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Cloud Computing

Nvidia launches Metropolis edge-to-cloud video analytics platform for ‘AI cities’

Tom StoneBy Tom StoneMay 10, 20172 Mins Read
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Paving the way for the widespread use of artificial intelligence (AI) in smart cities, Nvidia has unveiled the Metropolis intelligent video analytics platform, which makes cities safer and smarter by applying deep learning to video streams for applications such as public safety, traffic management, and resource optimization.

Video is the world’s largest generator of data, captured by hundreds of millions of cameras deployed in areas such as government property, public transit, commercial buildings, and roadways. By 2020, the cumulative number of cameras is expected to rise to approximately one billion. Humans currently monitor only a fraction of captured video, with most stored on disks for later review. Initial efforts at real-time video analytics techniques have proved far less reliable than human interpretation. Intelligent video analytics solves this challenge by using deep learning in cameras, on-premises video recorders and servers, and in the cloud, to monitor video instantaneously with accuracy and scalability.

Instead of just recording and storing footage, using the Metropolis platform, every camera’s output can be constantly analyzed and transformed into useful data points. For transportation agencies, its abilities in vehicle recognition and pattern tracking could be applied to intersections that can read traffic flows and adjust their traffic light patterns accordingly; camera systems that can automatically flag incidents or unusual events and notify operators for immediate action; or intelligent car parks that can direct vehicles to the closest vacant spaces.

Metropolis spans multiple Nvidia products that operate on a unified architecture. High-performance deep learning inferencing happens at the edge with the Jetson embedded computing platform, and through servers and data centers with Tesla GPU accelerators. Rich data visualization is powered by Quadro professional graphics, and the entire edge-to-cloud platform is supported by Nvidia’s rich software development kits, including JetPack, DeepStream, and TensorRT. More than 50 Nvidia AI city partners already help customers reveal insights and take real-time action using deep learning on the company’s GPUs (graphics processing units). Among them are surveillance camera and video management industry leaders, such as Avigilon, Dahua, Hanwha Techwin, Hikvision and Milestone.

“Deep learning is enabling powerful intelligent video analytics that turn anonymized video into real-time valuable insights, enhancing safety and improving lives,” explained Deepu Talla, vice president and general manager of the Tegra business at Nvidia. “Our Metropolis platform enables customers to put AI behind every video stream to create smarter cities.”

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Tom Stone

Tom has edited Traffic Technology International (TTi) magazine and its Traffic Technology Today website since May 2014. During his time at the title, he has interviewed some of the top transportation chiefs at public agencies around the world as well as CEOs of leading multinationals and ground-breaking start-ups. Tom's earlier career saw him working on some the UK's leading consumer magazine titles. He has a law degree from the London School of Economics (LSE).

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