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Спутники
РН
SpaceX
Роскосмос
NASA
СпутникиРНSpaceXРоскосмосNASAPublication date: 13 April 2026
Source: Applied Mechanics and Materials Vol. 935
Author(s): Francis Anyebe Oteikwu, Osezua Ejodame, Norman Osa-Uwagbue
This paper proposes a conceptual framework for an intelligent soldier monitoring system, integrating multimodal sensor networks with Multimodal Large Language Models (MLLMs) to advance battlefield healthcare and situational awareness. The envisioned architecture combines physiological sensors (e.g., heart rate variability, cortisol levels, core temperature) with environmental sensors (e.g., acoustic, visual, thermal) through an edge-AI processing pipeline. Based on our literature review, we target three key limitations in existing systems: (1) real-time data fusion latency (aiming for <100 ms), (2) predictive health analytics accuracy (aiming for >90% for critical conditions), and (3) adaptive threat response capabilities. Our research suggests that the proposed technologies are at an early conceptual stage, supported by analysis of existing component technologies not yet integrated into a cohesive system. We identify challenges in power efficiency (targeting <50 mW per sensor) and ethical implementation, proposing solutions such as on-device processing and explainable AI. This work establishes a theoretical foundation and a research roadmap for future development of advanced military monitoring systems, balancing performance with operational and ethical considerations..
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