Subsurface Contaminant Monitoring and Prediction using Wireless Sensor Networks

Release of chemicals or biological agents in the subsurface often results in plumes migrating in the medium, posing risk to human and ecological environments. Temporal and spatial monitoring of the plume concentrations are needed to assess risk, make decisions and take remedial action. Current underground contaminant plume monitoring technologies are inefficient, expensive and ineffective. Wireless sensor technologies have the potential to dramatically improve this process.


A closed-loop system integrating wireless sensor network based monitoring with numerical models for plume tracking is being developed, in which sensor data continuously calibrates and validates the system identification and prediction models, while the output from these models direct the sensor network operation to optimize constraints such as accuracy and power consumption. The system is based on a novel virtual sensor network architecture with broader applicability beyond plume tracking. Algorithms and protocols being developed support the formation, usage, adaptation and maintenance of dynamic subsets of collaborating sensors, named Virtual Sensor Networks (VSNs). VSN protocols for collaboration among groups of sensors will greatly ease the task of deploying sensor networks, especially in environments where multiple geographically overlapping applications are deployed. A proof-of-concept laboratory test bed that captures the complex subsurface processes is used for integration and evaluation of VSN protocols. This interdisciplinary project significantly advances the state-of-the art in subsurface plume tracking and sensor networking technologies. It stimulates a unique partnership of electrical engineers, computer scientists and environmental researchers, and demonstrate closed-loop operation of computer models and sensor networks to solve complex environmental problems.


  • Qi Han (Faculty)
  • Nicholas Hubbell (Master's Student)
  • Tissa Illangasekare (Co-PI, Division of Environmental Science and Engineering, Colorado School of Mines)
  • Toshi Sakaki (Co-PI, Division of Environmental Science and Engineering, Colorado School of Mines)
  • Anura Jayasumana (PI at Colorado State University)
  • Kevin Barnhart (Environmental Science and Engineering, PhD student)
  • Paul Shulte (CS, MS student)
  • Lisa Porta (Environmental Science and Engineering, MS student)
  • Kyle Fullerton (Undergraduate Student)
  • Anhvu Le (Undergraduate Student)
  • Philip Loden (Undergraduate Student)
  • Alex Osecky (Undergraduate Student)
  • Breian Wells (Undergraduate Student)



This project is supported in part by NSF CSR grants CNS-0720875 and CNS-0720889.