The application of edge artificial intelligence in the Internet of Battlefield Things

This paper systematically discusses the indispensable role and technical pathways of edge artificial intelligence (AI) in the Internet of Battlefield Things (IoBT). Considering the high real-time, dynamic, and security demands of the battlefield environment, a hierarchical collaborative architecture design based on “terminal layer - intelligent edge layer - cloud layer” is proposed, and its practical value is analyzed in scenarios such as real-time situational awareness, autonomous weapon control, and soldier health monitoring. By addressing core challenges like heterogeneous device management, low-latency response, and robustness assurance, solutions for dynamic resource allocation, lightweight model deployment, and intelligent spectrum management are provided. Lastly, the security threats and defense strategies of edge intelligence are analyzed, building an integrated military-grade security architecture of “detection-response-recovery”. This paper provides theoretical support and technical reference for the practical deployment of edge AI empowering the IoBT.

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Publication Details

Published
2025-03-21
DOI
https://doi.org/10.1109/iscait64916.2025.11010328
Citations
1
Primary Topic
Technology and Security Systems
Type
article
Field-Weighted Citation Impact
3.25
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The application of edge artificial intelligence in the Internet of Battlefield Things

Jialin Ma, Yan‐Feng Wang, Qi Jia, Suzhen Wang
1 citations
Technology and Security Systems
3.25
article

The application of edge artificial intelligence in the Internet of Battlefield Things

Jialin Ma, Yan‐Feng Wang, Qi Jia, Suzhen Wang
article en
1 citations

Abstract

This paper systematically discusses the indispensable role and technical pathways of edge artificial intelligence (AI) in the Internet of Battlefield Things (IoBT). Considering the high real-time, dynamic, and security demands of the battlefield environment, a hierarchical collaborative architecture design based on “terminal layer - intelligent edge layer - cloud layer” is proposed, and its practical value is analyzed in scenarios such as real-time situational awareness, autonomous weapon control, and soldier health monitoring. By addressing core challenges like heterogeneous device management, low-latency response, and robustness assurance, solutions for dynamic resource allocation, lightweight model deployment, and intelligent spectrum management are provided. Lastly, the security threats and defense strategies of edge intelligence are analyzed, building an integrated military-grade security architecture of “detection-response-recovery”. This paper provides theoretical support and technical reference for the practical deployment of edge AI empowering the IoBT.

Air Force Engineering University (CN)
Openalex Percentile: Top 9%
Technology and Security Systems
3.25
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