European Research Tracks Biology for Emergency Sensor Networks (12/12)
Tuesday, December 12, 2006 | Comments
A new research and development project has been launched to investigate using biological processes to devise sensor networks for emergency applications. The project will use biologically inspired formulations to devise efficient sensor networks to overcome the current constraints that arise from treating a sensor network with a philosophy similar to that used in traditional communications networks. Known as Wireless Sensor Networks with Self-Organization Capabilities for Critical and Emergency Applications (WINSOC), the project is funded by the European Commission under the umbrella of Framework Programme 6 - Information Society Technologies. WINSOC is intended to significantly improve performance and competitiveness in both generic network sensor design and in key selected emergency applications - landslide monitoring, gas leakage detection and location, and fire detection and prediction. It will last 30 months and is coordinated by Selex Communications (Italy). Other partners include the University of Rome La Sapienza (Italy), the Ecole Polytechnique FŽdŽrale de Lausanne (Switzerland), Intracom (Greece), the Commissariat per l'Energie Atomique-LETI (France), the Czech Centre for Science and Society (Czech Republic), Dune (Italy), Technical University of Catalonia - UPC (Spain), Indian Space Organisation (India), Amrita University (India), and the Sci-Tech consultancy firm Sapienza (Spain). WINSOC's major aim is to solve the important problem about the specific conflicting requirements appearing in a sensor network - low complexity in sensor devices, high reliability of the decision/estimation/measurement of the network as a whole, long-term lifetime, high scalability, and resilience to congestion. To this end, the network design is conceived as a biologically inspired system - the result of using insights from biology to design a system that could be able to self assemble into organized structures, in which the devices (sensors) can make decisions based on their local environment and individual states. In this way, distributed detection and estimation capabilities can be built. Work planned includes developing algorithms to be implemented in the sensors, simulations at system level for the performance evaluation of a network, the development of the sensor network prototype, and the deployment and evaluation of the network performance in the selected fields of application. Further information will be published at 

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