Smart resource-aware multi-sensor network (SRSnet)
The Smart resource-aware multi-sensor network project (SRSnet) is an Interreg IV research project funded by the European Community.
The project started on the 01.09.2009. The SRSnet project is planned for three years and it is a joint project with the Institute of Pervasive Computing and Smart Systems Technologies at Klagenfurt University, and the University of Udine. The involved partners have already an excellent expertise within the research areas “computer vision & signal processing algorithms” and “pervasive computing including the aspect of self-organized network systems”.
Lakeside Labs GmbH is responsible for the coordination and the financial management of the project. The University of Klagenfurt, who is doing the scientific work within relevant work packages, is subcontracted by the Lakeside Labs GmbH. Its research focuses on the theory and application of various aspects of pervasive computing, in particular on distributed smart cameras, sensor networks, sensor fusion and embedded signal processing architectures. The project partner Eye-Tech has large experience in both national (Italian) and international research related to image sequence and audio processing techniques and therefore responsible for the scientific and technological aspect of the project. Eye-Tech is an academic spin-off founded in 2007 by members of the Artificial Vision and Real time Systems laboratory of the University of Udine.
The SRSnet project focuses on the design of a smart resource-aware multi-sensor network capable of autonomously detecting and localizing various events such as screams, animal noise, tracks of persons and more complex human behaviors. The project's research areas include (i) collaborative audio and video analysis, (ii) complex event detection and (iii) network reconfiguration. The SRSnet will be demonstrated in an biologically sensitive environmental, namely in the Hohe Tauern National Park. This National Park was chosen as a testing environment for offering realistic case studies. It also profits from the results of the project by having a better understanding of visitor and animal movements within the mostly restricted natural preserve area.
The SRSnet project focuses on the design of a smart resource-aware multi-sensor network capable of autonomously detecting and localizing various events such as screams, animal noise, tracks of persons and more complex human behaviors. The project's research areas include (i) collaborative audio and video analysis, (ii) complex event detection and (iii) network reconfiguration. The SRSnet will be demonstrated in an biologically sensitive environmental, namely in the Hohe Tauern National Park. This National Park was chosen as a testing environment for offering realistic case studies. It also profits from the results of the project by having a better understanding of visitor and animal movements within the mostly restricted natural preserve area.
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