OVERVIEW

The ultimate goal of embedded networked sensing (ENS) technology research is to create a new way for applications domain scientists and engineers to observe systems by creating the cyberinfrastructure enabling the network of specific environmental sensors to self-configure as a sophisticated, interactive virtual sensor (the network is the sensor). Science and engineering researchers working in earth, environmental and ecological systems understand that the key to answering many of their questions lies in better observation and decoding of the overlapping, multiscale spatiotemporal patterns that arise in the real world. The contaminant transport observation and management research area (known as “contam”) focuses on developing and implementing ENS technology to support this new observational strategy in the context of mass and energy distributions and fluxes across a range of temporal and synoptic scales. While this focus is similar to that for other applications domains (e.g., habitat monitoring), contam is unique in that it is often concerned with enabling adaptive management of environmental problems through engineered responses triggered by ENS observations.

Contam’s observational networks, like those of other application domains, must be collaboratively designed by technology and applications domain researchers. An interdisciplinary approach is needed because it is difficult to conceive of an effective spatiotemporal sampling plan without domain-specific knowledge and network programming tools are not yet user-friendly enough to see widespread use amongst application domain experts. The ENS problem being addressed by contam projects below is the design of sensor networks supporting physical and chemical observations within and between environmental media, including land, air and water. These projects demonstrate the CENS evolution from controlled test beds to limited real-world deployments to a proposed large, multiscale water quality observation and management network. The current emphasis of contam is on the soil domain which is by nature a rich context for ENS development because of the natural heterogeneity of such media and the inherent cost and technical challenges of deploying sensor networks in these environmental media.

Contam research accomplishments over the past year have been significant. The underlying themes have been (1) integration of deterministic environmental simulation models into sensor networks, and (2) beginning transition from laboratory to field with the objective of addressing the environmental sensor network calibration problem in a complex real system.

OBJECTIVES

The objectives of the 3 projects are summarized below.

Contaminant Source Assessment:

• Devise and execute heat transfer experiments as an analog to contaminant transport (exploiting OTS temperature sensing technology).
• Develop a DAQ system with embedded, real-time parameter estimation routines
• Develop a domain-specific real-time sensor network design algorithm.
• Extend the system to ionic contaminant species (e.g., nitrate).

Soil Pylon Sensor Array Design and Validation:

• Create and test prototypical soil pylon sensor array and DAQ system in controlled soil column experiments.
• Develop embedded, real-time soil simulator parameter estimation and adaptive management algorithms, and exercise these algorithms for temperature and soil moisture using soil column setup.
• Extend the system to key nutrient species using potentiometric nitrate sensors, then expand to other water quality sensors.
• Deploy and test pylons for remote DAQ, remote pylon reconfiguration, and 1D simulation/management at the Palmdale test bed.

Multiscale Soil Sensor Network Deployment:

• Characterize the geospatial soil properties at the Palmdale test bed and develop algorithms for designing a 3D sensor network in soils.
• Scale up soil pylon deployment to 3D heterogeneous array of sensors at the Palmdale test bed.
• Develop and test deterministic and nondeterministic algorithms for calibrating a 3D soil sensor network
• Demonstrate the effectiveness of project methods, technology, models and algorithms to understand nitrate propagation in the soil domain and manage a multi-objective water resources management problem.