“Dynamically adaptive applications for bat localization using embedded communicating sensor systems”
Sensor networks become extremely valuable if they barely affect their environment and moving objects. Capturing data should be possible even in hardly accessible or problematic areas. In this area, the research group proposed will make a decisive contribution.
For that purpose a genuine, forward-looking approach is pursued, which consciously involves expertise from the outset in the following three sensor network levels:
- Expertise at the application level, represented by the biology with the example application of bat research
- Expertise in the field of data processing and network communication, a domain of computer science.
- Expertise on the level of “minimally invasive” physical data acquisition and tracking techniques, a typical task of electrical and information engineering
The bat as was chosen an example for the focus of all partial projects, because the constraints concerning weight and energy and thus the requirements for mobile data processing and storage are particularly challenging.
Up to now observation of bats is done by foot or by plane. Thereby significant gaps in coverage often occurred.
Hence, optimization of capturing, managing and analyzing data is required, as well as the ability to flexibly react and online adapt to biological problems.
The demand and management of energy, as well as the weight and the robustness of the mobile sensor nodes play a central role. However, this results in substantial restrictions for distributed data processing and communication.
The solution of these scientific problems could be highly valuable for industrial applications. For example, in scenarios like the motion capturing of school beginners to better protect them from the traffic and avoid accidents.
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