IoT assisted Hierarchical Computation Strategic Making (HCSM) and Dynamic Stochastic Optimization Technique (DSOT) for energy optimization in wireless sensor networks for smart city monitoring

Abstract

Presently, Innovations and applications of the Internet of things (IoT) are empowering smart city activities worldwide. IoT technology is creating smart building frameworks with a heritage structure to enhance sustainability and energy optimization. The primary issue of energy consumption in sensor node depends on the average rate of power consumption of node times in Wireless Sensor Network (WSN) leads to several power optimization issues in the communication network during information sharing and processing. To address the optimization issues this research mainly focused to design and develop a Hybridized IoT assisted Hierarchical Computation Strategic Making (HCSM) Approach and Dynamic Stochastic Optimization Technique (DSOT) to oversee the energy optimization issue in a Wireless Sensor Network for smart city monitoring. Furthermore, the energy-constrained sensor node negotiates numerous activities associated with network and the selection of a sensor cluster node optimizes the energy consumption and sensing accuracy during information processing. The experimental outcomes show that the HCSM & DSOT approaches are found capable of improving the energy efficiency of wireless sensor network and sensor cluster node selection at lab scale experimental validation.