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dc.contributor.authorBitragunta, Sainath
dc.contributor.authorChamola, Vinay
dc.contributor.authorMishra, Puneet
dc.contributor.authorYenuganti, Sujan
dc.date.accessioned2023-03-09T04:32:28Z
dc.date.available2023-03-09T04:32:28Z
dc.date.issued2021-06
dc.identifier.urihttps://ieeexplore.ieee.org/document/9492907
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9583
dc.description.abstractProviding rapid testing and proper treatment has become highly challenging due to the rapid and highly unpredictable spread of the coronavirus disease (COVID-19). In most developing countries, rural areas lack adequate medical facilities and medical staff for effective diagnosis and treatment. Recently, there have been several technological advancements across various engineering disciplines such as the Internet of Things, unmanned aerial vehicles (UAVs) or drones, deep neural networks (DNNs), and intelligent robots. This work proposes a prototype that integrates these technologies to develop a payload deployable in a drone to help in providing rapid testing and healthcare. The proposed UAV prototype combines secure patient authentication, an automated disinfection system, and medical sensors as part of the UAV payload. It uses a DNN model for real-time COVID-19 detection. It uses intelligent flight path planning, operational management, battery recharge planning, disinfectant refilling, and strategic location planning to quickly disseminate testing kits and essential medical services to remote locations without direct human involvement.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectEEEen_US
dc.subjectCOVID-19en_US
dc.subjectDronesen_US
dc.subjectMedical servicesen_US
dc.subjectInternet of Medical Thingsen_US
dc.subjectMedical diagnostic imagingen_US
dc.titleIoMT and DNN-Enabled Drone-Assisted Covid-19 Screening and Detection Framework for Rural Areasen_US
dc.typeArticleen_US
Appears in Collections:Department of Electrical and Electronics Engineering

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