M
Mohammed F. Alhamid
Researcher at King Saud University
Publications - 67
Citations - 2067
Mohammed F. Alhamid is an academic researcher from King Saud University. The author has contributed to research in topics: Context (language use) & Ambient intelligence. The author has an hindex of 20, co-authored 66 publications receiving 1323 citations. Previous affiliations of Mohammed F. Alhamid include University of Ottawa.
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Journal ArticleDOI
Blockchain and IoT-Based Cognitive Edge Framework for Sharing Economy Services in a Smart City
Md. Abdur Rahman,Md. Mamunur Rashid,M. Shamim Hossain,Elham Hassanain,Mohammed F. Alhamid,Mohsen Guizani +5 more
TL;DR: A Blockchain-based infrastructure to support security- and privacy-oriented spatio-temporal smart contract services for the sustainable Internet of Things (IoT)-enabled sharing economy in mega smart cities.
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Blockchain-Based Mobile Edge Computing Framework for Secure Therapy Applications
Md. Abdur Rahman,M. Shamim Hossain,George Loukas,Elham Hassanain,Syed Sadiqur Rahman,Mohammed F. Alhamid,Mohsen Guizani +6 more
TL;DR: An in-home therapy management framework, which leverages the IoT nodes and the blockchain-based decentralized MEC paradigm to support low-latency, secure, anonymous, and always-available spatiotemporal multimedia therapeutic data communication within an on-demand data-sharing scenario.
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Towards the sustainable development of smart cities through mass video surveillance: A response to the COVID-19 pandemic
TL;DR: A data-driven deep learning-based framework for the sustainable development of a smart city, offering a timely response to combat the COVID-19 pandemic through mass video surveillance is proposed.
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Edge Computing with Cloud for Voice Disorder Assessment and Treatment
TL;DR: A voice disorder assessment and treatment system using a deep learning approach that achieves 98.5 percent accuracy and 99.3 percent sensitivity using the Saarbrucken Voice Disorder database is proposed.
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A Facial-Expression Monitoring System for Improved Healthcare in Smart Cities
TL;DR: A facial-expression recognition system to improve the service of the healthcare in a smart city by applying a bandlet transform to a face image to extract sub-bands and producing a feature vector of the face image.