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IoT-Enabled Remote Patient Monitoring for Chronic Disease Management and Cost Savings: Transforming Healthcare
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Author(s): J. Malathi (Department of Computer Science and Business Systems, Sri Sai Ram Engineering College, India), K. R. Kusha (Department of Machine Learning, BMSCE, Bengaluru, India), Samson Isaac (Department of Biomedical Engineering, Karunya Institute of Technology and Sciences, India), Alabazar Ramesh (Department of Computer Science and Engineering, B V Raju Institute of Technology, India), M. Rajendiran (Department of Computer Science and Engineering, Panimalar Engineering College, India)and Sampath Boopathi (Mechanical Engineering, Muthayammal Engineering College, India)
Copyright: 2024
Pages: 18
Source title:
Advances in Explainable AI Applications for Smart Cities
Source Author(s)/Editor(s): Mangesh M. Ghonge (Sandip Institute of Technology and Research Centre, India), Nijalingappa Pradeep (Bapuji Institute of Engineering and Technology, India), Noor Zaman Jhanjhi (School of Computer Science, Faculty of Innovation and Technology, Taylor’s University, Malaysia)and Praveen M. Kulkarni (Karnatak Law Society's Institute of Management Education and Research (KLS IMER), Belagavi, India)
DOI: 10.4018/978-1-6684-6361-1.ch014
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Abstract
The integration of internet of things (IoT) technology in healthcare has revolutionized chronic disease management and healthcare cost reduction. IoT-enabled remote patient monitoring systems provide real-time insights into patients' health parameters, enabling informed decisions and patient participation. The central hub of these systems provides accurate, up-to-date patient data, enabling timely alerts for chronic diseases. Electronic health records (EHR) offer comprehensive historical health data while ensuring privacy and security. However, challenges like data security, scalability, and interoperability remain. The healthcare industry must improve security measures, standardize interoperability, and adopt advanced analytics, artificial intelligence, and wearable technology for personalized, data-driven, and cost-effective care.
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