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DC Field | Value | Language |
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dc.contributor.author | Rajapaksha, R.A.D.S. | - |
dc.contributor.author | Costa, L.S. | - |
dc.contributor.author | Prasanna, P.L.U.S.C. | - |
dc.contributor.author | Disanayaka, A.P.D. | - |
dc.contributor.author | Senarathne, A. N. | - |
dc.contributor.author | Wijekoon, Janaka L. | - |
dc.date.accessioned | 2022-02-17T06:49:44Z | - |
dc.date.available | 2022-02-17T06:49:44Z | - |
dc.date.issued | 2021-12-09 | - |
dc.identifier.issn | 978-1-6654-0862-2/21 | - |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/1216 | - |
dc.description.abstract | Today, this coronavirus is spread all around the world. Most organizations and businesses start to think about how to continue their business in a situation like COVID-19 and their employees’ health and business security. To avoid and be safe from this type of disease, there are some common rules to follow. Keeping a distance, wearing a mask, cleaning our hands, are some health guidelines from them. According to the current situation, many inventors are trying and have already given some solutions to avoid these kinds of situations aligning with health guidance’ provided by WHO. With the advantage of advanced modern-day technologies and ideas, researchers started to think about how to face situations like these with the new technologies and found that many users are highly interested and motivated with automated systems. Thus, from this study, we aim to provide a fully automated office management system to prevent corona with advanced technology in combination with IoT technologies, Machine learning, Cloud technologies, and sensor technologies. Considering the security aspect, Controlling the main entrance, identifying, ensuring user’s authentication before entering the building, and monitoring employee activities are very significant aspects of the study. As the result of the study, the combination of IoT technologies and Machine Learning with deep learning mechanisms have guaranteed organizational business continuity, employees' health, and security. | en_US |
dc.language.iso | en | en_US |
dc.publisher | 2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT | en_US |
dc.subject | Machine Learning | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | Flask | en_US |
dc.subject | OpenCV | en_US |
dc.subject | MobilenetV2 | en_US |
dc.title | Smart Office Automation System for Covid Prevention | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/ICAC54203.2021.9671168 | en_US |
Appears in Collections: | 3rd International Conference on Advancements in Computing (ICAC) | 2021 Research Papers - IEEE |
Files in This Item:
File | Description | Size | Format | |
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Smart_Office_Automation_System_for_Covid_Prevention.pdf Until 2050-12-31 | 1.55 MB | Adobe PDF | View/Open Request a copy |
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