Spatiotemporal context modelling in pervasive context-aware computing environment: a logic perspective

Pervasive context-aware computing, is one of the topics that received particular attention from researchers. The context, itself is an important notion explored in many works discussing its: acquisition, definition, modelling, reasoning and more. Given the permanent evolution of context-aware systems, context modeling is still a complex task, due to the lack of an adequate, dynamic, formal and relevant context representation. This paper discusses various context modeling approaches and previous logic-based works. It also proposes a preliminary formal spatiotemporal context modelling based on first-order logic, derived from the structure of natural languages.

Additional Info

Reference: International Journal of Advanced Computer Science and Applications 7.4 (2016): 407-414.

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.