Suparna Biswas (editor) - Internet of Things Based Smart Healthcare: Intelligent and Secure Solutions Applying Machine Learning Techniques (Smart Computing and Intelligence)
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- Book:Internet of Things Based Smart Healthcare: Intelligent and Secure Solutions Applying Machine Learning Techniques (Smart Computing and Intelligence)
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This book provides both the developers and the users with an awareness of the challenges and opportunities of advancements in healthcare paradigm with the application and availability of advanced hardware, software, tools, technique or algorithm development stemming the Internet of Things. The book helps readers to bridge the gap in their three understanding of three major domains and their interconnections:
Hardware tested and software APP development for data collection, intelligent protocols for analysis and knowledge extraction.
Medical expertise to interpret extracted knowledge towards disease prediction or diagnosis and support. Security experts to ensure data correctness for precise advice.
The book provides state-of-the-art overviews by active researchers, technically elaborating healthcare architectures/frameworks, protocols, algorithms, methodologies followed by experimental results and evaluation. Future direction and scope will be precisely documented for interested readers.Suparna Biswas (editor): author's other books
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This book series aims to establish itself as a medium for the publication of new research and development of innovative paradigms, models, architectures, conceptual underpinnings and practical implementations encompassed within smart computing and intelligence.
The scope of the series includes but is not limited to smart city, smart education, health informatics, smart ecology, data and computational analytics, smart society, smart learning, complex systems-chaos, computational thinking, brain computer interaction, natural/computer interaction, humanoid behaviour, and impact of educational psychology on computing.
The cornerstone of this series editorial policy is its unwavering commitment to report the latest results from all areas of smart computing and intelligence research, development, and practice. Our mission is to serve the global smart computing and intelligence community by providing a most valuable publication service.
This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd.
The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
Continuous growth in global population and the demand of healthcare, particularly for the elderly and physically disabled people, is a challenge in the current era. The growth in ageing population led to complex health issues and rise in healthcare expenditures. Conventional health monitoring system for these people is time consuming, inconvenient, and insufficient most of the times. However, there has been a demand for developing efficient healthcare solutions for these people for an improved lifestyle. Advances in artificial intelligence (AI) technologies and Internet of Things (IoT) have opened up a new revolution in the healthcare domain. The response time in diagnosis and treatment of elderly and disabled patient can be reduced through Internet of Things and wearable body sensors. Using low-cost and lightweight body sensors placed very close to the body of the patient, the lifestyle data can be collected, and the information, in turn, could be shared with the doctors and health caretakers remotely. Machine intelligence is another aspect to remote healthcare system in analyzing the huge and heterogeneous data collected by the sensors. The promising technological area of wearable sensors, IoT, and machine intelligence seems to afford a smart and intelligent means for an automated health monitoring system for elderly and disabled patients staying remotely. The intension of this chapter is to explore the advancement, modality, specification, and applications of wearable body sensors for acumination of body symptoms from remote patients. Then, the importance and necessity of machine intelligence for analysis of healthcare data will be discussed. Finally, a conceptual model integrating wearable body sensors, IoT, and machine intelligence for remote healthcare will be presented. The model may be helpful in reducing the complexities and healthcare expenditure faced by aging, physical disabilities and remote population.
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