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An Extended Reality(XR)-Based Tactical Support System Integrating Edge-AI Threat Detection and a Distributed Sensor Network for High-Risk Operations

Author

Listed:
  • Chandrkha R

    (Department of Electrical Engineering, Sri Ranganathar Institute of Engineering and Technology, Coimbatore, India)

  • Kiran Kumar S

    (Department of Electrical Engineering, Sri Ranganathar Institute of Engineering and Technology, Coimbatore, India)

  • Vikram J

    (Department of Electrical Engineering, Sri Ranganathar Institute of Engineering and Technology, Coimbatore, India)

  • Palanivel D

    (Department of Electrical Engineering, Sri Ranganathar Institute of Engineering and Technology, Coimbatore, India)

Abstract

Until now, most defence-oriented immersive systems relied primarily on VR and AR interfaces to visualize mission data, maps, and environmental cues. These solutions offered useful overlays but lacked the capability to perform real-time threat identification directly from the soldier’s visual feed. Building on these earlier technologies, the proposed system introduces a next-generation Extended Reality (XR)–based tactical platform that not only displays information but also performs intelligent on-ground analysis using integrated image processing.The XR headset is equipped with a compact camera module that captures images of individuals encountered during mission entry. These images are processed through an AI-driven facial recognition model, enabling the system to instantly determine whether the person matches a known terrorist or high-risk suspect stored in an encrypted database. When a match is found, the soldier receives an immediate XR alert, while the base station simultaneously receives the captured image and identity confirmation for coordinated decision-making.

Suggested Citation

  • Chandrkha R & Kiran Kumar S & Vikram J & Palanivel D, 2026. "An Extended Reality(XR)-Based Tactical Support System Integrating Edge-AI Threat Detection and a Distributed Sensor Network for High-Risk Operations," International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 15(3), pages 1526-1535, March.
  • Handle: RePEc:bjf:ijltem:v:15:y:2026:i:3:a:2296
    DOI: 10.51583/IJLTEMAS.2026.150300134
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