M
Mohsen Guizani
Researcher at Qatar University
Publications - 1337
Citations - 48275
Mohsen Guizani is an academic researcher from Qatar University. The author has contributed to research in topics: Computer science & Cloud computing. The author has an hindex of 79, co-authored 1110 publications receiving 31282 citations. Previous affiliations of Mohsen Guizani include Jaypee Institute of Information Technology & University College for Women.
Papers
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Journal ArticleDOI
When Traffic Flow Prediction and Wireless Big Data Analytics Meet
TL;DR: Whether or not prediction performance can be improved by fitting the actual data to optimize the parameter values of a prediction model is verified by comparing the optimized and the normal time series prediction models.
Journal ArticleDOI
Federated Learning and Autonomous UAVs for Hazardous Zone Detection and AQI Prediction in IoT Environment
TL;DR: A distributed federated learning (FL) algorithm within a UAV swarm that collects air quality data using built-in sensors and predicts AQI daily with a minimal error rate on a real-time data set from Delhi is implemented.
Journal ArticleDOI
A Two-Step Secure Localization for Wireless Sensor Networks
TL;DR: A novel scheme called two-step secure localization (TSSL) stand against many typical malicious attacks, e.g. wormhole attack and location spoofing attack and the localization algorithm accomplishes localization with high localization accuracy.
Proceedings ArticleDOI
Discovering influential users in micro-blog marketing with influence maximization mechanism
TL;DR: This paper tries to analyze the influences of nodes in a micro-blog network and proposes a Community Scale-Sensitive Maxdegree (CSSM) algorithm for maximizing the influences when placing ads.
Journal ArticleDOI
IoMT and DNN-Enabled Drone-Assisted Covid-19 Screening and Detection Framework for Rural Areas
Naren Naren,Vinay Chamola,Sainath Baitragunta,Ananthakrishna Chintanpalli,Puneet Mishra,Sujan Yenuganti,Mohsen Guizani +6 more
TL;DR: In this paper, the authors proposed a prototype that combines secure patient authentication, an automated disinfection system, and medical sensors as part of the UAV payload for real-time COVID-19 detection.