Due to advances in sensor technology, sensors are getting more powerful, cheaper and smaller in size, which hasstimulated large scale deployments. As a result, today wehave a large number of sensors already deployed and it is predicted that the numbers will grow rapidly over the nextdecade [4]. Ultimately, these sensors will generate big data[5]. The data we collect may not have any value unless weanalyse, interpret, and understand it. Context-aware computing has played an important role in tackling this challenge inprevious paradigms, such as mobile and pervasive, which lead us to believe that it would continue to be successful in the IoT paradigm as well. Context-aware computing allows us to store context information linked to sensor data so the interpretation can be done easily and more meaningfully. Inaddition, understanding context makes it easier to perform machine to machine communication as it is a core elementin the IoT vision.
When large numbers of sensors are deployed, and start generating data, the traditional application based approach (i.e.connect sensors directly to applications individually and manually)becomes infeasible. In order to address this inefficiency,significant amounts of middleware solutions are introduced by researchers. Each middleware solution focuses on different aspects
in the IoT, such as device management,interoperability,
platform portability, context-awareness, security and privacy,and many more. Even though, some solutions address multiple aspects, an ideal middleware solution that addresses all the aspects required by the IoT(Internet of things,) is yet to be designed.
From , May , 2013
Context Aware Computing for
The Internet of Things: A Survey