Exploring conflicts in rule-based Sensor Networks

Abstract

This paper addresses rule conflicts within wireless sensor networks. The work is situatedwithin psychiatric ambulatory assessment settings where patients are monitored in andaround their homes. Detecting behaviours within these settings favours sensor networks,while scalability and resource concerns favour processing data on smart nodes incorporatingrule engines. Such monitoring involves personalisation, thereby becoming important toprogram node rules on the fly. Since rules may originate from distinct sources and changeover time, methods are required to maintain rule consistency. Drawing on lessons fromFeature Interaction, the paper contributes novel approaches for detecting and resolving rule-conflict across sensor networks.