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Resolving and Mediating Ambiguous Contexts in Pervasive Environments

Resolving and Mediating Ambiguous Contexts in Pervasive Environments

Nirmalya Roy, Sajal K. Das, Christine Julien
Copyright: © 2013 |Pages: 25
ISBN13: 9781466627703|ISBN10: 1466627700|EISBN13: 9781466627710
DOI: 10.4018/978-1-4666-2770-3.ch031
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MLA

Roy, Nirmalya, et al. "Resolving and Mediating Ambiguous Contexts in Pervasive Environments." User-Driven Healthcare: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2013, pp. 630-654. https://doi.org/10.4018/978-1-4666-2770-3.ch031

APA

Roy, N., Das, S. K., & Julien, C. (2013). Resolving and Mediating Ambiguous Contexts in Pervasive Environments. In I. Management Association (Ed.), User-Driven Healthcare: Concepts, Methodologies, Tools, and Applications (pp. 630-654). IGI Global. https://doi.org/10.4018/978-1-4666-2770-3.ch031

Chicago

Roy, Nirmalya, Sajal K. Das, and Christine Julien. "Resolving and Mediating Ambiguous Contexts in Pervasive Environments." In User-Driven Healthcare: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 630-654. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2770-3.ch031

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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.

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