Optimizing Industrial Wireless Sensor Networks Using the Mean Shift Algorithm for Enhanced Efficiency and Longevity

Abstract

Optimizing sensor location and data aggregation in Industrial Wireless Sensor Networks (IWSNs) is essential to increasing network efficiency and prolonging the system's operational lifecycle. This study suggests using the Mean Shift method to improve sensor placement and data handling, hence enhancing the performance of IWSNs. We obtain notable gains in network longevity and energy efficiency by implementing the Mean Shift algorithm in a three-dimensional industrial setting. The approach's usefulness is demonstrated by experimental findings, which result in reduced energy consumption and more efficient data aggregation.