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Neural Net Water Level Trend Prediction and Dynamic Water Level Sampling Frequency

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7 Author(s)
Steven P. Sweeney ; Dept. of Math. & Comput. Sci., Univ. of Maryland Eastern Shore, Princess Anne, MD ; Sehwan Yoo ; Albert Chi ; Frank Lin
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We have used neural network water level trend prediction (NNWLTP) in support of a water level sensing project. The NNWLTP approach allows dynamic change in water level sampling frequency, which will reduce power consumption and extend battery life in energy constrained devices. This paper deals primarily with the NNWLTP, which would allow sampling frequency change commands to be transmitted to the sensors when a transition or turning point was detected.

Published in:

Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2008. SNPD '08. Ninth ACIS International Conference on

Date of Conference:

6-8 Aug. 2008