Measurement scheduling for soil moisture sensing: From physical models to optimal control
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Entekhabi_Measurement Scheduling.pdf
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818.88 KB
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Author(s)
Shuman, David I.
Nayyar, Ashutosh
Mahajan, Aditya
Goykhman, Yuriy
Li, Ke
Liu, Mingyan
Teneketzis, Demosthenis
Moghaddam, Mahta
Entekhabi, Dara
Date Issued
November 2010
Journal
Proceedings of the IEEE
Publisher
Institute of Electrical and Electronics Engineers
Citation
Shuman, D.I. et al. “Measurement Scheduling for Soil Moisture Sensing: From Physical Models to Optimal Control.” Proceedings of the IEEE 98.11 (2010): 1918-1933. Copyright © 2010, IEEE
Version
Final published version
Abstract
In this paper, we consider the problem of monitoring soil moisture evolution using a wireless network of in situ sensors. Continuously sampling moisture levels with these sensors incurs high-maintenance and energy consumption costs, which are particularly undesirable for wireless networks. Our main hypothesis is that a sparser set of measurements can meet the monitoring objectives in an energy-efficient manner. The underlying idea is that we can trade off some inaccuracy in estimating soil moisture evolution for a significant reduction in energy consumption. We investigate how to dynamically schedule the sensor measurements so as to balance this tradeoff. Unlike many prior studies on sensor scheduling that make generic assumptions on the statistics of the observed phenomenon, we obtain statistics of soil moisture evolution from a physical model. We formulate the optimal measurement scheduling and estimation problem as a partially observable Markov decision problem (POMDP). We then utilize special features of the problem to approximate the POMDP by a computationally simpler finite-state Markov decision problem (MDP). The result is a scalable, implementable technology that we have tested and validated numerically and in the field.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/JPROC.2010.2052532
