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Multimodal IoT-Based Autonomous Emergency and Response Care for Healthcare Ecosystems
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Author(s): D. Sudha (Sathyabama Institute of Science and Technology, India), S. Violet (Meenakshi College of Engineering, India), Thirupurasundari D. R. (Bharath Institute of Higher Education and Research, India), Anlin Sahaya Infant Tinu M. (Rohini College of Engineering and Technology, India), Balasubramanian Prabhu Kavin (SRM Institute of Science and Technology, India)and Santosh Reddy Addula (University of the Cumberlands, USA)
Copyright: 2025
Pages: 22
Source title:
Future Innovations in the Convergence of AI and Internet of Things in Medicine
Source Author(s)/Editor(s): Velliangiri Sarveshwaran (National Chung Cheng University, Taiwan), Karthikeyan Periyaswami (National Chung Cheng University, Taiwan)and Keping Yu (University of Hosei, Japan)
DOI: 10.4018/979-8-3693-7703-1.ch005
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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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