Adaptive Sampling with Mobile WSN develops algorithms for optimal estimation of environmental parametric fields. With a single mobile sensor, several approaches are presented to solve the problem of where to sample next to maximally and simultaneously reduce uncertainty in the field estimate and uncertainty in the localisation of the mobile sensor while respecting the dynamics of the time-varying field and the mobile sensor. A case study of mapping a forest fire is presented. Multiple static and mobile sensors are ...
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Adaptive Sampling with Mobile WSN develops algorithms for optimal estimation of environmental parametric fields. With a single mobile sensor, several approaches are presented to solve the problem of where to sample next to maximally and simultaneously reduce uncertainty in the field estimate and uncertainty in the localisation of the mobile sensor while respecting the dynamics of the time-varying field and the mobile sensor. A case study of mapping a forest fire is presented. Multiple static and mobile sensors are considered next, and distributed algorithms for adaptive sampling are developed resulting in the Distributed Federated Kalman Filter. However, with multiple resources a possibility of deadlock arises and a matrix-based discrete-event controller is used to implement a deadlock avoidance policy. Deadlock prevention in the presence of shared and routing resources is also considered. Finally, a simultaneous and adaptive localisation strategy is developed to simultaneously localise static and mobile sensors in the WSN in an adaptive manner. Experimental validation of several of these algorithms is discussed throughout the book.
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Add this copy of Adaptive Sampling With Mobile Wsn: Simultaneous Robot to cart. £101.07, very good condition, Sold by Michael Knight, Bookseller rated 4.0 out of 5 stars, ships from Forest Grove, OR, UNITED STATES, published 2011 by The Institution of Engineering a.
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Publisher:
Institution of Engineering and Technology
Published:
2011
Language:
English
Alibris ID:
18566783174
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Fine. 208 p. Control, Robotics and Sensors . Intended for college/higher education audience. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Adaptive Sampling with Mobile WSN: Simultaneous robot to cart. £123.87, new condition, Sold by GreatBookPricesUK5 rated 4.0 out of 5 stars, ships from Castle Donington, DERBYSHIRE, UNITED KINGDOM, published 2011 by Institution of Engineering and Technology.
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Institution of Engineering and Technology
Published:
2011
Language:
English
Alibris ID:
18566616452
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New. 208 p. Control, Robotics and Sensors . Intended for college/higher education audience. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Adaptive Sampling with Mobile WSN: Simultaneous robot to cart. £125.06, like new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2011 by Institution of Engineering and Technology.
Publisher:
Institution of Engineering and Technology
Published:
2011
Language:
English
Alibris ID:
18565952487
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Fine. 208 p. Control, Robotics and Sensors . Intended for college/higher education audience. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
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