Abstract
The paper describes the use of a wireless sensor network (WSN) for performing parallel pattern recognition computations. A complexity analysis indicates that the proposed algorithm is independent of the number of nodes and hence may scale up indefinitely with the network. It's shown that any material object once overlaid with a WSN, develops a latent associative memory, which enables the object to memorise some of its critical internal states for a real time comparison with those induced by the transient external conditions.