Electricity Access in Developing Countries from Aerial Imagery

Project Summary

Boning Li (Masters Electrical and Computer Engineering), Ben Brigman (Electrical and Computer Engineering), Gouttham Chandrasekar (Electrical and Computer Engineering), Shamikh Hossain (Computer Science, Economics), and Trishul Nagenalli (Electrical and Computer Engineering, Computer Science) spent ten weeks creating datasets of electricity access indicators that can be used to train a classifier to detect electrified villages. This coming academic year, a Bass Connections Team will use these datasets to automatically find power plants and map electricity infrastructure.

Themes and Categories
Public Policy, Energy & Environment
Data+, Energy Data Analytics
Year
2017
Contact
Ashlee Valente
Center for Applied Genomics and Precision Medicine
ashlee.valente@duke.edu

Project Results: The team gathered electrification ground-truth data for over 36,000 villages in the Indian state of Bihar, and also collected measurements relevant to electricity consumption for those villages including lights at night data and irrigation metrics. They also created an Amazon MTurk tool that crowdsourced the annotation of key electricity indicators (such as power plants and transmission lines) in imagery data.

Partially sponsored by Bass Connections and the Duke University Energy Initiative

Click here for the Executive Summary

Faculty Leads:

Kyle Bradbury

Leslie Collins

Timothy Johnson

Marc Jeuland

Guillermo Sapiro

Project Manager: Boning Li

"The Data+ team created two new datasets that we'll immediately deploy as a part of our core research efforts and will serve as the basis for an upcoming Bass Connections in Energy project. The outputs will be used towards two new research projects on energy infrastructure and access in developing countries, and will serve as the ground truth data for developing machine learning techniques for identifying energy infrastructure and access. The students were fantastic - hardworking, passionate about their work, and all-around wonderful people to work with." — Kyle Bradbury, Lecturing Fellow and Managing Director, Duke Energy Data Analytics Lab

 

Related People

Related News

Mapping Electricity Access for a Sixth of the World’s People
Tuesday, August 8, 2017
For ten weeks from May through July, a team of Duke students in the Data+ summer rese ...
Duke Undergraduates Use Machine Learning Techniques to Evaluate Electricity Access in Developing Countries
Thursday, September 14, 2017
A team of Data+ students, led by researchers in the Energy Initiative's Energy Data Analytics L ...

Related Projects

American Predatory Lending (Year 3)

This team is part of an ongoing project dedicated to exploring how states and local communities responded to the causes of the 2007-09 Global Financial Crisis. Led by faculty from the Global Financial Markets Center at Duke Law the Data+ team  will conduct analysis of multiple states mortgage enforcement databases to gain a better understanding of how state regulators were, or were not, enforcing existing state law pertaining to mortgages leading up to the crisis. Our website has an example of what this will look like, as last year we analyzed North Carolina’s mortgage enforcement actions and displayed them by topic.

Project Lead: Lee Reiners

Project Manager: Malcolm Smith Fraser

Racial Disproportionality and Disparities in the Child Welfare System: Child Protective Services and Foster Care

Nationally there is a disproportionate number of children of color (African American & Latino) in the child welfare system. Durham County is no different. However, reviewing this problem through the lens of data has not been done to formulate or implement possible solutions. Durham County Department of Social Services Child & Family Services would like to evaluate systems to identify where and how disproportionality and disparity are occurring. It is occurring at the entry point of Reporting child abuse and neglect? Is it occurring at the case decision? Is our reunification time different for African American children? Or Does it take longer for a child of color to achieve permanence through adoption? Organizing the data to show us our “hot spots” would facilitate further discussion and focus on solutions to an age-old systemic problem.

Faculty Lead: Greg Herschlag

Project Lead: Jovetta L Whitfield

Agile Waveform Design in the Presence of Opposition: Quantifying Performance

Student teams will develop a benchmark dataset and explore its efficacy in an in house competition where they will put new innovative techniques such as machine learning to the test through a series of challenges.  A team of students will develop benchmark data pertaining to network performance in the presence of intentional and non-intentional degradation, ranging from sensor failure and additive noise to adversarial interference.  The students will analyze the baseline performance of the network, and measure performance of the degraded network with and without the inclusion of robust techniques that shore up robustness.  Students will have the opportunity to present findings to scientists & engineers from the Air Force Research Laboratory.

Faculty leads: Robert Calderbank, Vahid Tarokh, Ali Pezeshki

Client leads: Dr. Lauren Huie, Dr. Elizabeth Bentley, Dr. Zola Donovan, Dr. Ashley Prater-Bennette, Dr. Erin Trip

Project Manger: Suya Wu

See all Research