Publication:
A Surveillance System Controlling Covid-19 in Office Environments

dc.contributor.authorBandara, P A D
dc.contributor.authorPerera, P D D S
dc.contributor.authorPerera, N P D D D
dc.contributor.authorDe Silva, P. N.
dc.contributor.authorKasthuriarachchi, S
dc.contributor.authorRajapaksha, U.U.S
dc.date.accessioned2023-05-15T10:12:39Z
dc.date.available2023-05-15T10:12:39Z
dc.date.issued2022-12-09
dc.description.abstractCOVID-19 is one of the pandemic diseases that has hit the world including Sri Lanka. He has a virus that became the target of bids to stop its spread. Including the implementation of health protocols, to provide information about the spread of the virus emergency response, detection services for suspicious persons infected with the virus, and programs to contain the spread of the virus ensuring that the whole of Sri Lanka gets vaccinated. Here, the research focuses on the minimal spread of the face mask in the office environment an identification system that uses a deep learning model that prioritizes object recognition for the identification of employees who wear a face mask and detects social distancing and crowd gathering, if any if there is a violation, it will inform via a voice notification. Loss of Smell after the next component. One person can use one disposable card to check the smell of sniffing. Each disposable card has QR codes, and all QR codes are encrypted by adding data. The user scans the QR code on their ticket and then scratches off and smelled the smelling area and selected the corresponding scent on the disposable card. Employee company attendance is a proposed automated attendance system using facial recognition. Because it requires minimal human influence and offers a high level of accuracy and marking employee attendance and employee body temperature measurement, facial recognition will appear to be a practical option. This system aims to provide a high level of protection. Automated Attendance systems that detect and recognize are safe, fast, and time-consuming savings. This technique can also be used to identify an unknown person.en_US
dc.identifier.citationD. P. A. Bandara, S. P. D. D. Prera, D. N. P. D. D. Perera, P. N. D. Silva, S. Kasthuriarachchi and U. U. Samantha Rajapaksha, "A Surveillance System Controlling Covid-19 in Office Environments," 2022 4th International Conference on Advancements in Computing (ICAC), Colombo, Sri Lanka, 2022, pp. 299-303, doi: 10.1109/ICAC57685.2022.10025286.en_US
dc.identifier.doi10.1109/ICAC57685.2022.10025286en_US
dc.identifier.isbn979-8-3503-9809-0/22/
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/3385
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2022 4th International Conference on Advancements in Computing (ICAC);
dc.subjectSurveillance Systemen_US
dc.subjectControlling Covid-19en_US
dc.titleA Surveillance System Controlling Covid-19 in Office Environmentsen_US
dc.typeArticleen_US
dspace.entity.typePublication

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