Intelligent IoT Systems in Personalized Health Care

Intelligent IoT Systems in Personalized Health Care provides a forum for advancing IoMT learning in parallel computing environments, focusing on identifying and acquiring valid knowledge sources for biomedical engineering applications.

\n Format: Paperback / softback
\n Length: 360 pages
\n Publication date: 11 November 2020
\n Publisher: Elsevier Science Publishing Co Inc
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Intelligent IoT Systems in Personalized Health Care presents a remarkable platform for advancing the technical development of IoMT learning in parallel computing environments across biomedical engineering and diverse domains. By adopting an interdisciplinary approach, the book delves into the methods employed to identify and acquire valid, potentially valuable knowledge sources. This comprehensive volume offers novel, in-depth, fundamental research contributions from a methodological/application perspective, aimed at helping readers gain a deeper understanding of the fusion of AI with IoT and its remarkable capabilities in addressing a wide array of problems within biomedical engineering and its real-world personalized health care applications. The book is particularly valuable for researchers interested in exploring the significance of IoT-based architectures in performing predictive analytics of user activities for sustainable health.

Introduction:
The Internet of Medical Things (IoMT) has emerged as a transformative technology in healthcare, enabling the collection, analysis, and interpretation of vast amounts of patient data. With the increasing demand for personalized health care, there is a growing need for intelligent IoT systems that can provide accurate and timely insights into patient health. This book aims to provide a comprehensive overview of intelligent IoT systems in personalized health care, focusing on their technical advancements, applications, and challenges.

Technical Advancements:
One of the key technical advancements in intelligent IoT systems is the integration of artificial intelligence (AI) and machine learning (ML) algorithms. AI and ML algorithms can analyze large datasets and identify patterns and trends that are difficult for humans to detect. This integration allows for more accurate diagnosis, treatment planning, and patient monitoring. Another important advancement is the use of edge computing, which enables real-time processing and analysis of patient data. Edge computing reduces the latency and bandwidth requirements, making it ideal for remote and underserved areas.

Applications:
Intelligent IoT systems in personalized health care have numerous applications across various domains. In the healthcare industry, they can be used for patient monitoring, remote diagnosis, and drug delivery. For example, wearable devices can monitor vital signs, track exercise patterns, and provide real-time feedback to patients. AI-powered algorithms can analyze this data and provide personalized recommendations for diet, exercise, and medication. In the healthcare industry, intelligent IoT systems can also be used for medical equipment management, inventory control, and patient safety. For example, sensors can be used to monitor the condition of medical equipment and alert healthcare professionals if any issues arise.

Challenges:
Despite the numerous benefits of intelligent IoT systems, there are also several challenges that need to be addressed. One of the biggest challenges is the security and privacy of patient data. With the increasing amount of sensitive information being collected and transmitted, there is a risk of data breaches and unauthorized access. Another challenge is the interoperability of different devices and systems. Different healthcare providers use different devices and systems, making it difficult to share and exchange patient data.

Conclusion:
Intelligent IoT systems in personalized health care have the potential to revolutionize healthcare by providing accurate and timely insights into patient health. However, there are several challenges that need to be addressed to ensure the security and privacy of patient data, and to promote interoperability of different devices and systems. By continuing to invest in research and development, we can overcome these challenges and realize the full potential of intelligent IoT systems in personalized health care.

\n Weight: 584g\n
Dimension: 153 x 230 x 22 (mm)\n
ISBN-13: 9780128211878\n \n