Location based Wireless Sensor Services in Life Science Automation

Abstract. Over the last years Wireless Sensor Networks (WSN) have been becoming increasingly applicable for real world scenarios and now production ready solutions are available. In the same period the upcoming combination of Service-oriented Architectures and Web Service technology demonstrated a way to realize open standardized, flexible, service component based, loosely coupled and interoperable cross domain enterprise software solutions. But those solutions have been too resource-intensive and complex to be applicable for limited devices like wireless sensor nodes or small-sized embedded systems. Thus, more and more research investigations have been launched to bring the aspect of cross domain interoperability to the field of embedded battery powered devices. The proposed laboratory assistance solution in this paper demonstrates the benefits of Web Service enabled WSNs for process monitoring and disaster management by extending an existing system in the Life Science Automation domain. Especially, the capability to provide location based services in industrial automation environment represents a beneficial feature of the presented integration approach and results in high-quality information delivery bundled with specific data about the locational origin of the capturing sensor

Effiziente Algorithmen der Positionsbestimmung und positionsbasierte Kontextgewinnung zur Selbstorganisation in drahtlosen Sensornetzwerken

Als zentrales Thema der Arbeit wird die Positionsbestimmung einzelner Knoten innerhalb drahtloser Sensornetzwerke betrachtet. Im zweiten Themenkomplex, der Clusterbildung, wird zum einen ein auf Lokalisierung aufbauendes Verfahren betrachtet. Zum anderen wird ein Algorithmus vorgestellt, welcher nicht auf die Ermittlung konkreter Positionen angewiesen ist. Das im dritten Themenkomplex betrachtete Verfahren zur Erkennung von Fehlern innerhalb drahtloser Sensornetzwerke bietet eine Möglichkeit, um Fehler innerhalb ermittelter Informationen in drahtlosen Sensornetzwerken zu erkennen.As its main topic this thesis deals with positioning of single nodes within wireless sensor networks. Clustering in wireless sensor networks forms the second part of this work. Two newly developed algorithms will be presented. One of them is based on location information. The other uses coarse grained localization technique but without the need for location information. The third topic of this thesis is about an algorithm newly developed to detect erroneous data at a sensor node