An Efficient 3D Localization Algorithm for Mobile Target Nodes Utilizing Enhanced Adaptive Butterfly Optimization

Accurate localization is a cornerstone of Wireless Sensor Network (WSN) applications, especially in three‐dimensional environments. The complexity of 3D localization increases with the constraints of cost and resource efficiency. This paper introduces an innovative concept that leverages the projection of virtual anchor nodes for 3D localization utilizing a single static anchor node and multiple movable target nodes. Upon the entry of a movable target node within the operational range of an Anchor Node (AN), six virtual anchors are strategically projected at an identical radial distance corresponding to the separation between the anchor node and the target node. From these projections, three virtual anchors are meticulously selected based on their spatial proximity to both the anchor node and the movable unknown nodes, thereby meeting the minimum necessity of four anchor nodes to accurately compute the spatial coordinates of the target node within a three‐dimensional framework. This research employs an enhanced adaptive butterfly optimization algorithm (EABOA) to localize sensors with more precision, demonstrating its effectiveness in 3D environments. Comparative analysis shows that the EABOA outperforms other techniques in terms of accuracy and convergence speed. This methodology applies to a wide range of fields, including disaster management, industrial automation, and environmental monitoring. The study offers a scalable and cost‐effective solution for 3D WSN localization.