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Smart City & Government

Dubai Traffic AI

Using AI to optimize traffic flow and reduce congestion in a major metropolitan smart city.

25%
Reduced Congestion
15%
Lower Emissions
AI
Powered Control

The Challenge

With a rapidly growing population and vehicle count, Dubai was facing increasing traffic congestion during peak hours. Traditional timer-based traffic signals were inefficient, leading to unnecessary delays and higher carbon emissions. The RTA needed a smart, adaptive solution to optimize traffic flow in real-time.

Our Solution

We implemented a comprehensive Smart Traffic Management System leveraging Computer Vision and AI.

Vision-Based Detection

Deployed AI-powered cameras at key intersections to count vehicles and analyze queue lengths in real-time.

Adaptive Signal Control

Signals dynamically adjust their timing cycles based on current traffic density rather than fixed schedules.

Incident Management

Automated detection of accidents and stalled vehicles, alerting the command center instantly for rapid response.

The Outcome

The pilot implementation resulted in a 25% reduction in average commute times across the controlled corridors. Carbon emissions dropped by 15% due to reduced idling, and traffic incident response times improved significantly.

Project Scope

Industry
Government / Smart City
Services
AI, Computer Vision, IoT
Tech Stack
PyTorch OpenCV Edge Computing

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