This new volume discusses the applications and challenges of deep learning and the internet of things for applications in healthcare. It describes deep learning techniques in conjunction with IoT used by practitioners and researchers worldwide.
The authors explore the convergence of IoT and deep learning to enable things to communicate, share information, and coordinate decisions. The book includes deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. Chapters look at assistive devices in healthcare, alerting and detection devices, energy efficiency in using IoT, data mining for gathering health information for individuals with autism, IoT for mobile applications, and more. The text also offers mathematical and conceptual background that presents the latest technology as well as a selection of case studies.
Table of Contents
1. Deep Learning for Healthcare
C. Deepa and K. Tharageswari
2. Role of AI in Healthcare
3. Case Studies: Healthcare and Deep Learning
Ashish Tripathi, Arun Kumar Singh, K. K. Mishra, Pushpa Choudhary, and Prem Chand Vashist
4. Assistive Devices and IoT in Healthcare Functions
Abhineet Anand, Sai Prasad Mishra, and Subrata Sahana
5. Impact of IoT on Healthcare-Assistive Devices
R. Indrakumari, Rishabh Kumar Srivastava, Subba, and Manavalan
6. Smart Fall Detection Systems for Elderly Care
Pratik Bhattacharjee and Suparna Biswas
7. Smart Sensors Transform Healthcare System
Amrita Rai, Shylaja Vinaykumar Karatangi, Reshu Agarwal, and Om Prakash
8. Healthcare Applications of the Internet of Things (IoT)
Ritam Dutta, Subhadip Chowdhury, and Ahmed A Elngar
9. Mobile-App-Enabled System for Healthcare
Vikram Sandhu and Harleen Kaur
10. Energy-Efficient Network Design for Healthcare Services
Amit Sehgal, T. L. Singal, Rajeev Agrawal, and Sweta Sneha
11. Applying Data Mining to Detect the Mental State and Small Muscle Movements for Individuals with Autism Spectrum Disorder (ASD)
Rashbir Singh, Prateek Singh, and Latika Kharb
Krishna Kant Singh, PhD, is Professor in Computer Science and Engineering, Faculty of Engineering and Technology, Jain (Deemed-to-be University), Bengaluru, India. He has wide teaching and research experience. He has authored more than 50 research papers in Scopus- and SCIE-indexed journals as well as 25 technical books. He is also Associate Editor of the Journal of Intelligent & Fuzzy Systems and IEEE ACCESS and a guest editor of Open Computer Science. He is also a member of the editorial board for Applied Computing & Geoscience.
Akansha Singh, PhD, is Associate Professor in the Department of Computer Science and Engineering, ASET, Amity University, Noida, India. She has to her credit more than 40 research papers, 20 books, and numerous conference papers. She has been the editor for books on emerging topics and has served as a reviewer and technical committee member for multiple conferences and journals. She is also the Associate Editor for IEEE Access. Dr. Singh has also undertaken a government-funded project as a principal investigator. Her research areas include image processing, remote sensing, IoT, and machine learning.
Jenn-Wei Lin, PhD, is Professor with the Department of Computer Science and Information Engineering, Fu Jen Catholic University, Taiwan. Prior to that, he was a researcher with Chunghwa Telecom Co., Ltd., Taoyuan, Taiwan, from 1993 to 2001. His current research interests include cloud computing, mobile computing and networks, distributed systems, and fault-tolerant computing.
Ahmed A. Elngar, PhD, is the Founder and Head of Scientific Innovation Research Group and Assistant Professor in the Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef, Egypt, where he is also Director of the Technological and Informatics Studies Center. Dr. Elngar has published more than 25 scientific research papers and several books. He participates in many professional activities such as organizing workshops hosted by universities throughout Egypt.