Watch: A Wider Lens on Energy - Adapting Deep Learning Techniques to Inform Energy Access Decisions
Posted On:Wednesday, Jul 29, 2020 - 12:40 pm
Nearly a billion people in the world lack access to electricity. This global challenge is made all the more daunting by gaps in critical data about existing energy infrastructure. Policymakers and businesses need these data in order to make sound decisions (e.g., whether to expand the national grid, build a microgrid, provide direct off-grid solar PV, or pursue some other solution).
In this April 2020 webinar, an interdisciplinary team of Duke University students and faculty describe their efforts to use satellite imagery and cutting-edge deep learning techniques to help fill some of these gaps. Their project, “A Wider Lens on Energy: Adapting Deep Learning Techniques to Inform Energy Access Decisions,” is part of Duke’s unique Bass Connections program. Faculty affiliated with Duke’s Energy Data Analytics Lab led the team.
The team built on previous research projects conducted by students and faculty at Duke. Ultimately, with this series of projects, the Energy Data Analytics Lab seeks to build a tool researchers can use to identify and map out worldwide energy infrastructure and electrification needs to supplement ground truth information and support improved decision-making.
The 2019-2020 team sought to improve the existing model’s ability to adapt to different geographies, a goal that requires training the model with highly diverse datasets. Toward this end, team members worked to develop synthetic imagery that would help make the training datasets more representative of a broader range of geographies. In particular, they sought to train the model to recognize a more diverse array of rooftop textures (which differ by location).
Check out their presentation to learn more about their project’s aims, process, and outputs!
Student team members:
- Ayooluwa Balogun - Mechanical Engineering (E’21) (Participated Fall 2019)
- Aneesh Gupta - Computer Science (T’22)
- Scott Heng - Computer Science & Statistical Science (T’21)
- Vivek Sahukar - Masters Program in Interdisciplinary Data Science (MIDS’20)
- Norah Tan - Computer Science & Mathematics (T’22)
- Gaurav Uppal - Mechanical Engineering (E’20)
- Jason Wang - Computer Science (T’21)
- Winston Yau - Public Policy & Physics (T’22)
Duke faculty team leaders:
- Dr. Kyle Bradbury – Duke University Energy Initiative, Pratt School of Engineering
- Dr. Leslie Collins – Pratt School of Engineering
- Dr. Jordan Malof – Pratt School of Engineering
Visit the 2019-2020 team’s project website.
View the team’s data on GitHub.
Learn more about Bass Connections at Duke.
Learn more about the Energy Data Analytics Lab.
Join the Duke University Energy Initiative email list for updates on energy news, events, and opportunities at Duke.