Introduction
Nevada’s largest metropolitan transit agency is embracing machine learning and artificial intelligence to tackle core responsibilities such as responding to traffic incidents, planning transit routes, and enhancing safety at bus facilities.
AI in Action
The Regional Transportation Commission of Southern Nevada (RTC) has partnered with ZeroEyes to deploy its AI-supported gun detection technology across RTC transit facilities. This innovative technology can analyze thousands of images within seconds to identify firearms, addressing the pressing issue of gun violence in public spaces.
How Does ZeroEyes Work?
ZeroEyes processes vast amounts of imagery data every second, scanning for weapons. Upon detecting a firearm, its operational center—staffed around the clock by trained professionals—takes immediate action. If the threat is deemed valid, alerts and detailed information are dispatched to local law enforcement and RTC staff within three to five seconds.
Impact on Public Safety
RTC is the first transit provider to implement ZeroEyes on a large scale, setting a precedent for other agencies. While SEPTA had previously piloted the technology, it was not expanded due to limited effectiveness. RTC’s CEO, M.J. Maynard, believes that this added layer of security will reassure customers about their safety while using public transit.
Integrating Technology for Efficiency
In addition to ZeroEyes, RTC utilizes Rekor’s system for traffic management, which has significantly improved response times for traffic incidents. By integrating transit data into the Rekor platform, RTC can streamline operations, allowing for efficient detours and real-time monitoring of buses and traffic incidents.
Future of Transit Planning
Machine learning and AI are revolutionizing transit planning, making traditionally labor-intensive tasks more efficient. Maynard notes that technology can reduce project timelines significantly, allowing for quicker implementation of necessary changes.
Conclusion
As RTC continues to innovate with AI and machine learning, the agency aims to provide a safer and more efficient transit experience for all. The integration of advanced technologies not only enhances security but also improves operational efficiency, paving the way for a smarter public transit system.
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