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.