Challenge

The City of Vaughan sought to evaluate emerging AI technologies that could improve traffic safety and mobility in school-zone areas. The goal was to understand how autonomous drone-based monitoring and real-time analytics could identify congestion, queuing, and near-miss incidents more accurately than manual methods.

Solution

Through Ontario’s OVIN Demonstration Zone, AirMatrix deployed its Aether AI platform to collect and analyze live footage from camera-mounted drones operating around Maple High School and the Creditstone rail crossing. Libra processed the footage using AI models to extract traffic behavior data such as vehicle speeds, queue lengths, and near-miss events. The system combined aerial footage with software analytics to quantify road safety metrics and identify opportunities for infrastructure improvement.

"It was a valuable experience collaborating with city stakeholders as we worked to responsibly integrate AI technology. Our system successfully demonstrated how AI can leverage existing camera networks to generate key traffic insights, optimize signal timings, and improve traffic flow" 
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Shayaan Haider, Co-Founder & Head of Product, AirMatrix

Results

• Captured 750+ vehicle trajectories and 39 safety conflict events.
• Accurately measured queue lengths and near-miss incidents using AI post-encroachment metrics.
• Demonstrated the operational viability of drone-based traffic observation for short-term studies.
• Provided Vaughan’s Traffic Engineering team with data-driven insights to support future planning.

‍Whats next?

Building on the Vaughan deployment, AirMatrix is introducing its AI-powered traffic camera, capable of performing real-time analytics on highways, intersections, and urban corridors. The system brings Libra’s intelligence to fixed infrastructure, giving cities continuous visibility without new hardware complexity.

Contact us to schedule a demo of Aether AI and see how real-time analytics can redefine traffic management in your city.

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