Wireless Sensor Networks are the key-enabler for low cost ubiquitous applications in the area of homeland security, health-care, and environmental monitoring. A necessary prerequisite is reliable and efficient event detection in spite of sudden failures and environmental changes. Due to the fact that the sensors need to be low cost, they have only scarce resources leading to a certain level of failures of sensor nodes or sensing devices attached to the nodes. Available fault tolerant solutions are mainly customized approaches that revealed several shortcomings, particularly in adaptability and energy efficiency. The authors present a complete event detection concept including all necessary steps from formal event definition to autonomous device configuration. It features an event definition language that allows defining complex events as well as enhance the reliability by tailor-made voting schemes and application constraints. Based on that, this paper introduces a novel approach for self-adapting on-node and in-network processing, called Event Decision Tree (EDT). EDT autonomously adapts to available resources and environmental conditions, even though it requires to (re-)organize collaboration between neighboring nodes for evaluation. The authors’ approach achieves fine-grained event-related fault tolerance with configurable adaptation rate while enhancing maintainability and energy efficiency.
Near-Optimal User Recruitment in Mobile Crowdsensing for Urban Fine-Grained Event Detection