{"id":1549,"date":"2019-03-19T00:00:00","date_gmt":"2019-03-19T07:00:00","guid":{"rendered":"https:\/\/azure.microsoft.com\/blog\/microsoft-and-nvidia-extend-video-analytics-to-the-intelligent-edge"},"modified":"2025-06-18T07:26:42","modified_gmt":"2025-06-18T14:26:42","slug":"microsoft-and-nvidia-extend-video-analytics-to-the-intelligent-edge","status":"publish","type":"post","link":"https:\/\/azure.microsoft.com\/en-us\/blog\/microsoft-and-nvidia-extend-video-analytics-to-the-intelligent-edge\/","title":{"rendered":"Microsoft and NVIDIA extend video analytics to the intelligent edge"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Artificial Intelligence (AI) algorithms are becoming more intelligent and sophisticated every day, allowing IoT devices like cameras to bridge the physical and digital worlds. The algorithms can trigger alerts and take actions automatically \u2014 from finding available parking spots and missing items in a retail store to detecting anomalies on solar panels or workers approaching hazardous zones.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Processing these state-of-the-art AI algorithms in a datacenter requires a stable high-bandwidth connection to deliver videos feeds to the cloud. However, these cameras are often located in remote areas with unreliable connectivity or it may not be sensible given bandwidth, security, and regulatory needs.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Microsoft and NVIDIA are partnering on a new approach for intelligent video analytics at the edge to transform raw, high-bandwidth videos into lightweight telemetry. This delivers real-time performance and reduces compute costs for users. The \u201ccameras-as-sensors&#8221; and edge workloads are managed locally by <a href=\"https:\/\/azure.microsoft.com\/services\/iot-edge\/\" target=\"_blank\" rel=\"noopener\">Azure IoT Edge<\/a> and the camera stream processing is powered by <a href=\"https:\/\/developer.nvidia.com\/deepstream-sdk\" target=\"_blank\" rel=\"noopener\">NVIDIA DeepStream<\/a>. Once the videos are converted, the data can be ingested to the cloud using <a href=\"https:\/\/azure.microsoft.com\/en-us\/services\/iot-hub\/\" target=\"_blank\" rel=\"noopener\">Azure IoT Hub<\/a>.<\/p>\n\n\n\n<figure class=\"wp-block-image has-custom-border\"><img decoding=\"async\" src=\"https:\/\/azure.microsoft.com\/en-us\/blog\/wp-content\/uploads\/2019\/03\/e86d2867-40b5-4726-9334-82fb715526f5.webp\" alt=\"Edge appliance and Azure cloud diagram\" style=\"border-radius:0px\" title=\"Edge appliance and Azure cloud diagram\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">The companies plan to offer customers enterprise-ready devices running DeepStream in the <a href=\"https:\/\/catalog.azureiotsolutions.com\/\" target=\"_blank\" rel=\"noopener\">Azure IoT device catalog<\/a>, and the NVIDIA DeepStream module will soon be made available in the <a href=\"https:\/\/aka.ms\/iot-edge-marketplace\" target=\"_blank\" rel=\"noopener\">Azure IoT Edge marketplace<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Over the years, Microsoft and NVIDIA have helped customers run demanding applications on GPUs in the cloud. With this latest collaboration, NVIDIA DeepStream and Azure IoT Edge extend the AI-enhanced video analytics pipeline to where footage is captured, securely and at scale. Now, our customers can get the best of both worlds\u2014accelerated video analytics at the edge with NVIDIA GPUs and secure connectivity and powerful device management with Azure IoT Edge and Azure IoT Hub.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To learn more, visit the <a href=\"https:\/\/azure.microsoft.com\/services\/iot-edge\/\" target=\"_blank\" rel=\"noopener\">Azure IoT Edge<\/a> and <a href=\"https:\/\/developer.nvidia.com\/deepstream-sdk\" target=\"_blank\" rel=\"noopener\">NVIDIA DeepStream<\/a> product pages. If you are attending <a href=\"https:\/\/www.nvidia.com\/en-us\/gtc\/\" target=\"_blank\" rel=\"noopener\">GTC<\/a> in person, join us <strong>Tuesday, March 19, 2019 from 9:00 \u2013 10:00 AM <\/strong>at session S9545 \u2013 \u201cUsing the DeepStream SDK for AI-Based Video Analytics\u201d or visit Microsoft at Booth 1122.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial Intelligence (AI) algorithms are becoming more intelligent and sophisticated every day, allowing IoT devices like cameras to bridge the physical and digital 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