AI and IoMT Convergence for Emergency Healthcare: Aadhaar Authentication, Secure Data Management, and Automated Fracture Detection

Abstract

The Internet of Medical Things (IoMT) and artificial intelligence enhance real-time data management by optimizing the integration of emergency units. In this study, we propose an AI-based IoMT framework to facilitate quick patient identification and delivery of critical support. In emergencies, when facial recognition is not possible, the biometric fingerprint system (Unique Identification Authority of India [UIDAI] Aadhaar repo) will assist in accurately identifying the patient and retrieving their full medical history. IoMT-enabled ambulance devices read physiological signals (ECG, SpO2, BP, Temperature), which are analyzed by fog computing nodes for anomalies and securely transmitted to a cloud server. The AI algorithm will perform predictive risk assessments, support triage prioritization, and optimize treatment. The blockchain-based asset management layer will ensure record accuracy and prevent tampering. Federated identifiability will improve care quality and services at the point of care. This approach will reduce or eliminate the need to defer or palliate care when patients cannot consent, as interoperability across biometrics, IoMT, cloud, and hospital infrastructure will enhance response times.

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