Big Data Analytics for Sensor-Network Collected Intelligence

ISBN-13: 9780128093931 / Angielski / Miękka / 2017 / 326 str.

Hui-Huang Hsu; Chuan-Yu Chang; Ching-Hsien Hsu

Opis

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

Spis treści

Part I: Big Data Architecture and Platforms 1. Big Data: A Classification of Acquisition and Generation Methods 2. Cloud Computing Infrastructure for Data Intensive Applications 3. Open Source Private Cloud Platforms for Big Data

Part II: Big Data Processing and Management 4. Efficient Nonlinear Regression-Based Compression of Big Sensing Data on Cloud 5. Big Data Management on Wireless Sensor Networks 6. Extreme Learning Machine and Its Applications in Big Data Processing

Part III: Big Data Analytics and Services 7. Spatial Big Data Analytics for Cellular Communication Systems 8. Cognitive Applications and Their Supporting Architecture for Smart Cities 9. Deep Learning for Human Activity Recognition 10. Neonatal Cry Analysis and Categorization System Via Directed Acyclic Graph Support Vector Machine

Part IV: Big Data Intelligence and IoT Systems 11. Smart Building Applications and Information System Hardware Co-Design 12. Smart Sensor Networks for Building Safety 13. The Internet of Things and Its Applications 14. Smart Railway Based on the Internet of Things