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

Author Connect URL

https://authorconnect.aisnet.org/conferences/AMCIS2025/papers/1825

Comments

SIGHEALTH

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Aug 15th, 12:00 AM

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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