Context-aware Reasoning Engine with High Level Knowledge for Smart Home
Abstract
We are interested in providing people living or working in smart home environment with sensor network based assistive technology. We propose a novel rule-based reasoning engine that could be used in ubiquitous environments to infer logical consequences from events received over a sensor network. We introduce methods for rule design with high level knowledge input and using minimum information to infer micro-context. Personalised profiles can be introduced into the reasoning engine to customise features for a particular user using our rule refinement and generation module. New mechanism for sensor-engine communication is also introduced. As a proof of concept, a prototype system has been developed to demonstrate the functionalities of our reasoning engine in a simulated smart home environment.