This book proposes novel context-inferring algorithms and generic framework designs that can help readers enhance existing tradeoffs in mobile sensing, especially between accuracy and power consumption. It provides numerous application examples that guide readers from fundamental concepts to the implementation of context-aware-related algorithms and frameworks. Covering theory and practical strategies for context awareness in mobile sensing, the book promotes the development of modeling and analysis skills for context awareness on resource-constrained mobile platforms.
This book proposes novel context-inferring algorithms and generic framework designs that can help readers enhance existing tradeoffs in mobile sensing, especially between accuracy and power consumption. It provides numerous application examples that guide readers from fundamental concepts to the implementation of context-aware-related algorithms and frameworks. Covering theory and practical strategies for context awareness in mobile sensing, the book promotes the development of modeling and analysis skills for context awareness on resource-constrained mobile platforms.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Ozgur Yurur received a double major from the Department of Electronics Engineering and the Department of Computer Engineering at Gebze Institute of Technology, Kocaeli, Turkey, in 2008, and MSEE and PhD from the Department of Electrical Engineering at the University of South Florida (USF), Tampa, Florida, in 2010 and 2013, respectively. He is currently with RF Micro Devices, responsible for the research and design of new test development strategies and also for the implementation of hardware, software, and firmware solutions for 2G, 3G, 4G, and wireless-based company products. In addition, Dr. Yurur conducts research in the field of mobile sensing. His research area covers ubiquitous sensing, mobile computing, machine learning, and energy-efficient optimal sensing policies in wireless networks. The main focus of his research is on developing and implementing accurate, energy-efficient, predictive, robust, and optimal context-aware algorithms and framework designs on sensor-enabled mobile devices. Chi Harold Liu is a full professor at the School of Software, Beijing Institute of Technology, China. He is also the deputy director of IBM Mainframe Excellence Center (Beijing), director of IBM Big Data Technology Center, and director of National Laboratory of Data Intelligence for China Light Industry. He holds a PhD from Imperial College, United Kingdom, and a BEng from Tsinghua University, China. Before moving to academia, he joined IBM Research, China, as a staff researcher and project manager and was previously a postdoctoral researcher at Deutsche Telekom Laboratories, Germany, and a visiting scholar at IBM T. J. Watson Research Center, Armonk, New York. Dr. Liu's current research interests include the Internet of Things (IoT), big data analytics, mobile computing, and wireless ad hoc, sensor, and mesh networks. He received the IBM First Plateau Invention Achievement Award in 2012 and an IBM First Patent Application Award in 2011. He was interviewed by EEWeb.com as the featured engineer in 2011. Dr. Liu has published more than 50 prestigious conference and journal papers and owns more than 10 EU, U.S., and China patents. He serves as the editor for KSII Transactions on Internet and Information Systems and was book author or editor of three books published by CRC Press. He has served as the general chair of the IEEE SECON'13 workshop on IoT Networking and Control, the IEEEWCNC'12 workshop on IoT Enabling Technologies, and the ACM UbiComp'11Workshop on Networking and Object Memories for IoT. He has also served as a consultant for Bain & Company and KPMG, United States; and as a peer reviewer for Qatar National Research Foundation and the National Science Foundation in China. He is a member of the IEEE and the ACM.
Inhaltsangabe
Context Awareness for Mobile Sensing. Context Inference: Posture Detection. Context-Aware Framework: A Basic Design. Energy Efficiency in Physical Hardware. Context-Aware Framework: A Complex Design. Probabilistic Context Modeling.
Context Awareness for Mobile Sensing. Context Inference: Posture Detection. Context-Aware Framework: A Basic Design. Energy Efficiency in Physical Hardware. Context-Aware Framework: A Complex Design. Probabilistic Context Modeling.
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