Artificial Intelligence Meets Gun Violence
Since the beginning of the 21st century, gun violence has become one of America's most pervasive problems. According to the Gun Violence Archive, there have been more than 22,000 gun-related crimes year to date; however, civilians only report about 20 percent of shootings to law enforcement. ShotSpotter, a company dedicated to making campuses and cities safer, utilizes machine learning to detect the exact location and type of a shot.
The company uses a series of sensors that differentiates everyday noise from the bang of a bullet. After a shot, ShotSpotter's building-mounted monitors record the exact moment of the shooting. The company's smart software locates the gunshot by triangulating the acoustic signals among nearby monitors. Once nearby monitors absorb the sound, ShotSpotter's artificial intelligence instantaneously determines the type of shot. Within minutes, ShotSpotter provides local police officers with the location, time, and analytics of the kind of shot. This technology protects the police force from casualties associated with incomplete information while providing a more effective way of identifying suspects and preventing further shootings.
ShotSpotter has decreased the number of gun-related crimes and increased the number of arrests in many of America's most violent cities. For example, since implementing ShotSpotter: Englewood, one of Chicago's most dangerous areas experienced a 40 percent decline in shootings. Additionally, Camden County, New Jersey has reported a 46 percent decrease in homicides, and Rochester, New York has seen a 40 percent decline in gunshot incidents.
Written by Matthew Durborow & Edited by James Mueller & Alexander Fleiss
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