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Nevada Transportation Agency Uses AI for Weapons Detection

The Regional Transportation Commission of Southern Nevada is using artificial intelligence, machine learning and real-time data analysis to keep its facilities safe and improve response times to traffic incidents.

A passenger boards the SX-A Sahara Express Route bus operated by RTC of Southern Nevada.
Shutterstock/RYO Alexandre
Nevada’s largest metropolitan transit and transportation agency is turning to machine learning and artificial intelligence for some of its core jobs like responding to traffic incidents, planning transit routes, and even keeping bus facilities safer.

The Regional Transportation Commission of Southern Nevada (RTC), a far-reaching transportation agency with oversight of regional transportation planning and infrastructure in the Las Vegas metro area, is using a range of technologies to help it manage traffic and transit. In June, RTC began a partnership with ZeroEyes, using its AI-supported gun detection technology in a wide-scale deployment across RTC transit facilities.

ZeroEyes technology can process thousands of images in seconds in search of guns. It is viewed by law enforcement and other agencies as an aid in an era where guns are endemic and mass shootings have become nearly routine.

“There’s a different type of pressure on transit systems to try and solve for something that’s, quite frankly, a very complex societal issue,” RTC CEO M.J. Maynard said.

ZeroEyes is able to process massive amounts of imagery data every second, scanning areas for weapons. When a gun is detected, its operational center — staffed 24 hours a day with officials trained in law enforcement, military and other areas of public safety — takes over, said Sam Alaimo, ZeroEyes co-founder and chief revenue officer. The technology does not employ facial recognition.

“If these experts determine that the threat is valid, they dispatch alerts and actionable intelligence — including visual description, gun type, and last known location — to local law enforcement and RTC staff as quickly as three to five seconds from detection,” Alaimo said via email.

ZeroEyes is being used at RTC transit facilities, though not on transit vehicles. RTC “is the first transit provider to deploy ZeroEyes on a wide scale,” Alaimo said. The Southeastern Pennsylvania Transportation Authority (SEPTA) launched a pilot project with ZeroEyes in 2022 but an official said it was not expanded.

“There were only a few instances where the system alerted police to someone with a firearm, so we decided it wasn’t the right fit for SEPTA at this time,” said Kelly Greene, a SEPTA senior press officer, adding its “Virtual Patrol Unit,” which uses uses retired police officers to monitor live video feeds from SEPTA’s 31,000 cameras, “is helping to identify incidents sooner, dispatch officers more quickly, and share information in real time to apprehend offenders.”

An article in The Philadelphia Enquirer noted SEPTA’s security cameras lacked the modernization needed to support the ZeroEyes technology.

RTC’s CEO said the widespread deployment of ZeroEyes across its camera network should have a positive impact on customers.

“I think, for our customers, knowing that there’s an added layer of security, they understand that we’re doing all we can to provide the safest environment that is available to them while they’re taking public transit,” Maynard said.

Elsewhere in its tech stack, RTC uses a system from Rekor for traffic management. Rekor provides real-time data analysis for what’s occurring on roadways. Its technology, relying on the analysis of large amounts of data from numerous sources, led to a 17 percent decrease in response time for traffic incidents, Maynard said.

Last year, RTC began feeding transit data into the Rekor platform. This, along with other shared technology, lets its Traffic Management Center and Bus Operations Center essentially read the same screens, conducting traffic management and transit operations as one and allowing officials to jointly view the locations of buses and traffic incidents in one comprehensive map.

“If there’s an accident, that means a detour. And so the sooner we can get the bus onto the detour … that will ensure that we are able to operate in a way that is as efficient and effective as possible,” Maynard explained. “And that’s taking massive amounts of data, and then sharing it among data sets and databases, and it’s proven to be very, very effective.”

Data and technology used for transportation planning is also being used for transit planning. Traditionally, transit functions like route planning have been exceedingly labor intensive — but technology like machine learning and AI is able to take different data sets to do the heavy lifting in these tasks.

“If we’re able to tap into technology, that’s another huge tool for that planning team,” Maynard said. “For example, we’re able to take something that’s going to take three months, it now takes one month.”
Skip Descant writes about smart cities, the Internet of Things, transportation and other areas. He spent more than 12 years reporting for daily newspapers in Mississippi, Arkansas, Louisiana and California. He lives in downtown Yreka, Calif.