Context information modelling for Internet of Things (Invited paper)

The number of sensors deployed at each and every place is growing at a faster rate to meet the current needs of modern society. The uninterrupted huge amount of data generated from sensors and other devices in Internet of Things (IoT) is to be captured and inferred into meaningful information. Context-aware computing is one of the key research issues in IoT paradigm and it is evident that it is successful in understanding each sensor data. As the physical world is highly dynamic the sensed context information is inherently imperfect or imprecise. Therefore the challenge here is to design a context information modelling and reasoning technique so as to extract meaningful information from raw sensor data. In this paper, we propose a rich and unique classification of context information from the perspective of IoT. Our research findings indicate the importance of the proposed context information classification and modelling process.