Routing Protocol Mechanisms in Wireless Sensor Networks using Fuzzy Interface Algorithm

Numerous sensor nodes make up a wireless sensor network. Sensor nodes work together to send information about the environment to the base station. Nodes are susceptible to failure during these operations due to power failure, hardware or software failure, etc.. Consequently, delivering dependable packages necessitates achieving two important objectives: energy efficiency and minimized error rate. A novel approach is proposed to distribute the workload among each sensor node to accomplish these objectives. When estimating the scope of communication between nodes, uncertainties are dealt with using the fuzzy logic method. During some weather hazards, the features and cables are particularly challenging to monitor with simple devices in the WAN area. Remote sensing units are used to check and display the feature conditions to resolve this issue. Using machine learning algorithms, the collected data will be analyzed and processed to create a prediction horizon that will be useful for environmental studies and early warning systems. The MatLab2020b simulation program, which has useful tools and learning applications, will be used to carry out this task. The FIS algorithm obtained a cost distance of just 629 m out of the total WSN sensor lengths of 2600 m, which is the best cost among all implemented routing protocol techniques in this study.