Nvidia is rolling out a new platform that aims to provide deep learning analytics to video streams produced from smart city applications.
Dubbed Metropolis, the platform takes data captured by cameras deployed in government properties, public transit systems, commercial buildings and roadways, and then runs it through AI to help cities monitor video instantaneously.
The idea is that cities are inundated with video data and need a system that can focus attention on what matters most and where immediate action is needed. By Nvidia’s calculations, smart cities will have nearly 1 billion cameras in operation by 2020, creating a massive market opportunity around deep learning for video-enabled IoT devices.
From a technical perspective, Metropolis is a combination of multiple Nvidia products operating on a unified architecture. According to Nvidia, high-performance deep learning inferencing happens at the edge with the Nvidia Jetson embedded computing platform, and through servers and data centers with Nvidia Tesla GPU accelerators. Data visualization is powered by Nvidia Quadro professional graphics, and the entire platform is supported by Nvidia’s SDKs, including JetPack, DeepStream and TensorRT.
“Deep learning is enabling powerful intelligent video analytics that turn anonymized video into real-time valuable insights, enhancing safety and improving lives,” said Deepu Talla, VP and GM of the Tegra business at Nvidia. “The Nvidia Metropolis platform enables customers to put AI behind every video stream to create smarter cities.”
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