Resolving and Mediating Ambiguous Contexts in Pervasive Environments

INTRODCUTION Recent research in smart environments offers promising solutions to the increasing needs of pervasive computing applications; our work has demonstrated the use of such environments to support the elderly in home based healthcare ap-ABSTRACT Pervasive computing applications envision sensor rich computing and networking environments that can capture various types of contexts of inhabitants of the environment, such as their locations, activities , vital signs, and environmental measures. Such context information is useful in a variety of applications , for example to manage health information to promote independent living in " aging-in-place " scenarios. In reality, both sensed and interpreted contexts are often ambiguous, leading to potentially dangerous decisions if not properly handled. Thus, a significant challenge facing the development of realistic and deployable context-aware services for pervasive computing applications is the ability to deal with these ambiguous contexts. In this chapter, the authors discuss a resource optimized quality assured ontology-driven context mediation framework for resource constrained sensor networks based on efficient context-aware data fusion and information theoretic sensor parameter selection for optimal state estimation. It has the ability to represent contexts according to the applications' ontology and easily composable ontological rules to mediate ambiguous contexts.