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IGERT WISeNet Trainee, Keith Rudd, completes WISeNet Graduate Training Research Experience in Sardinia and Venice, Italy
Erosion and spatial patterns in the vegetation at the WISeNet Experiment site in Venice, Italy
Achievement/Results
Keith Rudd, a Mechanical Engineering and Materials Science PhD student and Trainee in the NSF Integrative Graduate Education and Research Training Program (IGERT) on Wireless Intelligent Sensor Networks (WISeNet) at Duke University completed a WISeNet Graduate Training Research Experience in June 2012 at our international experiment sites in Sardinia and Venice, Italy. The research focus at the Sardinia field site is on drought monitoring and prediction in semi-arid climates whereas the focus at the Venice Lagoon is on sea-level rise mitigation and adaptation measures. Through his research project titled “Optimal Root Structures in Water Limited Ecosystems”, Keith investigated root structures that maximize water extraction. During his research visit to the islands of Sardinia and the Venice Lagoon he was able to gain a better understanding of the environment he is simulating and was also able to get hands-on experience with many of the instruments used in environmental sensing.
Address Goals
As part of the WISeNet Certificate Program, students are required to complete a laboratory or field experiment selected from a menu of research experiences in environmental science or engineering and computer science at Duke or at partner companies and research institutions. These experiments are designed to provide students with unique multidisciplinary training experiences at research sites and laboratories equipped with state-of-the-art wireless sensors and facilities. Distributed sensing is crucial to understanding environmental change, and to protecting the health of humans. WISeNet trainees involved in the “environmental science” experiments apply emerging theoretical and computational tools for optimally collecting and assimilating sensor observations into distributed environmental forecasting models, and utilizing them for intelligent decision making. Also, trainees have the opportunity to apply sensor modeling, prediction, navigation and control methods to sensing problems on climate change, water quality, and drought monitoring and prediction.
