Stephan Adler

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In radio frequency based indoor human localization systems with body mounted sensors, the human body can cause non-line-of-sight (NLOS) effects which might result in severe range estimation and localization errors. However, previous studies on the impact of the human body only conducted static experiments in controlled environments. We confirm known effects(More)
Event detection in wireless sensor networks is a sophisticated method for processing sampled data directly on the sensor nodes, thereby reducing the need for multi-hop communication with the base station of the network. In contrast to application-agnostic compression or aggregation techniques, event detection pushes application-level knowledge into the(More)
Fences are used all over the world to protect areas against unauthorized access. While most fences meet these requirements by building a physical and psychological barrier against intruders, this is not sufficient for areas of particular interest like restricted areas of an airport or construction sites with expensive goods. To detect intruders we integrate(More)
Distributed event detection in wireless sensor networks is an approach to increase event recognition accuracy by fusing correlated parts of events, recognized by multiple sensor nodes. Events range from simple threshold detection to complex events requiring pattern analysis. Our previous deployment in this area of research investigates the possibility to(More)
In the current practice, the performance evaluation of RF-based indoor localization solutions is typically realized in non-standardized environments and following ad-hoc procedures, which hampers objective comparison and does not provide clear insight into their intrinsic properties. Many evaluation procedures also neglect important environmental factors(More)
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(More)