Multimodal IoT-Based Autonomous Emergency and Response Care for Healthcare Ecosystems

Abstract

Emergency and response care is a critical part of a country's healthcare infrastructure. The nation's healthcare sector is more concerned with developing a comprehensive, autonomous emergency, and response care by including multimodal data collected from different IoT devices. The existing systems use the body area networks (BAN) along with IoT sensors to gather critical health data to save lives. This system considers data from biosensors, medical IoT sensors, and patient activity sensors. However, most of the decision-making part resides on the medical practitioners, and also there are few provisions for integrating multi modal data like x-rays, MRI, and CT images as a part of automated emergency and response system. The chapter is a holistic intelligent framework which includes multimodal data as a part of decision support systems. This system has multiple layers of data analysis, as each mode of data world require different processing and ML models.

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