Advanced Bio-inspired Plausibility Checking in a Wireless Sensor Network Using Neuro-immune Systems: Autonomous Fault Diagnosis in an Intelligent Transportation System

Recent developments in wireless sensing technology lead to implement advanced algorithms for distributed data processing in various applications; intelligent transportation system is one of the main applications of the advanced networked sensing technology to monitor the environmental conditions for controlling the quality of the products. To ensure the desired performance of a wireless sensor network, the reliability of the network records needs to be evaluated using an efficient data processing algorithm. In this paper, a new application of a bio-inspired technique is introduced for autonomous plausibility checking in a wireless sensor network; at first, an optimized Neuro-immune system is introduced and developed to predict the sensor records; then, performance of the proposed Neuro-immune system is compared with a neural network approximation mechanism. A secondary algorithm evaluates the sensor records to check the plausibility of the records in the wireless sensor network. The proposed data processing algorithm could serve in various applications of wireless sensor networks.