In this session we will explore strategies for secure IoT device connectivity in real-world edge environments, specifically how use of the Azure IoT Edge Gateway can accommodate offline, intermittent, legacy environments by means of Gateway configuration patterns. We will then look at implementations of Artificial Intelligence at the Edge in a variety of business verticals, by adapting a common IoT reference architecture to accommodate specific business needs. Finally, we will conclude with techniques for implementing artificial intelligence at the edge to support an Intelligent Video Analytics solution, by walking through a project which integrates Azure IoT Edge with an NVIDIA DeepStream SDK module and a custom object detection model built using CustomVision.AI to create an end-to-end solution that allows for visualization of object detection telemetry in Azure services like Time Series Insights and PowerBI.
This content may be reused as-is across partner, field, and third party events or modified to suit custom audiences. The video resources and presentation decks are open-source and can be found on GitHub @ http://aka.ms/iotlp