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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.

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Underwater Object Identification with Edge Computing Paradigms

  • 会议论文

  • 发表日期：

    2026年

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  • Shekhar Tyagi,
  • Akshat Shah,
  • Abhishek Srivastava

摘要

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.