Mo Charnot
Raúl Alvarado and Haize Christiansen demonstrate how SCOOBY detects the location of a sound after the club’s other members pop a balloon across the room.
As the threat of school shootings continues to loom over the country—with EducationWeek reporting 18 shootings resulting in five deaths and 27 injuries in 2024—a team of students in Capital High School’s Computer Science Club have been working on technology that could help in such situations: a robotic gunshot detection system they named SCOOBY (named after Scooby-Doo).
The club’s mentor and electronics expert Dave Ritter originally brainstormed the project; Ritter has been working with computer science teacher and club sponsor Barbara Teterycz and Capital High students for the past four years to show them “the possibility of a career in electronics.”
“In a Zoom meeting [with the students and Teterycz], I mentioned I’d seen in the papers that morning that there was a big school shooting,” Ritter tells SFR. “In a school shooting, the first thing that happens is a loud sound, and basically no one in the building knows what it is—it could be anything, and they don’t know where it came from. So, I said, ‘I think we could solve that with technology. Are you guys interested in that?’ And they were.”
Edward Scott, who led what was then a team of three students, says he felt the issue was of utmost importance, relating that the project was introduced to him and the other club members—Craig Andree Abajo and Jesse Burch—almost exactly a year after the May 24, 2022 school shooting at Robb Elementary in Uvalde, Texas, which resulted in the deaths of 19 students and two teachers, alongside 17 injured.
“With Uvalde, they struggled actually finding the shooter, and it took a while to go in,” Scott tells SFR. “With SCOOBY, we could let the officials know where the shooting exactly is, what room they’re in and how many shots they fired.”
As a student who had recently moved to the area from Riyadh, Saudi Arabia, where school shootings are rare, Andree Abajo tells SFR he was “grateful” for Ritter’s suggestion
“When I came here, I was super afraid of school shootings,” Andree Abajo says. “Not only would this make people feel safe, but it would keep them safe.”
When designing SCOOBY, the students connected a few microphones to a small Arduino Nano computer. Throughout the summer, they learned how to code a processor that listens to the microphones and tested it repeatedly. When researching for the project, Ritter says he and the students found the closest way for the students to test SCOOBY’s abilities is to inflate balloons until they burst, which produces a sound similar to gunshots in length and noise level.
“It was such a great idea, because it’s a wonderful solution to a problem that our nation’s really plagued with, because every day I’m wondering, ‘Is a shooter going to come in?’” Scott says. “In my freshman year, there was one morning where there was a lockdown because a kid took a gun to the parking lot. I remember that really well.”
The project took inspiration from the Shotspotter, a gunshot detection system several large cities use to detect, locate and alert law enforcement of potential gunshot sounds. However, the Shotspotter has been continuously criticized for its high cost and low accuracy in detecting gunshots—including in Albuquerque— so Ritter, Teterycz and the students utilized inexpensive parts that would set the unit price under $100, making it more affordable to schools, and used a 2011 paper from the Acoustical Society of America to study gunshot sound characteristics.
Throughout the year, four more students joined the Computer Science Club and contributed heavily to the project—Raúl Alvarado, Britny Marquez, Haize Christiansen and Jordan Minh Lam.
Alvarado says when he joined, he felt the project’s focus on solving a real-world issue “really hit my core values.” Christiansen, who joined the project in early September after hearing about it from Andree Abajo and Burch, says he “got super invested” in the work.
“I’ve always liked stuff like this, so I figured, now I have an actual opportunity to work on it,” Christiansen tells SFR. “If we can help even in a small way, even just by bringing some sort of awareness to it, that’s already doing a big thing to help prevent it.”
Several students involved in the SCOOBY project had little experience in coding, and Ritter says the students impressed him with how quickly they caught on.
“We had a session where we hooked some LEDs on this processor for the prototype SCOOBY, and I wanted them to write code to blink the LED lights,” Ritter says. “Jesse [Burch] never had a coding course, not even Python. You can imagine the kind of intellectual leap you have to take to understand what code is and modify it. At the end of the session, he got it working. When I looked at it, I was just shocked, because it was completely different from either what I had done or what everyone had done, and it was beautiful.”
After completing the project and entering several state competitions, the students won several awards and finalist positions, including Samsung Solve for Tomorrow; the Governor’s STEM Challenge; the Congressional App Challenge in New Mexico’s 3rd Congressional District; and this year’s Supercomputing Challenge.
“This is just amazing,” Teterycz tells SFR. “In one year, they’ve had so many achievements, so much learning—and I’ve never had such a huge team.”
The students plan to further improve SCOOBY this summer and in the upcoming school year. Alvarado intends to build a supercomputer out of Raspberry Pi computers that will train AI to help SCOOBY better detect gunshots; others want to add cameras to point in the direction from which SCOOBY detects gunshots.
“In the beginning, they need you a lot to give them guidance, but at some point they kind of take over the project, and then it’s their project and I’m just here, giving a little advice here and there,” Ritter says. “It’s a strange feeling, but it’s exactly the kind you want to have.”
