Deployment And Evaluation Of A Fully Applicable Distributed Event Detection System In Wireless Sensor Networks

Versatility and real world applicability are key features of Wireless Sensor Networks (WSNs). In order to achieve these benefits we have to face the challenges of high practical relevance during application. We deploy and evaluate the concrete example of a fence monitoring task to reveal how our distributed event detection system is able to perform under real application conditions.The challenge is to bring both opposing aspects-high event detection accuracy and long service life-into one applicable ubiquitous system. If sensor nodes compose parts of events cooperatively, a comprehensive event assessment with low energy demands is possible. We propose a classifier based distributed event detection system consisting of two frameworks. The evaluation framework delivers a classification model and enables the theoretical evaluation of a given training set. The distributed event detection framework subsequently applies the classification model to assess, filter and classify events within the network. We evaluate our system by training and detecting events with our WSN composed of 49 nodes which are integrated in construction site fence elements. We compare four different data application scenarios with varying data processing concepts and varying network sizes to analyze the resulting communication load as well as the system lifetime.We compare the results of our evaluation framework with the results of our application to show that the evaluation framework reflects the real world deployment results in a credible way. We show the full applicability of our approach by comparing the resulting increased event detection accuracy against our previous work. Compared to other information fusion scenarios, our distributed event detection system reduces energy consumption beyond a communication distance of two hops which yields a prolonged lifetime of the network while additionally achieving an improved event detection accuracy. (C) 2015 Elsevier B.V. All rights reserved.