I joined the working group Computer Systems & Telematics (CST) at the Institute of Computer Science, Freie Universität Berlin inJanuary2010, after graduation with the degree Diplomain 2010.
VIVE VIVE investigates new applications that benefit of an in-network evaluation of predefined events. The wireless Compounds of sensor nodes are sharing information in a cooperative way which allows to evaluate events autonomously within the network. transferred data is reduced and evaluated within the network which allows short response time on events. As a result, the lifetime of the whole network will be enhanced. More information about the VIVE project is available on the VIVE homepage.
AVS-Extrem AVS-Extrem is a use case for Wireless Sensor Networks (WSNs) focused on collaborative, in-network data processing. The goal is to develop a distributed event detection system that can reliably report security relevant incidents (e.g. a person climbing over a fence and accessing restricted areas) to a base station. The vision is that through cooperation of many sensor nodes the accuracy of event detection can be greatly improved, while at the same time saving energy by reducing multi-hop communication with the base station. More information about the AVS-Extreme project is available on theAVS-Extrem homepage.
Voicelink Voicelink is a system for autonomous nightingale song recording. It incorporated a number of cheap netbook computers spanning a wireless mesh network. Each netbook was capable of using few wired microphones for simultaneous nightingale song recording. The system was extended with a small embedded device based on an ARM microcontroller that could be easily placed very close to a nightingale nest. Management software supported reconfiguration of recording schedules and remote download of nightingale song records. Read more about the VoiceLink Project.
Voicelink is part of:
Environmental Monitoring In natural sciences, research often relies on extensive manual investigation. Such methods can be error-prone and obviously don’t scale well. The development of autonomous data acquisition systems based on Wireless Sensor Networks (WSNs) research has provides a method to significantly reduce the amount manual of work during field studies. It allows addressing of scientific questions that were previously infeasible.
Our research group gathered comprehensive experience in creating robust WSN based systems for environmental monitoring. In the recent years we worked in close collaboration with researchers from natural science area and together, we built and deployed a number of WSNs that run autonomously under real-world conditions.