Analysis of Context Aware Computing Systems in Internet of Things

Abstract

Internet of Things (IoT) has been developed speedily due to modern advancements in communications and sensor technologies. Similarly IoT deployments are rising with accelerating speed. Since this field develops in number and heterogeneity, intelligence has become important aspect of IoT. The data has become Big in nature so understanding, extracting knowledge and interpreting this Big Data is critical step for upcoming future of IoT. One of the major difficulties in the way to smart IoT is understanding context.  Context is defined as making sense of the situation or environment using data received from the sensors and performing actions accordingly. This is referred as context-aware computing. Context aware systems are in high demand in fields/area like Smart/Intelligent Environments, Pervasive & Ubiquitous Computing etc. They collect the data and adjust the system actions accordingly with the help of context details. In this survey paper, we discuss the perception of context awareness, context lifecycle, context modeling approaches and context reasoning methods in detail. The survey shows that Ontology based modeling and Supervised learning reasoning are widely used in context-aware computing systems. Finally, applications of context-aware systems are listed along with discussion on open issues to point out challenges and upcoming development direction of context-aware systems.