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.
The Internet of Things Event Learning Path is designed for Solution Architects, Business Decision Makers, and Development teams that are interested in building IoT Solutions with Azure Services. The content is comprised of 5 video based modules that approach topics ranging from IoT device connectivity, IoT data communication strategies, use of artificial intelligence at the edge, data processing considerations for IoT data, and IoT solutioning based on the Azure IoT reference architecture.
Each session includes a curated selection of associated modules from Microsoft Learn that can provide an interactive learning experience for the topics covered and may also contribute toward preparedness for the official AZ-220 IoT Developer Certification @ https://aka.ms/iotlp/certification.