Paper Type
Complete
Abstract
AI Innovations in the IoT for Real-Time Patient Monitoring On one hand, the current traditional centralized healthcare architecture poses numerous issues, including data privacy, delay, and security. Here, we present an AI-enabled decentralized IoT architecture to address such challenges during a pandemic and critical care settings. This work presents our architecture to enhance the effectiveness of the current available federated learning, blockchain, and edge computing approach, maximizing data privacy, minimizing latency, and improving other general system metrics. Experimental results demonstrate transaction latency, energy consumption, and data throughput orders of magnitude lower than competitive cloud solutions.
Paper Number
1825
Recommended Citation
sammangi, Harsha; Ambati, Loknath Sai; Liu, Jun; and Bojja, Giridhar Reddy, "AI-Driven Decentralized IoT for Secure and Scalable Healthcare" (2025). AMCIS 2025 Proceedings. 3.
https://aisel.aisnet.org/amcis2025/health_it/sig_health/3
AI-Driven Decentralized IoT for Secure and Scalable Healthcare
AI Innovations in the IoT for Real-Time Patient Monitoring On one hand, the current traditional centralized healthcare architecture poses numerous issues, including data privacy, delay, and security. Here, we present an AI-enabled decentralized IoT architecture to address such challenges during a pandemic and critical care settings. This work presents our architecture to enhance the effectiveness of the current available federated learning, blockchain, and edge computing approach, maximizing data privacy, minimizing latency, and improving other general system metrics. Experimental results demonstrate transaction latency, energy consumption, and data throughput orders of magnitude lower than competitive cloud solutions.
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