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
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 Projects

Marine mammals exhibit extreme physiological and behavioral adaptions that allow them to dive hundreds to thousands of meters underwater despite their need to breathe air at the surface. Through the development of new remote monitoring technologies, we are just beginning to understand the mechanisms by which they are able to execute these extreme behaviors. Long- term animal-borne tags can now record location, dive depth, and dive duration and then transmit these data to satellite receivers, enabling remote access to behavior occurring both many kilometers out to sea and several kilometers below the ocean surface. 

The aim of this Data Expedition was for students to learn hands-on data visualization techniques using a variety of data types. Students first discussed how data visualization is useful, and tips to make graphs both visually appealing and easy to understand. 

The aim of our data expeditions course was to give students in Bio 190S-0.2, a summer session course in sensory systems, an introduction to how real data may actually look and how they may actually be analyzed. Over the course of a two-hour class session, 16 students ranging from 16-22 years old were given the opportunity to explore a dataset on the color vision capabilities of three species of cleaner shrimp.