Smart Transportation


Miovision, a global leader in smart traffic technology, is building the foundation for smart cities with the world’s most advanced traffic AI.Earlier this year, Miovision launched Miovision Labs to be the research and testing ground for the next generation of traffic technology. Part of that work is helping cities use traffic data to make better decisions, and study how emerging technologies such as computer vision, deep learning, big data analytics and embedded device design can play roles. Miovision Labs explores new ways to make intersections more responsive to real-time traffic conditions. They do this using industry-leading NVIDIA graphics processing units (GPUs) to quickly analyze huge volumes of data, and in doing so, bring their AI capabilities to a whole new level.

“Miovision is creating the world’s first neural network for traffic,” said Kurtis McBride, Miovision CEO and co-founder. “In the near future, the combination of our technology will make it easier for cities to monitor traffic and address problems to help people get around more quickly and safely.”

Today, Miovision transforms video of vehicle, cyclist and pedestrian traffic into analytics via the cloud where it is processed by the NVIDIA GPUs and converted to usable data to help city planners improve traffic flow.

Eventually, AI will be built into devices to process data at the roadside. That information will then be fed back into the system to alert the right departments in real time. For example, a sensor might detect a double-parked car blocking a lane of traffic and alert traffic managers to adjust nearby traffic lights to improve vehicle flow. They could also alert police in case of an emergency. The goal is to use Miovision’s advanced AI in real time so that traffic incidents can be addressed immediately. Responsive cities are smarter cities, and giving them the ability to react quickly helps cities get on the right track to achieving their smart city visions.

“Today, we’re helping cities with information and technology to build better transportation systems, but we’ve only scratched the surface,” McBride said. “Through the research we’re doing at Miovision Labs, using NVIDIA GPUs, with academic partners like the University of Waterloo, University of Toronto, and University of Sherbrooke, we’re building a neural network for transportation that will be the foundation for smart cities of tomorrow.”

McBride will speak about Miovision’s deep learning traffic analytics system today at the GPU Technology Conference in Silicon Valley.