ARI is an unmanned aerial system capable of detecting people from aerial video data during the initial search for a missing person.
ARI is designed to increase the chances of finding a missing person using the newest drone and machine learning technology. The system is modified to fit the methods of search and rescue teams of the National Parks so that it can be easily integrated without disrupting the current search processes.
HOW IT WORKS
At the start of a search for a missing person, a drone is deployed and autonomously scans the area around the initial planning point (IPP). RGB and thermal video from the flight is quickly processed through a trained neural network from AWS to determine the exact video frame and GPS location at which a person was found. All data collected can be viewed on the ARI app, allowing members of the Search and Rescue team access to the locations of the found person and images where the neural network detected a person.
Our drone platform is the 3DR Solo, which is already being used for search and rescue throughout the National Park System. ARI uses and RGB camera as well as FLIR thermal sensors for more accurate data and the ability to perform searches during the night.
ARI began as an undergraduate research project at the University of California, Merced, and is now competing in the Berkeley Big Ideas Competition for Spring 2017 in the Hardware for Good category.
What We've Achieved
- Initial stages of training the neural network
- ArcGIS online capabilities
- System integration into existing SAR methods
Our Future GOals
- Get full system working for Yosemite National Park to use
- Successfully help find missing persons
- Use for other applications such as wildlife research