In-Situ Soil Moisture Sensing: From Physical Models to Optimal Control to Field Deployment
In this talk we describe the monitoring of soil moisture evolution using a wireless network of in-situ sensors. Soil moisture measurement has many applications in hydrology and is one of the most important indicators in agricultural drought monitoring. Traditionally soil moisture data have been collected solely through remote sensing, i.e., from satellite radars and radiometers. These measurements allow global mapping but have large footprints. In-situ soil moisture sensors can capture variability at much finer spatial and temporal scales but a large deployment is costly and impractical. The objective of this study is to improve the scalability of in-situ soil moisture sensing through optimal measurement scheduling and judicial sensor placement so as to allow sparse measurements (both spatially and temporally) to meet monitoring needs, which include using in-situ measurements to validate remote sensing.
Specifically, in this talk we will describe the conceptualization of the optimal measurement scheduling framework; this is formulated as a partially observable Markov decision problem (POMDP) by using statistics of soil moisture evolution from a physical model. We then utilize special features of the problem to approximate the POMDP by a computationally simpler finite-state Markov decision problem (MDP). We will also describe our instrumentation and system integration effort and a recent field deployment of this wireless monitoring system on a cattle farm in Canton, Oklahoma, along with experience and lessons learned in building practical unattended wireless sensor networks.
This is joint work with Profs. M. Moghaddam, D. Teneketzis, D. Entekhabi, and our team of students.
Mingyan Liu joined the Electrical Engineering and Computer Science Department at the University of Michigan in September 2000, after receiving a Ph.D degree in electrical engineering from the University of Maryland, College Park, where she is now an associate professor. Her research interests are in optimal resource allocation, performance modeling and analysis, and energy efficient design of wireless, mobile ad hoc, and sensor networks. She is the recipient of the 2002 NSF CAREER Award, the University of Michigan Elizabeth C. Crosby Research Award in 2003, and the 2010 EECS Department Outstanding Achievement Award. She serves on the editorial boards of IEEE/ACM Trans. on Networking, IEEE Trans. on Mobile Computing, and ACM Trans. on Sensor Networks.