05/27/2019
New research seeks to improve the effectiveness of unmanned aerial vehicles in search and rescue operations.
The U.S. National Park Service documented almost 3,500 search and rescue missions in 2017 alone. And speed is essential when someone goes missing, so search coordinators tend to throw in every tool at their disposal: volunteers, scent-trained dogs, horses and vehicles of all kinds often pour into the area.
Drones may seem like an obvious way to save precious time and resource. Now, with the summer outdoor season fast approaching, researchers at Virginia Tech (supported by a $1.5 million grant from the National Science Foundation) are developing algorithms and machine learning tools to better utilize these eyes in the sky.
First, there is the matter of where a drone should start looking. To find ways to narrow this down, Nicole Abaid, an assistant professor in Virginia Tech’s Department of Biomedical Engineering and Mechanics, used algorithms to develop a mathematical model of what humans do in such situations. “Someone with dementia, when they're lost, will behave significantly differently than like a child or a despondent person,” Abaid says.
For data to feed the algorithms she turned to search theory researcher Robert J. Koester, who says he has used information from more than 140,000 search and rescue incident reports for his 2008 book Lost Person Behavior, which he regularly updates. Before becoming a consultant on the new project, he had already created a set of predictive tools to help coordinators narrow their search parameters. “I've been able to create models that potentially predict what the missing person is going to do,” Koester says. Abaid incorporated his historical data into her own mathematical model. “The model generates a trajectory, like a path that we think the lost person would take,” Abaid explains.
This model could help guide a search and rescue operation, says research team leader Ryan Williams, an assistant professor in the Bradley Department of Electrical and Computer Engineering within Virginia Tech’s College of Engineering. “If we have an idea of where this person started, and when they were last seen, we can better predict where they may have gone and deploy drones and people to better cover those areas,” Williams says. “We can generate meaningful maps that human searchers can use for much better decisions at the beginning of the search.”
Below, the Weber County Sheriff’s Search and Rescue teams wait for drones to complete an initial field survey during a field training exercise in Ogden, UT. Search operations often use multiple resources including drones, K9 assets, and ground searchers. Credit: Sheri Trbovich Weber County Sheriff’s Search and Rescue