Advances in Healthcare IoT Devices for AI Driven Clinical Decision Supporting System for Emergency Medicine

Abstract

Advances in artificial intelligence (AI), the Internet of Things (IoT) and its healthcare-focused subset, the Internet of Medical Things (IoMT) are gradually improving the quality of emergency medicine, speeding up the diagnostic process, improving patient tracking and helping doctors make decisions in real time. This study carefully looks at the technological progress made between 2020 and Aug. 2025 in three main areas: telemedicine tools, wearable health monitoring systems, and point-of-care diagnostic devices. It shows how new technologies like AI built into wearables, cloud-connected remote diagnostics, CRISPR-based detection systems, and mobile-enabled biosensors have all made emergency response systems stronger. The research also looks at how deep learning models have changed over time, from traditional architectures to transformer-based networks, and how they might be used in clinical decision support systems. The combination of these systems with edge computing, federated learning, and image-based diagnostics has changed the way data is processed and acted upon in critical care situations. This analysis looks ahead at how AI-IoT convergence will affect emergency medicine in the future, the problems it will face when it is put into practice, and what the future direction will be.