Learn how VisionLabs GPU-powered solutions contribute to creating a safer, smarter Megacity a metropolitan area with a total population in excess of ten million people. We'll do a deep dive into three implemented and ongoing huge scale smart-city projects, understand challenges, technical specifics and how GPU computing impacts each of these cases: Face authentication-based immobilizer and driver monitoring systems for municipal service vehicles powered by the NVIDIA Jetson TX2 embedded platform; Megacity scale vehicle traffic analysis and anomalies detection powered by NVIDIA Tesla P40 with over 80 million daily recognition requests; National scale face identification platform for financial services with over 110 million faces in its database. The foundation of all these projects is VisionLabs LUNA a cross-platform object recognition software based on proprietary deep neural networks (DNN) inference framework. To build cost-effective solutions, VisionLabs use know-hows in DNN quantization and acceleration. In terms of accuracy, VisionLabs is recognized as a top three best in the world by National Institute of Standards and Technology's face recognition vendor test, and LFW by University of Massachusetts challenges.