PFI:BIC - A Smart, Flexible, Large-Scale Sensing and Response Service System (LASSaRESS) for Monitoring and Management of Ground, Air and Waterborne Contaminants

Award ID: 1632069

Oil leakage from underground cable systems leads to environmental damage and economic loss. World-wide, the impact is estimated at $2 billion in direct economic losses. When environmental and productivity costs are considered, the total harm from underground oil leakage is estimated to be much higher. The goal of this project is to develop a cost-effective, scalable, smart underground oil leak location system that can be modified to serve a host of applications in leak detection and pollution measurement including applications in gas leak detection, water leak detection, and pollution monitoring. The techniques developed through this project have the potential to improve future generations of distributed networked sensors through application of cloud computing technologies. This new smart system, when implemented to detect underground leaks, and more generally, pollutants is expected to make significant, positive environmental impacts. Given the team's past successful work in underground oil leak detection and mitigation, an immediate impact in scaling oil leak detection is expected. At the same time, the mini-mass spectrometers can in the future be configured to monitor many contaminants, thereby addressing a variety of environmental challenges. Project objectives are: 1) build the core smart system components, 2) develop core algorithms and build the smart system test bed, and 3) validate the test bed functionality in the field. First, mini-mass spectrometers will be fabricated, and a dynamically configurable cloud computing network will be developed with the goal of connecting multiple mini-mass spectrometers into an analytical system to collect leak source data. Collected data will be analyzed and leakage locations will be identified based on distributed sensor readings using an algorithm developed to dynamically optimize sensor positioning and identify leak location. Finally, the smart system will be implemented in the field to monitor a controlled, low-level, perfluorocarbon tracer leak. The expected outcome of this program is a low cost, self-configurable, highly flexible, mobile system that can locate leaks and contaminants with minimal human intervention. The team consists of faculty at Duke University (Pratt School of Engineering, Nicholas School of the Environment, and Psychology and Neurosciences), and staff at UNC's Renaissance Computing Institute (Chapel Hill, NC) as well as industry partners, PFT Technology, LLC (Bellmore, NY; small business). Duke's team combines material science, computer engineering, mass spectrometry, behavioral science and commercialization expertise. RENCI brings expertise in the latest cyber tools and technologies. Our industry collaborator, PFT Technology, LLC is recognized internationally as the leader in the field of perfluorocarbon-based leak detection, demonstrating successful leak detection programs for utilities in both the U.S. and the U.K. The project will impact multiple levels of students. Two PhD students (Duke) will be employed by the project. Professional Masters and PhD students in the Nicholas Environmental Innovation and Entrepreneurship Certificate Program (Duke) will, through their coursework, actively follow the progress of this research program to learn important aspects of translational research activities. Undergraduate students in Duke's Pratt School of Engineering Pratt Fellows and Grand Challenge Scholars programs will be offered opportunities to work on the project through these programs. This project will also engage students and faculty at Jordan High School by offering engagement opportunities such as independent study or science fair projects.

NSF Program Director: Jesus Soriano Molla