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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 co… Read more
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Immediately download your ebook while waiting for your print delivery. No promo code needed.
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
Big Data and Networking researchers, practitioners, and upper level and graduate students
Part I: Big Data Architecture and Platforms
Chapter 1: Big Data: A Classification of Acquisition and Generation Methods
Chapter 2: Cloud Computing Infrastructure for Data Intensive Applications
Chapter 3: Open Source Private Cloud Platforms for Big Data
Part II: Big Data Processing and Management
Chapter 4: Efficient Nonlinear Regression-Based Compression of Big Sensing Data on Cloud
Chapter 5: Big Data Management on Wireless Sensor Networks
Chapter 6: Extreme Learning Machine and Its Applications in Big Data Processing
Part III: Big Data Analytics and Services
Chapter 7: Spatial Big Data Analytics for Cellular Communication Systems
Chapter 8: Cognitive Applications and Their Supporting Architecture for Smart Cities
Chapter 9: Deep Learning for Human Activity Recognition
Chapter 10: Neonatal Cry Analysis and Categorization System Via Directed Acyclic Graph Support Vector Machine
Part IV: Big Data Intelligence and IoT Systems
Chapter 11: Smart Building Applications and Information System Hardware Co-Design
Chapter 12: Smart Sensor Networks for Building Safety
Chapter 13: The Internet of Things and Its Applications
Chapter 14: Smart Railway Based on the Internet of Things
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