Mar 13, 2009

PhD Studentships in Sensor Networks for Surveillance and Monitoring Applications

As part of our collaborative research work with SELEX Sensors and Airborne Systems Limited, we wish to recruit a research student for a PhD study on sensor networks for surveillance and monitoring applications. The main objective of the proposed research project is to explore the usage of sensor networks in improving monitoring and surveillance performances, with an emphasis on the provision of actionable user information (e.g. decision support etc.) gathered from integrated multi-modal systems.

This requires, first, improving deployment strategies and associated supporting tools for the deployment of static sensor nodes in order to provide optimal coverage/context awareness from the deployed system within the monitored area. Based on decentralized sensing architecture, robust threat identification and sensor node localization algorithms will also be investigated. In addition, efficient data/information fusion from heterogeneous sensors (such as EO/IR
visual, acoustic and seismic sensors) will be carried on to improve threat detection, behaviour within it´s operating context.

The potential to exploit the distributed tracking capabilities of multi-modal sensor networks will also be assessed during this work. The project will be carried out in close collaboration with our industrial partner and the resulting interactions will provide an exceptionally rich research environment. In addition to simulation validation, this project entails 30% real time experiments to embed proposed algorithms on representative sensor network hardware capabilities.

Entry Requirements: For this research studentship, we are seeking a talented graduate, having (or be expected to obtain) at least an upper second class honours degree (first class honours preferred), MSc or equivalent in electrical engineering or computer science. Good mathematical background and experience of sensor signal processing, distributed/ networked systems, Bayesian based inference techniques, data/information fusion and real time systems would be most desirable.


Visit this website for more information

http://www.scholars hips-links.com/viewdetail/id/225/PhD_Studentships_in_Sensor_ Networks_for_Surveillance_and_Monitoring_Applications,_Cranfield_Universi/


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