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Real-Time Data Analytics for Large Scale Sensor Data. Advances in ubiquitous sensing applications for healthcare

  • ID: 4768629
  • Book
  • September 2019
  • 298 Pages
  • Elsevier Science and Technology
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Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the development of software methods, techniques and tools, applications, governance and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. The book captures the essence of real-time IoT based solutions that require a multidisciplinary approach for catering to on-the-fly processing, including methods for high performance stream processing, adaptively streaming adjustment, uncertainty handling, latency handling, and more.

  • Examines IoT applications, the design of real-time intelligent systems, and how to manage the rapid growth of the large volume of sensor data
  • Discusses intelligent management systems for applications such as healthcare, robotics and environment modeling
  • Provides a focused approach towards the design and implementation of real-time intelligent systems for the management of sensor data in large-scale environments

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1. Internet of things in healthcare: Smart devices, sensors, and systems related to diseases and health conditions 2. Real-time data analytics in healthcare using the Internet of things 3. Lightweight code self-verification using return-oriented programming in resilient IoT 4. Monte-Carlo Simulation models for reliability analysis of low-cost IoT communication networks in smart grid 5. Lightweight ciphertext-policy attribute-based encryption scheme for data privacy and security in cloud-assisted IoT 6. Soft sensor with shape descriptors for flame quality prediction based on LSTM regression 7. Communication-aware edge-centric knowledge dissemination in edge computing environments 8. An effective blockchain-based, decentralized application for smart building system management 9. Privacy and security of internet of things devices 10. Software-defined networking for the Internet of things: Securing home networks using SDN

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Das, Himansu
Himansu Das is working as an as Assistant Professor in the School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. He has received his B. Tech and M. Tech degree from Biju Pattnaik University of Technology (BPUT), Odisha, India. He has published several research papers in various international journals and conferences. He has also edited several books of international repute. He is associated with different international bodies as Editorial/Reviewer board member of various journals and conferences. He is a proficient in the field of Computer Science Engineering and served as an organizing chair, publicity chair and act as member of program committees of many national and international conferences. He is also associated with various educational and research societies like IACSIT, ISTE, UACEE, CSI, IET, IAENG, ISCA etc., His research interest includes Grid Computing, Cloud Computing, and Machine Learning. He has also 10 years of teaching and research experience in different engineering colleges.
Dey, Nilanjan
Nilanjan Dey, PhD, is visiting fellow of the University of Reading, UK, and visiting Professor at Wenzhou Medical University, China and Duy Tan University, Vietnam. He was an honorary visiting scientist at Global Biomedical Technologies Inc., USA (2012-2015). Dr. Dey has authored/edited more than 45 books with Elsevier, Wiley, CRC Press, and Springer, and published more than 300 papers. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, Associated Editor of?IEEE Access and International Journal of Information Technology. He is the Series Co-Editor of Tracts in Nature-Inspired Computing (Springer), Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier), Series Editor of Computational Intelligence in Engineering Problem Solving and Intelligent Signal Processing and Data Analysis, CRC.?His main research interests include medical imaging, machine learning, computer-aided diagnosis and data mining.
Emilia Balas, Valentina
Valentina E. Balas holds a Ph.D. in Applied Electronics and Telecommunications from Polytechnic University of Timisoara. Dr. Balas is author of more than 250 research papers in refereed journals and International Conferences. Her research interests are in Intelligent Systems, Fuzzy Control, Soft Computing, Smart Sensors, Information Fusion, Modeling and Simulation. She is the Editor-in-Chief to International Journal of Advanced Intelligence Paradigms (IJAIP) and to International Journal of Computational Systems Engineering (IJCSysE), Editorial Board member of several national and international journals and is evaluator expert for national and international projects. Dr. Balas is the director of Intelligent Systems Research Centre in Aurel Vlaicu University of Arad and was Vice-president (Awards) of IFSA International Fuzzy Systems Association Council (2013-2015) and is a Joint Secretary of the Governing Council of Forum for Interdisciplinary Mathematics (FIM), - A Multidisciplinary Academic Body, India.
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