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Learning from data streams : Processing techniques in sensor networks
The book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education.
Body Sensor Networks
While the problems of long-term stability and biocompatibility are being addressed, several promising prototypes are starting to emerge for managing patients with acute diabetes, for treatment of epilepsy and other debilitating neurological disorders and for monitoring of patients with chronic cardiac diseases. Despite the technological developments in sensing and monitoring devices, issues related to system integration, sensor miniaturization, low-power sensor interface circuitry design, wireless telemetric links and signal processing still have to be investigated.
Anomaly Detection : Techniques and Applications
When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identification of the rare items, events, observations, patterns which raise suspension by differing significantly from the majority of data is called anomaly detection. With progress in the technologies and the widespread use of data for the purpose for business the increase in the spams faced by the individuals and the companies are increasing day by day. This noisy data has boomed as a major problem in various areas such as Internet of Things, web service, Machine Learning, Artificial Intelligence, Deep learning, Image Processing, Cloud Computing, Audio processing, Video Processing, VoIP, Data Science, Wireless Sensor etc. Identifying the anomaly data and filtering them before processing is a major challenge for the data analyst. This anomaly is unavoidable in all areas of research. This book covers the techniques and algorithms for detecting the deviated data.
AmIware : Hardware Technology Drivers of Ambient Intelligence
Ambient Intelligence is one of the new paradigms in the development of information and communication technology, which has attracted much attention over the past years. The aim is the to integrate technology into people environment in such a way that it improves their daily lives in terms of well-being, creativity, and productivity. Ambient Intelligence is a multidisciplinary concept, which heavily builds on a number of fundamental breakthroughs that have been achieved in the development of new hardware concepts over the past years. New insights in nano and micro electronics, packaging and interconnection technology, large-area electronics, energy scavenging devices, wireless sensors, low power electronics and computing platforms enable the realization of the heaven of ambient intelligence by overcoming the hell of physics.
Advances in Ad Hoc and Sensor Networks
This volume provides a complete survey of the state-of-the-art research that encompasses all areas of ad hoc and sensor networks. These chapters focus on the theoretical and experimental study of advanced research topics involving security and trust, broadcasting and multicasting, power control and energy efficiency, and QoS provisioning.
Advances in Unmanned Aerial Vehicles : State of the Art and the Road to Autonomy
There has been tremendous emphasis in unmanned aerial vehicles, both of fixed (airplanes) and rotary wing (vertical take off and landing, helicopters) types over the past ten years. Applications span both civilian and military domains, the latter being the most important at this stage. This edited book provides a solid and diversified reference source related to basic, applied research and development on small and miniature unmanned aerial vehicles, both fixed and rotary wing. As such, the book offers background information on the evolution of such vehicles over the years, followed by modeling and control fundamentals that are of paramount importance due to unmanned aerial vehicle model complexity, nonlinearity, coupling, inhirent instability and parameter values uncertainty. Aspects of navigation, including visual-based navigation and target tracking are discussed, followed by applications to attitude estimation on micro unmanned aerial vehicles, autonomous solar unmanned aerial vehicle, biomimetic sensing for autonomous flights in near-earth environments, localization of air-ground wireless sensor networks, decentralized formation tracking, design of an unmanned aerial vehicle for volcanic gas sampling and design of an on-board processing controller for miniature helicopters.
