Mission Oriented Sensor Networks And Systems Art And Science
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Mission-Oriented Sensor Networks and Systems: Art and Science
This book discusses topics in mission-oriented sensor networks and systems research and practice, enabling readers to understand the major technical and application challenges of these networks, with respect to their architectures, protocols, algorithms, and application design. It also presents novel theoretical and practical ideas, which have led to the development of solid foundations for the design, analysis, and implementation of energy-efficient, reliable, and secure mission-oriented sensor network applications. Covering various topics, including sensor node architecture, sensor deployment, mobile coverage, mission assignment, detection, localization, tracking, data dissemination, data fusion, topology control, geometric routing, location privacy, secure communication, and cryptograph, it is a valuable resource for computer scientists, researchers, and practitioners in academia and industry.
Mission-Oriented Sensor Networks and Systems: Art and Science
This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.
Theory and Practice of Wireless Sensor Networks: Cover, Sense, and Inform
This book aims at developing a reader’s thorough understanding of the challenges and opportunities of two categories of networks, namely k-covered wireless sensor networks and k-barrier covered wireless sensor networks. It presents a variety of theoretical studies based on percolation theory, convexity theory, and applied computational geometry, as well as the algorithms and protocols that are essential to their design, analysis, and development. Particularly, this book focuses on the cover, sense, and inform (CSI) paradigm with a goal to build a unified framework, where connected k-coverage (or k-barrier coverage), sensor scheduling, and geographic data forwarding, gathering, and delivery are jointly considered. It provides the interested reader with a fine study of the above networks, which can be covered in introductory and advanced courses on wireless sensor networks. This book is useful to senior undergraduate and graduate students in computer science, computer engineering, electrical engineering, information science, information technology, mathematics, and any related discipline. Also, it is of interest to computer scientists, researchers, and practitioners in academia and industry with interest in these two networks from their deployment until data gathering and delivery.