Smart Sensing and Context

Abstract

Abstract. Research in context-aware systems shows that using context information enables the development of personalized mobile applications. The context acquisition process in a context-aware (CA) system consists of two main roles: context producing entities (e.g. wrapped sensors) and context consuming entities (e.g. CA application). A CA system can be seen as a hierarchy of associated context producers and consumers which exchange contextual information. Managing contextual information used in context aware systems, introduces additional complexity for mobile application developers. We focus on the dynamic processes of discovery, selection, (re)binding and monitoring of entities that produce context information. Dynamic context binding is complex because of the dynamic nature, in terms of availability and quality, of context producers. We propose to delegate the responsibility for context binding to the middleware infrastructure and provide application designers with a declarative language to specify context information requirements on a high-level of abstraction. In this way, our Context-Aware Component Infrastructure (CACI) provides support for dynamic context bindings between application components and context producers.

Computing for the future of the planet

“…One solution to this problem is to collect movement traces from vehicles in the road network and post-process these traces to maintain our maps automatically. Davies et al (2006b) described an algorithm for both automatic construction of a map and automatic comparison between maps to discover topology changes. Technology such as this improves the efficiency of transportation by allowing changes to the road network to be rapidly disseminated to drivers.…”