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    Real-Time Data Analytics for Large Scale Sensor Data

    AvHimansu Das,Nilanjan Dey

    Häftad, Engelska, 2019

    Del i serien Advances in ubiquitous sensing applications for healthcare

    1 714 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    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

    Produktinformation

    • Utgivningsdatum:2019-09-03
    • Mått:191 x 235 x 16 mm
    • Vikt:610 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:Advances in ubiquitous sensing applications for healthcare
    • Antal sidor:298
    • Förlag:Elsevier Science
    • ISBN:9780128180143

    Utforska kategorier

    • Referensverk och tvärvetenskap inom Samhälle och politik
    • Biokemisk teknik inom Naturvetenskap och teknik
    • Biomedicinsk teknik inom Medicin

    Mer om författaren

    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. Nilanjan Dey (Senior Member, IEEE) received the B.Tech., M.Tech. in information technology from West Bengal Board of Technical University and Ph.D. degrees in electronics and telecommunication engineering from Jadavpur University, Kolkata, India, in 2005, 2011, and 2015, respectively. Currently, he is Associate Professor with the Techno International New Town, Kolkata and a visiting fellow of the University of Reading, UK. He has authored over 300 research articles in peer-reviewed journals and international conferences and 40 authored books. His research interests include medical imaging and machine learning. Moreover, he actively participates in program and organizing committees for prestigious international conferences, including World Conference on Smart Trends in Systems Security and Sustainability (WorldS4), International Congress on Information and Communication Technology (ICICT), International Conference on Information and Communications Technology for Sustainable Development (ICT4SD) etc.He is also the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, Associate Editor of IEEE Transactions on Technology and Society and series Co-Editor of Springer Tracts in Nature-Inspired Computing and Data-Intensive Research from Springer Nature and Advances in Ubiquitous Sensing Applications for Healthcare from Elsevier etc. Furthermore, he was an Editorial Board Member Complex & Intelligence Systems, Springer, Applied Soft Computing, Elsevier and he is an International Journal of Information Technology, Springer, International Journal of Information and Decision Sciences etc. He is a Fellow of IETE and member of IE, ISOC etc.Dr. Valentina Emilia Balas is Full Professor in the Department of Automatics and Applied Software, Faculty of Engineering, Aurel Vlaicu University of Arad, Romania. She holds a PhD in Applied Electronics and Telecommunications from the Polytechnic University of Timisoara. Her research interests include intelligent systems, fuzzy systems, soft computing, smart sensors, information fusion, modeling, and simulation.Dr. Balas serves as Director of the Intelligent Systems Research Center and Director of International Relations, Programs and Projects at Aurel Vlaicu University of Arad. She is Editor-in-Chief of the International Journal of Advanced Intelligence Paradigms and International Journal of Computational Systems Engineering, and serves on the editorial boards of several scientific journals. She has led and contributed to numerous national and international research initiatives, including the European Union-funded BioCell-NanoART project on bio-inspired cellular nano-architectures. She is active in several professional societies and technical committees, including IEEE, the European Society for Fuzzy Logic and Technology, and the Society for Industrial and Applied Mathematics.

    Innehållsförteckning

    • 1. Internet of Things in healthcare: Smart devices, sensors, and systems related to diseases and health conditions2. Real-time data analytics in healthcare using the Internet of Things3. Lightweight code self-verification using return-oriented programming in resilient IoT4. Monte-Carlo Simulation models for reliability analysis of low-cost IoT communication networks in smart grid5. Lightweight ciphertext-policy attribute-based encryption scheme for data privacy and security in cloud-assisted IoT6. Soft sensor with shape descriptors for flame quality prediction based on LSTM regression7. Communication-aware edge-centric knowledge dissemination in edge computing environments8. An effective blockchain-based, decentralized application for smart building system management9. Privacy and security of Internet of Things devices10. Software-Defined Networking for the Internet of Things: Securing home networks using SDN