The students coded their own proof-of-principle algorithm which identified solar panels in a small test set with over ninety percent accuracy. They also painstakingly created a ground-truthed dataset that will help train future machine-learning algorithms.
Video: The students and their mentor talk about the project.
- Environmental Science
- Energy Systems
- Machine Learning
- Electrical Engineering
Undergraduates: Sharrin Manor, Wuming Zhang, Jeffrey Perkins, Arjun Devarajan
- Richard Newell, Director, the Energy Initiative at Duke
- Leslie Collins, Elec. and Comput. Engineering
- Timothy Johnson, Energy and the Environment
Project Mentor: Kyle Bradbury, Managing Director, Energy Data Analytics Lab