Wireless Sensor Network in Reliable Transportation Theory Using Fuzzy Logic and Genetic Algorithm

In a wireless sensor network (WSN), reduced energy resources between nodes present a complicated challenge in terms of data collection, routing, and aggregation, as all these procedures consume energy. The network's stability period, lifetime, and potential are all metrics that must be optimized within the limits. Firstly, this research describes the WSN architecture, its main components, characteristics, and applications in various fields. The Cluster Head (CH) selection problem in heterogeneous wireless sensor networks has received little attention and needs to be improved further to fully use WSN's potential. In this research, a novel WSN framework is designed by using transportation theory Clustering is performed using the fuzzy set theory. Furthermore, based on clustering, the CH is defined by computing the Composite Reputation Value (CRV) value. The entire process works toward designing a reliable WSN system and taking the point of energy consumption into consideration for the entire design and its working. Finally, the results revealed that the proposed WSN framework is 99.9% efficient, which is higher than any other conventional method.