Congratulations to Project ARI for taking second place in the 2017 Big Ideas Competition

I’ve been involved in the UC Berkeley Big Ideas competition as a judge for a couple years now, wanting to give back after the incredible experience I had with the CU New Venture Challenge. Over the course of these two years, I saw a number of amazing proposals, but this year I was absolutely blown away by Project ARI. The team was planning on working with the National Park Service to deploy drones equipped with their software to augment traditional search and rescue techniques. After reviewing their proposal, I gave their captain, Izzy Domi, high marks and went back about my business.

A month or two later, the Big Ideas team reached out to see if I wanted to mentor the team. I had never done this sort of thing before but was grateful for all of the guidance I got during the Agribotix pitch preparation sessions, so I agreed. Izzy and I met once a week for the duration of the competition and each week I was so impressed by the progress they made. In the end, ARI pivoted from a hardware/software play to a pure software one that integrated deeply into the technology already used in the SAR community.

I’m proud to report that the team’s hard work paid off and Izzy and her teammates took second place in the Hardware for Good category in the Big Ideas Competition. They beat out literally hundreds of teams for a nearly ten thousand dollar prize. Their award description is below.

ARI (2nd Place)
 Team Members: Isabella Domi, Jack Moorer, Jessica Palmer
 School: UC Merced
 Aerial Research Intelligence (ARI) is a service that allows search and rescue personnel to expand their options for locating missing persons in a more efficient manner using drone technology and machine learning capabilities. ARI can be used with any small unmanned aerial system that autonomously searches the area around an initial planning point and quickly processes aerial image data to detect people using a trained neural network. Using RGB and thermal video data from sensors on board the drone platform, ARI is able to determine images and GPS locations that indicate the presence of a missing person, which greatly speeds up the human intensive activity of reviewing footage.

While I hope I offered some help along the way, I can say for certain that the mentoring experience was a great one for me. I learned a ton from the team and wholeheartedly recommend anyone interested volunteer to mentor next year. Look forward to Big Ideas 2018!

Originally published at Daniel D. McKinnon.

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