CARE: A Context-Aware Rule Engine

Context-awareness is one of the key requirements for
intelligent systems in ubiquitous computing and smart space. A knowledge-based context-aware system infers the relevant services from its knowledge base, or KB, in which contexts are represented. To maintain relations between context KB and the physical environment synchronously, this thesis describes a logic-based model that attempts to management dynamic contexts stored in the KB from which a context-aware system can infer context-triggered actions and high-level contexts. By applying STRIPS representation and assumption, we model context-aware reasoning formally into a series of situation-driven actions.

A context-aware rule engine called or CARE is developed based on the proposed reasoning model. To support making context-aware reasoning and building context-aware applications, CARE provides a systematic way to manage contexts in the KB. It utilizes a forward chaining rule engine called Jess to process rules, facts, and contexts.

Three context-aware applications developed with CARE are
described in this thesis to demonstrate the capabilities of
context-aware reasoning, the design of context-aware applications, and the software support by CARE. All three applications are covered in healthcare domain. The first targets context-aware access control in pervasive healthcare
environment. The second introduces a context-aware services
integration system for assisting elder care in future smart home. The third aims to speedup the process of emergency visit by designing several location-aware notification services for medical members in an emergency department.