Traffic Management
Unlock unprecedented capabilities in Traffic Management through AI Computer Vision.
AI Computer Vision Capabilities In Traffic Management

Traffic Flow Monitoring and Analysis
Facilitate real-time monitoring and analysis of traffic flow, enabling the identification of congestion and the dynamic optimisation of signal timings; to alleviate traffic issues by providing timely adjustments to traffic signals based on the observed conditions.

Incident Detection
Automatically detect accidents, stalled vehicles, and other disruptions that impact traffic flow.

License Plate Recognition (LPR)
Identify licence plates, facilitating automated toll collection, managing parking efficiently, and supporting law enforcement practices.

Smart Parking
Monitor parking spaces, and provide drivers real-time information regarding available parking spots, to enhance the overall management of parking facilities.
The Value Of Applying AI Computer Vision To Traffic Management
Reduced Congestion
Optimise traffic flow and minimise delays, leading to shorter commute times and improved efficiency.
Enhanced Safety
Improve accident prevention by identifying potential hazards and allowing for quicker response to incidents.
Reduced Emissions
Minimise traffic congestion to decrease vehicle idling and lower overall emissions.
Improved Traffic Flow Predictability
Gain the ability to predict traffic patterns and proactively manage congestion before it occurs.
Data-Driven Decision Making
Gain real-time insights into traffic patterns to inform smarter infrastructure planning and traffic management strategies.
Tuba.AI: Your Gateway To Build AI Vision Models Effortlessly
Tuba.AI, is your one-stop platform for building AI computer vision applications faster & seamlessly. This user-friendly tool empowers anyone to effortlessly build computer vision models to recognise vehicles, signals, and patterns. Even without extensive AI expertise, you can leverage Tuba.AI to create solutions that address unique traffic challenges in your city.
For example, by using Tuba.AI, you can train AI computer vision models to analyse existing traffic camera footage, to identify and count vehicles, analyse lane usage patterns, and even flag potential hazards; all of which contributes to the optimisation of traffic management and the safety of citizens.