Big Data Analytics for Sensor-Network Collected Intelligence

Häftad, Engelska, 2017

Del i serien Intelligent Data-Centric Systems

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Beskrivning

Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services.

It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality.

In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation.

Indexing: The books of this series are submitted to EI-Compendex and SCOPUS

Contains contributions from noted scholars in computer science and electrical engineering from around the globe
Provides a broad overview of recent developments in sensor collected intelligence
Edited by a team comprised of leading thinkers in big data analytics

Produktinformation

Utgivningsdatum:2017-02-08
Mått:191 x 235 x 20 mm
Vikt:630 g
Format:Häftad
Språk:Engelska
Serie:Intelligent Data-Centric Systems
Antal sidor:326
Förlag:Elsevier Science
ISBN:9780128093931

Utforska kategorier

Databaser inom Data och IT
Artificiell intelligens inom Data och IT

Mer om författaren

Hui-Huang Hsu is a Professor in the Department of Computer Science and Information Engineering at Tamkang University in Taiwan. He also serves as the Dean of College of Engineering since August 2016. Previously, he was the Chairman of the Department. Prof. Hsu received both his Ph.D. and M.S. Degrees from the Department of Electrical and Computer Engineering at the University of Florida, USA. He got his B.E. degree in Electrical Engineering from Tamkang University. He has worked in the areas of machine learning, data mining, ambient intelligence, bio-medical informatics, and multimedia processing. Prof. Hsu is a senior member of the IEEE. He is also an Executive Board Member of Taiwanese Association for Artificial Intelligence (TAAI). Chuan-Yu Chang is Distinguished Professor and Dean of Research and Development at National Yunlin University of Science and Technology, Taiwan. He has more than 150 publications in journals and conference proceedings, and his research interests include machine learning, medical image processing, wafer defect inspection, digital watermarking, and pattern recognition. Ching-Hsien Hsu is a Professor in Department of Computer Science and Information Engineering at Chung Hua University, Taiwan. His research includes cloud computing, big data analytics, parallel and distributed systems, high performance computing, ubiquitous/pervasive computing and intelligence. Dr. Hsu is the Editor-in-Chief of International Journal of Grid and High Performance Computing and International Journal of Big Data Intelligence and serves as on the editorial board of a number of other journals. He has published 250 papers in refereed journals and conference proceedings and served as an author or editor of 10 books.

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Innehållsförteckning

Part I: Big Data Architecture and Platforms1. Big Data: A Classification of Acquisition and Generation Methods2. Cloud Computing Infrastructure for Data Intensive Applications3. Open Source Private Cloud Platforms for Big DataPart II: Big Data Processing and Management4. Efficient Nonlinear Regression-Based Compression of Big Sensing Data on Cloud5. Big Data Management on Wireless Sensor Networks6. Extreme Learning Machine and Its Applications in Big Data ProcessingPart III: Big Data Analytics and Services7. Spatial Big Data Analytics for Cellular Communication Systems8. Cognitive Applications and Their Supporting Architecture for Smart Cities9. Deep Learning for Human Activity Recognition10. Neonatal Cry Analysis and Categorization System Via Directed Acyclic Graph Support Vector MachinePart IV: Big Data Intelligence and IoT Systems11. Smart Building Applications and Information System Hardware Co-Design12. Smart Sensor Networks for Building Safety13. The Internet of Things and Its Applications14. Smart Railway Based on the Internet of Things