The Internet of Things (IoT) and the Wireless Sensor Network (WSN) concepts are currently combined to improve data transmission based on sensors in near future applications. Since IoT devices exist in WSN with built-in batteries, power efficiency is a challenge that must be resolved. Clustering and routing are effectively treated as methods for reducing the dissipation of energy and maximising WSN IoT support life. This paper presents the new Energy Aware Adaptive Fuzzy neuro clustering with the WSN assisted IoT algorithm EAANFC-MR. EAANFC-MR is proposed for two main stages, clustering and multihop routing on the basis of EAANFCs. For selecting CHs with Residual Energy (RE) and Distance and Node degrees the EAANFC based cluster technique is used. The QOB-FO algorithm, which is used as a Multihop Route Technique, is then used to select optimised roads to the destination. MATLAB is used to simulate the proposed EAANFC-MR model. The goodness of the EAANFC-MR model interspersed with various aspects was demonstrated through a series of experiments.
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