like this is detected, the inflatable tube-mounted self-driven drone will go on a rescue mission, sounding an alarm to inform the nearby lifeguards. The system also keeps an eye out for potentially dangerous actions that could result in drowning. This system’s ability to save a drowning victim in under a minute has been demonstrated in prototype experiments' performance evaluations.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2021 3rd International Conference on Advancements in Computing (ICAC);Pages 240-245-
dc.subjectComputer Visionen_US
dc.subjectEnabled Drowningen_US
dc.subjectDetection Systemen_US
dc.titleComputer Vision Enabled Drowning Detection Systemen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC54203.2021.9671126en_US
Appears in Collections:Department of Computer Science and Software Engineering-Scopes
Research Papers - Dept of Computer Science and Software Engineering
Research Papers - SLIIT Staff Publications

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