Neurallabs ORCHESTRAITOR

It combines real-time data from cameras, IoT sensors, and connected infrastructure to monitor traffic conditions continuously. Using advanced analytics and machine learning, the system can detect incidents such as accidents, congestion, and violations, and automatically adjust traffic signal timings to optimize vehicle movement.

The system also supports centralized traffic control through an integrated command-and-control platform, enabling authorities to respond quickly to emergencies and manage traffic efficiently. Key outcomes include shorter travel times, lower fuel consumption, reduced emissions, and improved overall road safety. The solution is scalable and can be adapted for smart city initiatives in both small and large urban environments.

Objects Detected:

• Passenger cars.
• Motorcycles.
• Vans.
• Trucks.
• Buses.
• People.
• Scooter.
• Bicycles.
• Sea containers.

Vehicle Attributes:

• License plate.
• Vehicle type (Motorcycle, passenger car, van, truck, bus, etc.).
• Make.
• Color.
• Country.
• Speed.
• Lane.
• Traffic direction.

Traffic Infractions:

• Vehicles running a red light.
• Vehicles that do not stop at the STOP sign.
• Wrong turn.
• Illegal Stop.
• Vehicles at a restricted area where they are not allowed (Low Emission Zones, pedestrian zones, city center…)
• Instant vehicle speed.
• Average vehicle speed (Section control).
• Wrong way.
• Blocked intersection.
• Lane changes.
• Dangerous overtaking.
• Opposing lane invasion.
• Pedestrians improper crossing.
• Ignoring Zebra crossings.
• Scooters at sidewalk.
• Bicycles outside their lane.

More traffic infractions detection can be programmed.