Underwater Object Identification with Edge Computing Paradigms

Abstract

In this work, we propose a solution that simplifies the complex process of underwater object detection, surveillance and environmental monitoring. The approach proposed harnesses an Underwater Acoustic Sensor (UAS) system to detect and analyze objects within a three-dimensional underwater environment incorporating constraints through acoustic path loss models. The approach integrates three core components - Delaunay’s Convex Hull-Based Reconstruction, Laws of Magnetic Equilibrium and Doppler’s Effect in doing so. The UASs are optimally deployed in a grid format with each grid consisting of 8 sensors. The grid is equipped with an Insulated Magnetometer at the center to measure the net magnetic field intensity. The detected information is transmitted to a surface anchor/sink node for further analysis and detection. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.