City-Scale Edge Inference, Built in 3 Weeks
April 24, 2019
Video surveillance is growing at a breakneck pace, creating urgent demand for automated analytics.
Video surveillance is growing at a breakneck pace, creating urgent demand for automated analytics. Deploying hundreds to thousands of cameras results in far too many video streams for humans to monitor. To help cities make better use of this data, cloud-based AI solutions are coming to the rescue.
In this article, IoT engineers will learn:
• Why deep learning at the edge enables more powerful analytics in the cloud
• How the OpenVINOTM Toolkit enables deep learning and accelerates edge surveillance
• About tuning video analytics algorithms for a range of CPUs, GPUs, and other accelerators