Tags: Smart Cities, Image Processing, Machine Learning, AI

Nvidia NoTraffic

The same technology advances that enable safer and self-driving vehicles can be used to improve traffic control systems by dynamically analyzing local traffic flows with sophistical image analysis, and then co-optimizing operation with adjacent control systems.

NoTraffic is an Israeli company that is building a turnkey traffic management platform powered by V2I communication & real-time optimization of signalized intersections.

Industry: Smart Cities

Business Need: Street traffic capacity and latency is an important municipal asset. Improved traffic flows improves commerce and makes the city a better place to live.

Key Enabling Technologies: Image Processing, Machine Learning, AI

Industry Perspective

Evolving technology can be translated into ongoing improvement in traffic capacity and latency.

Edge Need: Image processing and machine learning are computational intensive and latency sensitive. Edge cloud support as the low latency required for the application while enabling the outsourcing of server deployment and operation and the elimination of the need to deploy and support distributed servers.

Ease of Incorporation: Municipal traffic control systems are built on specific vendor or integrator architectures that would have to be adapted for this advance. It would also require significant investment in additional advanced cameras and their deployment.

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