Elaborating on the concept of context awareness, this book presents up-to-date research and novel framework designs for context-aware mobile sensing. Generic and Energy-Efficient Context-Aware Mobile Sensing 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. The book presents solutions that emphasize must-have system characteristics such as energy efficiency, accuracy, robustness, adaptability, time-invariance, and optimal sensor sensing. Numerous application examples 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 will help readers develop the modeling and analysis skills required to build futuristic context-aware framework designs for resource-constrained platforms. Includes best practices for designing and implementing practical context-aware frameworks in ubiquitous/mobile sensing Proposes a lightweight online classification method to detect user-centric postural actions Examines mobile device-based battery modeling under the scope of battery nonlinearities with respect to variant loads Unveils a novel discrete time inhomogeneous hidden semi-Markov model (DT-IHS-MM)-based generic framework to achieve a better realization of HAR-based mobile context awareness Supplying theory and equation derivations for all the concepts discussed, the book includes design tips for the implementation of smartphone programming as well as pointers on how to make the best use of MATLAB® for the presentation of performance analysis. Coverage includes lightweight, online, and unsupervised pattern recognition methods; adaptive, time-variant, and optimal sensory sampling strategies; and energy-efficient, robust, and inhomogeneous context-aware framework designs. Researchers will learn the latest modeling and analysis research on mobile sensing. Students will gain access to accessible reference material on mobile sensing theory and practice. Engineers will gain authoritative insights into cutting-edge system designs.

The arrival of the digital age has created the need to be able to store, manage, and digitally use an ever-increasing amount of video and audio material. Thus, video cataloguing has emerged as a requirement of the times. Video Cataloguing: Structure Parsing and Content Extraction explains how to efficiently perform video structure analysis as well as extract the basic semantic contents for video summarization, which is essential for handling large-scale video data. This book addresses the issues of video cataloguing, including video structure parsing and basic semantic word extraction, particularly for movie and teleplay videos. It starts by providing readers with a fundamental understanding of video structure parsing. It examines video shot boundary detection, recent research on video scene detection, and basic ideas for semantic word extraction, including video text recognition, scene recognition, and character identification. The book lists and introduces some of the most commonly used features in video analysis. It introduces and analyzes the most popular shot boundary detection methods and also presents recent research on movie scene detection as another important and critical step for video cataloguing, video indexing, and retrieval. The authors propose a robust movie scene recognition approach based on a panoramic frame and representative feature patch. They describe how to recognize characters in movies and TV series accurately and efficiently as well as how to use these character names as cataloguing items for an intelligent catalogue. The book proposes an interesting application of highlight extraction in basketball videos and concludes by demonstrating how to design and implement a prototype system of automatic movie and teleplay cataloguing (AMTC) based on the approaches introduced in the book.

The arrival of the digital age has created the need to be able to store, manage, and digitally use an ever-increasing amount of video and audio material. Thus, video cataloguing has emerged as a requirement of the times. Video Cataloguing: Structure Parsing and Content Extraction explains how to efficiently perform video structure analysis as well as extract the basic semantic contents for video summarization, which is essential for handling large-scale video data. This book addresses the issues of video cataloguing, including video structure parsing and basic semantic word extraction, particularly for movie and teleplay videos. It starts by providing readers with a fundamental understanding of video structure parsing. It examines video shot boundary detection, recent research on video scene detection, and basic ideas for semantic word extraction, including video text recognition, scene recognition, and character identification. The book lists and introduces some of the most commonly used features in video analysis. It introduces and analyzes the most popular shot boundary detection methods and also presents recent research on movie scene detection as another important and critical step for video cataloguing, video indexing, and retrieval. The authors propose a robust movie scene recognition approach based on a panoramic frame and representative feature patch. They describe how to recognize characters in movies and TV series accurately and efficiently as well as how to use these character names as cataloguing items for an intelligent catalogue. The book proposes an interesting application of highlight extraction in basketball videos and concludes by demonstrating how to design and implement a prototype system of automatic movie and teleplay cataloguing (AMTC) based on the approaches introduced in the book.

Compared with conventional communications, cooperative communication allows multiple users in a wireless network to coordinate their packet transmissions and share each other's resources, thus achieving high-performance gain and better service coverage and reliability. Energy Efficient Cooperative Wireless Communication and Networks provides a comprehensive look at energy efficiency and system design of cooperative wireless communication. Introducing effective cooperative wireless communication schemes, the book supplies the understanding and methods required to improve energy efficiency, reliability, and end-to-end protocol designs for wireless communication systems. It explains the practical benefits and limitations of cooperative transmissions along with the associated designs of upper-layer protocols, including MAC, routing, and transport protocol. The book considers power efficiency as a main objective in cooperative communication to ensure quality-of-service (QoS) requirements. It explains how to bring the performance gain at the physical layer up to the network layer and how to allocate network resources dynamically through MAC/scheduling and routing to trade off the performance benefits of given transmissions against network costs. Because the techniques detailed in each chapter can help readers achieve energy efficiency and reliability in wireless networks, they have the potential to impact a range of industry areas, including wireless communication, wireless sensor networks, and ad hoc networks. The book includes numerous examples, best practices, and models that capture key issues in real-world applications. Along with algorithms and tips for effective design, the book supplies the understanding you will need to achieve high-performing and energy efficient wireless networks with improved service coverage and reliability.

Cyber Physical Systems: Architectures, Protocols and Applications helps you understand the basic principles and key supporting standards of CPS. It analyzes different CPS applications from the bottom up, extracting the common characters that form a vertical structure. It presents mobile sensing platforms and their applications toward interrelated paradigms, highlighting and briefly discussing different types of mobile sensing platforms and the functionalities they offer. It then looks at the naming, addressing, and profile services of CPS and proposes a middleware component to meet the requirements of dynamic applications and sensors/actuators deployment/configurations across different platforms. The middle chapters of the book present a context-aware sensor search, selection, and ranking model which addresses the challenge of efficiently selecting a subset of relevant sensors out of a large set of sensors with similar functionality and capabilities. The authors consider various topics in the energy management of CPS and propose a novel energy-efficient framework. They also present the fundamental networking technologies of CPS and focus on machine-to-machine communications for CPS, specifically the open technologies such as IPv6-based solutions that can be integrated into IoT and enable wireless sensor communications. In the book's final chapters, the authors bring you up to date on mobile cloud computing (MCC) research activities that enhance the capabilities of resource-constrained smart devices in CPS sensory environments. They also present a few representative CPS applications, including connected healthcare, gaming in public transport crowds, and a series of MCC-enabled emerging CPS applications. You will find that these application fields fully demonstrate the great potential of applying CPS in public life.

Elaborating on the concept of context awareness, this book presents up-to-date research and novel framework designs for context-aware mobile sensing. Generic and Energy-Efficient Context-Aware Mobile Sensing 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. The book presents solutions that emphasize must-have system characteristics such as energy efficiency, accuracy, robustness, adaptability, time-invariance, and optimal sensor sensing. Numerous application examples 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 will help readers develop the modeling and analysis skills required to build futuristic context-aware framework designs for resource-constrained platforms. Includes best practices for designing and implementing practical context-aware frameworks in ubiquitous/mobile sensing Proposes a lightweight online classification method to detect user-centric postural actions Examines mobile device-based battery modeling under the scope of battery nonlinearities with respect to variant loads Unveils a novel discrete time inhomogeneous hidden semi-Markov model (DT-IHS-MM)-based generic framework to achieve a better realization of HAR-based mobile context awareness Supplying theory and equation derivations for all the concepts discussed, the book includes design tips for the implementation of smartphone programming as well as pointers on how to make the best use of MATLAB (R) for the presentation of performance analysis. Coverage includes lightweight, online, and unsupervised pattern recognition methods; adaptive, time-variant, and optimal sensory sampling strategies; and energy-efficient, robust, and inhomogeneous context-aware framework designs. Researchers will learn the latest modeling and analysis research on mobile sensing. Students will gain access to accessible reference material on mobile sensing theory and practice. Engineers will gain authoritative insights into cutting-edge system designs.