Interested in uncovering a use for unmanned arial vehicle technologies, or drones, that might de-stigmatize the popular image they’ve acquired through their military use abroad, Master of Science in Threat and Response Management students Joe Long, Lauren Peterson, Brandon Spakowski, and Howard Wu sought to outfit a drone with a signal-detecting device capable of locating cellphone signals as a way to improve the detection of humans following a major earthquake.
“There was some doubt expressed about whether we’d be able to do it or not,” said Wu, a resiliency manager and consultant based in New York. “Ultimately, that only had us think harder. The eureka moment
came with the realization that we could mount a detection device onto a drone and in that way, in the event of a major earthquake, determine where the greatest number of people were buried.”
Drawing on research that utilizes unmanned arial vehicle technology to triangulate a person’s location from cell phone signals in the case of avalanche rescue missions, the team realized that detecting earthquake survivors buried beneath rubble could be approached in a similar manner, even if it would involve a different set of technical specifications.
“We built on the avalanche literature by using it in a novel scenario,” said Peterson, an emergency management specialist with the Federal Emergency Management Agency. “Cell phone signal strength varies depending on the surrounding terrain, weather, and type of disaster wreckage, so there were additional factors we had to consider in the case of earthquakes.”
By mounting an off-the-shelf micro-computer equipped with a receiver and antenna onto a drone, the team then transported that signal to a laptop from where they were able to determine the signal’s original location.
“For proof of concept, it was really just a matter of fixing a platform to the drone and then mounting the micro-computer and antenna onto that,” said Long, a Chicago Police Department Sergeant in the narcotics division. “If we wanted to take the idea further, we’d have to build something internal to the drone and use a more powerful computer, but for what we needed to do something a little more basic sufficed.”
In field tests at Northeastern Illinois Public Safety Training Academy (NIPSTA), they successfully demonstrated their idea’s feasibility by flying their drone above a building with a collapsed roof and a multilevel parking structure, inside of which were two dummies with cell phones in their pockets.
“We were fortunate to have Jill Ramaker as our capstone advisor,” said Peterson, referring to the executive director at NIPSTA as well as MScTRM instructor. “She let us test out the device at NIPSTA in a setting that’s typically used to train firefighters. In this case, it served well to replicate earthquake conditions.”
The device successfully detected phone signals in mid-flight and sent those signals to a laptop. The only limitation was a lag of about 30 seconds in transporting the signal, which the team determined was a matter of a slow cellular network and an underpowered onboard antenna.
“Our device really represents a significant step in earthquake response,” Wu said. “Once the bugs are fixed, we can imagine teams of drones with signal-detecting ability being deployed immediately in a major earthquake scenario.”
“Our next step is to patent our idea,” he added. “And we’re already talking with some MScTRM instructors about possibly turning our idea into a paper and publishing it.”