Detecting Inconsistencies in Rule-Based Reasoning for Ambient Intelligence

TitleDetecting Inconsistencies in Rule-Based Reasoning for Ambient Intelligence
Publication TypeConference Paper
Year of Publication2016
AuthorsAloulou, H.., R.. Endelin, M.. Mokhtari, B.. Abdulrazak, F.. Kaddachi, and J.. Bellmunt
Conference Name2016 21st International Conference on Engineering of Complex Computer Systems (ICECCS)
Date PublishedNov
KeywordsActivity Recognition, Ambient Assisted Living, Cognition, Complexity theory, Electronic mail, Engines, Ground-Truth Acquisition, Ontologies, Production facilities, Quality insurance, Resource description framework, Semantic Reasoning

Rule-based reasoning engines have proven their value for Context-Awareness in Ambient Intelligence. However, the definition of rules is often prone to human-caused inconsistencies or sensor failures. In this paper, we propose to assist the definition of rules for context-awareness by automatically validating the consistency of the rules. Using our approach, we are able to detect conflicts between rules for context-awareness, as well as recommend adding sensors to improve the reasoner outcomes. We propose to define rules as a finite set of conditions to be verified, and provide consistency-checking capabilities to these conditions. We discuss in this paper our approach as well as results and validation.