Parallel Distributed Wireless Sensor Network Application for Critical Infrastructure Risk Analysis of Fossil Fuelled Power Stations

The present paper is an application paper to an already published fully distributed associative memory algorithm for use within a wireless sensor network (WSN). The published work shows that the set up allows a physical object to develop a capability, which to some extent may be considered as similar to our sense of touch, with WSN acting as the artificial nervous system in this regard. The published work general application areas range from new engineering structures, which make use of the surrounding information to increase their strength and stability to mechanical assemblies, which may warn of an imminent component failure. Consequently, the present paper set the scene to integrate the published algorithm within a total innovative set of engineering assessment and management application tools, tailored specifically towards critical infrastructure risk analysis of fossil-fuelled power stations

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