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During a mass shooting incident, every second matters. On August 4, the Dayton, Ohio shooter needed less than 20 seconds — the amount of time it took police to respond to the scene — to murder nine people and injure over a dozen more.
Technology firms in the US are leveraging artificial intelligence to identify firearms and alert law enforcement within seconds in case of a mass shooting incident.
Athena Security founders Lisa Falzone and Chris Ciabarra, realized that mass shootings were being recorded by cameras and that a layer of artificial intelligence could be added to these systems.
Their AI technology connects directly to current security camera systems to deliver fast, accurate threat detection – including guns, knives, and aggressive action. The system can also alert users to falls, accidents, and unwelcome visitors.
The company uses object-motion detection to spot when an individual brandishes a fireman, and immediately send an alert to their client, whether that’s a private security firm or local law enforcement, according to fastcompany.com.
The AI object-motion detection is camera agnostic, meaning it can work on any CCTV system. When a gun is detected, the video feed of the active shooter is made available to the client both on mobile devices and desktop computers, allowing officers to know what they are dealing with and where it is happening, all in the space of three seconds, according to the company.
“The way that police get information right now is through a lot of panic: People calling 911, and the police thought it was multiple stores and they had no idea where the shooter was, and it took a long time to find the shooter,” Falzone says. “Giving the police accurate information is so critical to response time. So, even if you do detect a gun that a shooter is firing, every second counts. If you can get police there 30 seconds faster, or even seconds faster, those are lives saved.”
“We send an alert to e-911 and then they have that link and see exactly what’s going on during the crime,” Falzone explains. “Lots of police forces have tested the technology… We’ve created a really accurate algorithm to achieve over 99% accuracy.”