IoT-Enabled Smart Health Care Systems
Dr. B. JegaJothi, Dr. K. Natarajan, Dr. B.Sandhiya
Indexed In: Google Scholar
Release Date: 26/06/2025 | Copyright:@2025 | Pages: 465
DOI: 10.71443/9789349552548
ISBN10: 9349552540 | ISBN13: 9789349552548
IoT-enabled smart health care systems integrate interconnected devices, sensors, and cloud technologies to revolutionize patient monitoring and medical services. These systems enable real-time data collection, remote diagnosis, and personalized treatment, enhancing efficiency and patient outcomes. Wearable devices and smart medical equipment continuously gather vital signs and transmit data securely to health care providers, facilitating timely interventions. IoT also streamlines hospital operations through smart asset tracking and predictive maintenance. By bridging patients, doctors, and health infrastructures, IoT-enabled smart health care systems promise improved accessibility, cost-effectiveness, and proactive care management, addressing challenges in modern health care delivery and advancing digital health innovations.
IoT-enabled smart health care systems revolutionize traditional health care by integrating connected devices, sensors, and real-time data analytics to improve patient monitoring, diagnostics, and treatment outcomes. These systems enable remote patient care, continuous vital sign tracking, and early detection of health issues, reducing hospital visits and healthcare costs. Wearable devices, smart medical equipment, and cloud-based platforms enhance data sharing among patients, doctors, and caregivers, ensuring timely interventions and personalized care plans. However, challenges like data privacy, cybersecurity, and interoperability must be addressed for widespread adoption. Overall, IoT in health care fosters more efficient, accessible, and patient-centric medical services worldwide.
Sathiyamoorthy M is an Assistant Professor and Research Scholar in the Department of Computer Science and Engineering at Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, India. He holds a B.Sc in Applied Sciences, MCA, M.Phil in Computer Science, and M.Tech in Computer Science and Engineering. With over 10 years of teaching and 3 years of industry experience, he is a Life Member of ISTE. His Ph.D. research focuses on AI-based Early Warning Systems for Urban Flooding. He has presented 5 IEEE conference papers, awaiting IEEE Xplore publication.
Dr. B. JegaJothi obtained her B.E in Electrical and Electronics engineering from Anna University, Chennai, Tamil Nadu, India in the year of 2006 and Master of engineering in Power Electronics and Drives in St.Peter's University, Chennai, Tamil Nadu, India in the year of 2011 respectively. She received his Ph.D in electrical engineering from Anna University, Chennai, Tamil Nadu, India in the year of 2022. She has over nine years of Teaching Experience and currently, she is working as Research Associate, SRS Tech Solutions, Chennai. She has presented many papers in national and international Conferences. Her Research interest covers Renewable Energy Systems, Artificial Intelligence techniques, Neural Networks and Embedded systems.
Dr. K. Natarajan received his Ph.D. from Anna University, Chennai, in 2017, his Master of Engineering degree in Electrical Machines from PSG College of Technology, Coimbatore, in 2012, and his Bachelor of Engineering in Electrical and Electronics Engineering from Sri Ramakrishna Institute of Technology, Coimbatore, in 2009. He has 15 years of teaching experience in various engineering colleges across India. His areas of interest include power electronic converters, electrical machines and drives, renewable energy systems, embedded systems, the Internet of Things, and electric vehicles. He is currently working as Professor and Head of the Department of Electrical and Electronics Engineering at Trinity College of Engineering and Technology, Peddapalli, Telangana.He has several journal publications and patents to his credit.
Dr.B.Sandhiya, received her B.Tech degree from Anna University in 2012 and ME degree from Anna University in 2016. She pursued Ph.D. in the area of Medical Image Processing with Deep Learning Technology in Anna University, Chennai. She has 8.8 years of experience in the teaching & educational field and currently works as an Assistant Professor (Department of CSE) in Christ University, Bangalore. She has published 15 papers in International Journals and Conferences including Scopus Indexed Journals. She has received fund Rs.4,47,000 from Indian Council for Medical Research for the project title “An association based deep learning framework for detecting COVID-19 disease patterns from bimodal clinical data”. She has been authorized as a mentor or guide for the TNSCST student project scheme 2022–2023 for the project entitled “Internet Of Things Based Dual Axis Solar Tracking System”. Her areas of interest are Artificial Intelligence, Machine Learning, Deep Learning, Medical Image Processing and Analysis.