Pure Chain-Integrated AI Framework for Health Risk Monitoring of Military Personnel

Abstract

Military personnel must remain in strong physical and mental health to carry out their duties. However, many chronic diseases like diabetes can develop silently over time. If detected early, the risk can often be managed with changes in routine, diet, or medication. Yet early detection relies on access to health data, and for military applications, that data is often sensitive and highly confidential. Most AI systems that predict health risks do not include strong privacy safeguards or consent control. This paper presents a secure health monitoring system designed specifically for military environments. The system combines AI with blockchain to ensure privacy, transparency, and individual control. It uses Pure Chain to manage access permissions through smart contracts. Military personnel must explicitly grant consent before their data is used for analysis. The health data, stored securely through IPFS, is only shared with the AI model after consent is confirmed. The AI model predicts health risks. Once a prediction is made, the result is sent securely to the respective personnel through a Flask-based backend. This way, the system maintains privacy while enabling timely health warnings. The model achieved 90.13% accuracy in cross-validation, 82.89% test accuracy, and an AUC of 0.90, showing strong potential for real-world deployment.

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