AI-Driven IoT Architecture Using Electric Vehicles for Emergency Healthcare Monitoring and Response
Abstract
The increasing demand for timely emergency healthcare services in mobile and resource-constrained settings requires reliable, secure, and low-latency access to patient data and decision support. This paper proposes an AI-driven IoT architecture that leverages electric vehicles (EVs) as mobile edge nodes to bridge wearable and in-vehicle medical sensors with cloud analytics and downstream Health IT services. The EV gateway performs local preprocessing, buffering (store-and-forward), and optional lightweight screening, then transmits authenticated, encrypted summaries to a cloud decision support pipeline for risk scoring, alerting, and integration with clinical dashboards and EHR/EMR interfaces. A scenario-based evaluation compares connected and intermittent connectivity conditions and contrasts the proposed design with a cloud-only baseline, demonstrating improved data continuity and reduced time-to-first-alert during outages. The results indicate that EV-enabled edge computing can enhance emergency monitoring workflows while maintaining practical security and deployment feasibility.
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- Authors
- Srivastava, P., Bajaj, M., & Güven, A. F.
- Affiliations
- Oracle America Inc.,Seattle,WA,USA
- Graphic Era University (IN)
- Yalova University (TR)
- Venue
- SoutheastCon 2026
- Publisher
- IEEE
- Published
- 2026-02-20
- Pages
- 1-6
- ISSN
- 1091-0050 (ISSN-L)
- OpenAlex
- W7154980229
- Semantic Scholar
- 1a3b0ae11f55bffe7cbda4ece85ba5346022a3ae
- Cited by
- 0
- References
- 18
- FWCI
- 0.00
- Type
- conference paper
- Open access
- closed
- Locations
- Proceedings of IEEE Southeastcon (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Health Sciences › Health Professions › Health Information Management › Innovation in Digital Healthcare Systems
- Keywords
- electric vehicles, mobile edge computing, wearable medical sensors, IoT architecture, encrypted data transmission, risk scoring, alerting, clinical dashboards, electronic health record integration, intermittent connectivity, resource-limited settings
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