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Corrosion of aircraft and rotorcraft costs the US military billions of dollars annually, and is by far the largest single maintenance cost driver for Navy and Marine Corps airframes. The various forms of localized corrosion, such as pitting corrosion, crevice corrosion, exfoliation, and environment assisted cracking, are particularly destructive and frequently occur without any outward signs of damage. To maintain acceptable risk levels, costly schedule based inspection and maintenance practices are used. In order to move away from schedule based maintenance and enable condition based maintenance techniques, a miniature corrosion monitoring smart sensor network to support diagnostics and prognostics for aircraft health management is being developed. The development of an ultra-low power, wireless, embedded corrosion monitoring system based on the IEEE 1451.X open architecture for smart transducers will be discussed in this paper. This system, funded through a NAVAIR Phase II SBIR, is capable of monitoring, recording, and analyzing data from environmental and corrosivity sensors for the purpose of aircraft health management. This paper will present the use of a standard network architecture consisting of transducer interface modules (TIMs) and network capable application processors (NCAPs), allowing for ease of system integration and plug-and-play simplicity. The hardware and software designs, relying on ultra-low power components and embedded energy conservation algorithms, will be presented. This low-power approach to aircraft corrosion and health monitoring is ideal for integration with energy harvesting techniques, giving rise to a self-contained, self-sustaining sensor network. Finally, corrosion modeling and embedded algorithm development based on data fusion from both commercial off the shelf (COTS) and novel, developmental sensors will be discussed and shown to be powerful diagnostic and prognostic tools.