Edge-of-Things in Personalized Healthcare Support Systems discusses and explores state-of-the-art technology developments in storage, sharing healthcare records of individuals in a secure manner that is globally distributed to incorporate best health care practices. The book provides a collection of research results that cover expertise in healthcare professionals, sharing of records over the cloud, access controls, rights of the shared document, privacy of the document, and edge computing techniques to identify the cause(s) of disease(s). The book advances personal healthcare, medical diagnosis, and treatment by applying IoT, cloud, and edge computing technologies in association with effective data analytics.
As medical records need to be shared with only a select few, new technologies must address clinician expertise and access to medical records in all media formats while also addressing privacy, security and access policies.
- Provides in-depth analysis on the state-of-the-art in healthcare systems and applications in modeling and design
- Presents discussions and explorations of the social impact on the intertwined use of emerging IT technologies for healthcare
- Covers system design and software building principles for healthcare using IoT, Cloud, and Edge technologies, along with the support of effective and efficient data analytics strategies
- Explores the latest algorithms using machine and deep learning in the areas of Cloud, Edge Computing, IoT and Healthcare analytics
1. Exploring the dichotomy on opportunities and challenges of smart technologies in healthcare systems
2. The architecture of smartness in healthcare
3. Personalized decision support for cardiology based on deep learning: an overview
4. Data-driven models for cuffless blood pressure estimation using ECG and PPG signals
5. A recommendation system for the prediction of drug-target associations
6. Towards building an efficient deep neural network based on YOLO detector for fetal head localization from ultrasound images
7. FunNet: a deep learning network for the detection of age-related macular degeneration
8. An improved method for automated detection of microaneurysm in retinal fundus images
9. Integration and study of map matching algorithms in healthcare services for cognitive impaired person
10. Emotion-recognition-based music therapy system using electroencephalography signals
11. Feedback context-aware pervasive systems in healthcare management: a Boolean Network approach
12. Mental stress detection using a wearable device and heart rate variability monitoring
13. Knowledge discovery and presentation using social media analysis in health domain
14. Computationally efficient integrity verification for shared data in cloud storage
15. Intelligent analysis of multimedia healthcare data using natural language processing and deep-learning techniques
16. Measurement of the effects of parks on air pollution in megacities: do parks support health betterment?
17. Internet of Things use case applications for COVID-19
Rajeswari Sridhar is currently working as an Associate Professor in the Department of Computer Science and Engineering at the National Institute of Technology, Tiruchirappalli, India. Her research interests include Cloud computing, Natural language processing, Information Retrieval, etc. She has guided 2 PhD students in the areas of Resource provisioning in Cloud computing and Access policies for data sharing through the cloud. She is currently guiding 5 research scholars in similar areas. She has published 70 articles in reputed journals and conferences. She is a member of the IEEE, ACM and CSI. G R Gangadharan is working as an Associate Professor in the National Institute of Technology, Tiruchirappalli, India. His research interests are mainly located on the interface between technological and business perspectives. He has published around 95 publications in the reputed international journals, conferences, and book chapters. He has also edited two books. He has received Ph.D. degree in Information and Communication Technology (2008) from the University of Trento, Trento, Italy and European University Association and an M.S. in Information Technology (2004) from Scuola Superiore SantAnna, Pisa, Italy. He is a Senior Member of IEEE and ACM. Michael Sheng is a full Professor and Head of Department of Computing at Macquarie University, Sydney, Australia. Before moving to Macquarie University, Michael spent 10 years at School of Computer Science, the University of Adelaide (UoA). Prof. Sheng has more than 400 publications as edited books and proceedings, refereed book chapters, and refereed technical papers in journals and conferences. He is ranked by Microsoft Academic as one of the Top Authors in Services Computing (ranked the 5th of All Time worldwide). He is the recipient of the AMiner Most Influential Scholar Award on IoT (2007-2017), ARC Future Fellowship (2014), Chris Wallace Award for Outstanding Research Contribution (2012), and Microsoft Research Fellowship (2003). Rajan Shankaran is a Senior Lecturer in the Department of Computing at Macquarie University. He leads the 'Security, Communications, and Networks Research Group'. He obtained his PhD in Wireless and Mobile communications from the Western Sydney University (Sydney, Australia). He has previously held an appointment at Western Sydney University. His research focuses on Internetworking security and Quality of service with a special focus on Body Area Networks and Medical Implants, Cognitive Radio, Internet of Things and Vehicular Networks and D2D Communications. He has supervised several Master by Research (MRES) and PhD students to successful completion in these areas. He has published in reputed journals such as IEEE Transactions on Vehicular communications and IEEE Sensors as well as in several prestigious conferences. He has also acted as a reviewer for many SCI journals. He has also served in Technical Program Committees for several conferences in computer networking and security.
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