Probabilistic Framework For Sensor Management
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Probabilistic Framework for Sensor Management
A probabilistic sensor management framework is introduced, which maximizes the utility of sensor systems with many different sensing modalities by dynamically configuring the sensor system in the most beneficial way. For this purpose, techniques from stochastic control and Bayesian estimation are combined such that long-term effects of possible sensor configurations and stochastic uncertainties resulting from noisy measurements can be incorporated into the sensor management decisions.
Aviation and Human Factors
Air safety is right now at a point where the chances of being killed in an aviation accident are far lower than the chances to winning a jackpot in any of the major lotteries. However, keeping or improving that performance level requires a critical analysis of some events that, despite scarce, point to structural failures in the learning process. The effect of these failures could increase soon if there is not a clear and right development path. This book tries to identify what is wrong, why there are things to fix, and some human factors principles to keep in aircraft design and operations. Features Shows, through different events, how the system learns through technology, practices, and regulations and the pitfalls of that learning process Discusses the use of information technology in safety-critical environments and why procedural knowledge is not enough Presents air safety management as a successful process, but at the same time, failures coming from technological and organizational features are shown Offers ways to improve from the human factors side by getting the right lessons from recent events
Distributed Sensor Networks
The best-selling Distributed Sensor Networks became the definitive guide to understanding this far-reaching technology. Preserving the excellence and accessibility of its predecessor, Distributed Sensor Networks, Second Edition once again provides all the fundamentals and applications in one complete, self-contained source. Ideal as a tutorial for students or as research material for engineers, the book gives readers up-to-date, practical insight on all aspects of the field.This two volume set, this second edition has been revised and expanded with over 500 additional pages and more than 300 new illustrations. This edition incorporates contributions from many veterans of the DARPA ISO SENSIT program as well as new material from distinguished researchers in the field. It offers 13 fully revised chapters and 22 new chapters, covering new perspectives on information fusion, the latest technical developments, and current sensor network applications. Volume 1 Image and Sensor Signal Processing includes: Distributed Sensing and Signal Processing; Information Fusion; and Power Management. Volume 2 Sensor Networking and Applications includes: Sensor Deployment; Adaptive Tasking; Self-Configuration; System Control; and Engineering Examples.