HR: 0800h
AN: IN21B-1174    [Abstracts]
TI: A Wireless Sensor Network For Soil Monitoring
AU: * Szlavecz, K
EM: szlavecz@jhu.edu
AF: Johns Hopkins University, Dept. of Earth and Planetary Sciences, Baltimore, MD 21218
AU: Cogan, J
EM: joshtron@gmail.com
AF: Johns Hopkins University, Dept. of Earth and Planetary Sciences, Baltimore, MD 21218
AU: Musaloiu-Elefteri, R
EM: razvanm@jhu.edu
AF: Johns Hopkins University, Dept. of Computer Sciences, Baltimore, MD 21218
AU: Small, S
EM: sam@cs.jhu.edu
AF: Johns Hopkins University, Dept. of Computer Sciences, Baltimore, MD 21218
AU: Terzis, A
EM: terzis@jhu.edu
AF: Johns Hopkins University, Dept. of Computer Sciences, Baltimore, MD 21218
AU: Szalay, A
EM: szalay@jhu.edu
AF: Johns Hopkins University, Dept. of Physics and Astronomy, Baltimore, MD 21218
AB: The most spatially complex stratum of a terrestrial ecosystem is its soil. Among the major challenges of studying the soil ecosystem are the diversity and the cryptic nature of biota, and the enormous heterogeneity of the soil substrate. Often this patchiness drives spatial distribution of soil organisms, yet our knowledge on the spatio-temporal patterns of soil conditions is limited. To monitor the environmental conditions at biologically meaningful spatial scales we have developed and deployed a wireless sensor network of thirty nodes. Each node is based on a MICAz mote connected to a custom-built sensor suite that includes a Watermark soil moisture sensor, an Irrometer soil temperature sensor, and sensors capable of recording ambient temperature and light intensity. To assess CO2 production at the ground level a subset of the nodes is equipped with Telaire 6004 CO2 sensor. We developed the software running on the motes from scratch, using the TinyOS development environment. Each mote collects measurements every minute, and stores them persistently in a non-volatile memory. The decision to store data locally at each node enables us to reliably retrieve the data in the face of network losses and premature node failures due to power depletion. Collected measurements are retrieved over the wireless network through a PC-class computer acting as a gateway between the sensor network and the Internet. Considering that motes are battery powered, the largest obstacle hindering long-term sensor network deployments is power consumption. To address this problem, our software powers down sensors between sampling cycles and turns off the radio (the most energy prohibitive mote component) when not in use. By doing so we were able to increase node lifetime by a factor of ten. We collected field data over several weeks. The data was ingested into a SQL Server database, which provides data access through a .NET web services interface. The database provides functions for spatial and a temporal interpolation of the data. This system enables us to continuously monitor environmental factors and ecosystem responses at very fine scales (cm to m) and to correlate both sets of data in time and space such that cause and effect relationships can be established. Such rich dataset will greatly contribute to our understanding of soil organism dynamics and more importantly the role these organisms play in important ecosystem processes. Soil moisture data on
DE: 0486 Soils/pedology (1865)
DE: 1865 Soils (0486)
SC: Earth and Space Science Informatics [IN]
MN: Fall Meeting 2005