Over the course of two years, Anika Puri created ElSa (short for elephant savior), a low-cost prototype of a machine-learning-driven software that analyzes movement patterns in thermal infrared videos of humans and elephants. Puri says the software is four times more accurate than existing state-of-the-art detection methods. It also eliminates the need for expensive high-resolution thermal cameras, which can cost in the thousands, she says. ElSa uses a $250 FLIR ONE Pro thermal camera with 206x156 pixel resolution that plugs into an off-the-shelf iPhone 6. The camera and iPhone are then attached to a drone, and the system produces real-time inferences as it flies over parks as to whether objects below are human or elephant.
Puri submitted her project to this year’s Regeneron International Science and Engineering Fair, the world’s largest international pre-college STEM competition, where her work is in the company of other highschoolers’ novel designs. Her eloquence in describing her research and its potential impact on society earned her the Peggy Scripps Award for Science Communication, and she also won a top award in the competition’s earth and environmental sciences category.