Context-awareness is one of the fundamental principles underpinning pervasive computing. Context prediction, a new trend in pervasive computing, is an open-ended research topic with a lot of challenges and opportunities for innovation. This work presents and analyzes the development in this area and compares different context prediction techniques and approaches.
A survey of prediction approach in pervasive computing.
Reference: International Journal of Scientific & Engineering Research
Authors: Darine Ameyed|
About the Author: Darine Ameyed
Darine Ameyed, Ph.D. in engineering, Software and Information Technologies (ÉTS-2017). She received an M.Msc applied IA ( Columbia university US-2019). She obtained her M.Sc. in Digital Art and Technology from the University Rennes 2 (U.R.2) (University of Upper Brittany, France) in 2010. She earned her M.Sc. Multimedia Engineering from the University Paris Est Marne la Vallée (U.P.E.M) (University of Paris 11, France) in 2008. She received a B.Sc. in computer science and Management from the Institut Supérieur de Gestion (I.S.G) (University of Tunis, Tunisia) in 2005. She is currently a research associate at Synchromédia lab, École Technologie Supérieure (ÉTS), Montreal. Also, an expert in United for smart and sustainable cities (U4SSC)-International Telecommunication Union- ITU-UN. She has been a scientific program and project manager at CIRODD (2015-2019), Co-founder and CEO of NyX-R (2015-2018), a tech advisor for tech and science-based startups. On the other hand, she has a long multidisciplinary academic and industrial career in Canada, Europe, and Africa in the areas of software engineering, mobile computing, ERP system management, art, and entrepreneurship. Her research interests include Predictive Modeling, Context-Aware System, Ambient Intelligence (AmI), C-IoT, Human-Centered Computing, Machine Learning, Activity Recognition, Human-Machine Interaction (HMI), Data security and privacy in IoT platforms and computational sustainability.