Building Safer Smarter Cities, Verizon Adopts NVIDIA's Metropolis AI Platform
【Summary】Data may one day be the lifeblood of the modern cities of the future. Right now, data is being captured by over 500 million cameras worldwide, and that number is growing exponentially. This is creating so much data, that’s impossible for humans to analyze. Nvidia is addressing this need with its Metropolis platform, which has just been adopted by Verizon.
Data may one day be the lifeblood of the modern cities of the future. Right now, data is being captured by over 500 million cameras worldwide, and that number is growing exponentially. This is creating so much data, that's impossible for humans to analyze.
Nvidia is addressing this need with its Metropolis platform, which has just been adopted by Verizon. Nvidia demonstrated the possibilities for its Metropolis AI platform at last week's Nvidia GTC Technology Conference in Silicon Valley.
NVIDIA's Metropolis AI software platform is leading this revolution, giving cities the tools and technologies to meet every challenge with smarter, faster applications, including the ability to recognize faces on a crowded city street.
AI is the key to turning data into insight. It's transforming how data is captured, inspected, and analyzed data to impact everything from public safety, traffic, and parking management to law enforcement and city services. To help make cities safer, smarter and greener, they need to be connected. This connectivity is a speciality of telecommunications giant Verizon.
Verizon is joined nearly 100 other companies already using NVIDIA Metropolis, the company's edge-to-cloud video platform for building smarter, faster deep learning-powered applications.
Verizon is a leading technology company with a reliable network service. Its Smart Communities group has been busy working with cities to connect communities and set them up for the future, including attaching NVIDIA Jetson-powered smart camera arrays to street lights and other urban vantage points.
Unveiled in May of last year, Metropolis is an edge-to-cloud video platform that includes tools, technologies and support to build smarter, faster AI-powered applications for everything from traffic and parking management to law enforcement and city services.
The Metropolis platform includes intelligent video analytics (IVA) including traffic management. IVA is helping to measure pedestrian flow and vehicle traffic to dynamically set traffic signal priority. This helps to eliminate congestion in cities, easing traffic and reducing pollution. The system can also reduce energy consumption.
"LED street lighting delivers big savings in operating expenditures," said David Tucker, head of product management in the Smart Communities Group at Verizon. "Rollout is happening fast across the globe and cities are expanding their lighting infrastructure to become a smart city platform that will enable them to link applications now and in the future, helping to create efficiency savings and a new variety of citizen services."
The arrays, which Verizon calls video nodes, use Nvidia's Jetson deep learning capability to analyze multiple streams of video data to look for ways to improve traffic flow, enhance pedestrian safety, and even optimize parking in urban areas.
Beta tests using proprietary datasets and models generated from neural network training are wrapping up in the U.S. Details of its commercial release are expected soon from Verizon.
Predicting Accidents Before They Occur
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.
Verizon's video nodes leverage Jetson TX1 to collect and analyze data on the furthest edges of a city's network. This supercomputer on a module accelerates deep learning at the edge, enabling real-time video analytics. All of this edge computing means more efficient, near real-time data analysis, and less high-cost streaming and storing of video over LTE and Wi-Fi networks.
Just like in a self-driving car, the video nodes capture and classify objects such as vehicles, cyclists and pedestrians, and identify interactions in near real time, providing city officials with a 24/7 data stream of everything from illegal right turns on red lights to pedestrian movement outside of designated crosswalks to parking lot metrics.
"In Jetson, we saw an ability to leverage GPUs to create a consistent deep learning view from the cloud to the edge — through the full stack," said Tucker.
In the future, you might get a speeding ticket without even being pulled over, when your car is connected to a smart city.
The Jetson-powered nodes can identify speeding vehicles, cyclist movements and handle other real-time tasks at the edge, once the data's back in the cloud, it can be used for predictive analytics.
"We're trending toward being able to spot something happening at intersection A and understanding the near real-time impact on intersections B and C a few blocks away," Tucker explained.
Smart Lights for Smarter Streets
In Boston and Sacramento, Calif., Verizon has deployed video nodes on existing street light infrastructures. In the future, these smart lights may be able to communicate with autonomous vehicles and support street light-to-car communication that could help reduce congestion and keep pedestrians and drivers safer.
Verizon's video nodes are part of its upcoming solution for supporting the safety of vehicles, pedestrians and cyclists. To enhance traffic safety, city leaders across the globe are increasingly turning to technology to help their communities become safer and friendlier.
More than 35 U.S. cities have signed up for Vision Zero, a global initiative to reduce pedestrian deaths. First implemented in Sweden in the 1990s, Vision Zero has spread to Europe and is now making its way to the U.S. — with deep learning at its core.
In September 2017, Alibaba and Huawei joined as new partners with Metropolis. Alibaba and Huawei join more than 50 of the world's leading companies already using the AI platform. Using Metropolis, companies can utilize data from more than 1 billion video cameras expected to be in cities by the year 2020 to solve a vast array of problems.
Originally hailing from New Jersey, Eric is a automotive & technology reporter covering the high-tech industry here in Silicon Valley. He has over 15 years of automotive experience and a bachelors degree in computer science. These skills, combined with technical writing and news reporting, allows him to fully understand and identify new and innovative technologies in the auto industry and beyond. He has worked at Uber on self-driving cars and as a technical writer, helping people to understand and work with technology.
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