PhD Thesis - Dr. Amir Padovitz

Abstract Context-awareness enables applications to become aware of useful circumstances in the environment. In the context of pervasive computing systems, context-awareness enables applications to respond, possibly intelligently, to sensory originated information.

Awareness of context, and in the broader perspective also awareness of situations, have been recognized as a key in adapting to changes in context by applications operating in multi-sensor pervasive computing systems.

This thesis addresses four key challenges in context-aware computing in pervasive environments, namely: (1) modelling and representing context in a unifying and general way, (2) reasoning about context under uncertainty, (3) managing context to promote proactive behaviour of applications in open pervasive computing environments, and (4) building an extensible reasoning-capable context framework.

Underpinning this dissertation is the development of a novel theoretical approach to model context and situations. The proposed model (titled Context Spaces) uses spatial metaphors and insights from the state-space model to describe context and situations in multi-dimensional space.

The model facilitates: (1) unifying context representation, (2) designing operations for manipulating and utilizing context, and (3) developing novel approaches to reasoning about context. Built on the proposed model, we develop a Context Spaces Algebra, comprising operations dealing with concepts such as intersection of situations, or composing the perspectives of different entities over the object of reasoning. We show that these and other operations are useful in enhancing reasoning about context and promoting proactive management of context.

Based on the Context Spaces model, we develop practical solutions for challenges in context-aware pervasive systems in the form of algorithms, methodologies, architecture and implementation. We propose innovative reasoning approaches, including: (1) A heuristically-based sensor data fusion algorithm, specifically developed for reasoning about context. The algorithm incorporates reasoning considerations concerning context in pervasive computing environments, such as the relative- values, importance and uncertainties of sensed information, and is evaluated with cases using real sensors as well as with elaborate simulations. (2) An approach to compute the confidence in the validity vii