Microsoft Fabric Real-Time: Streaming IoT Truck Data into an Ontology

In this video we'll take a look at a real-time streaming pipeline in Microsoft Fabric to process telemetry data from trucking equipment and automatically capture critical operational events. Our trucking company ontology models the core entities that drive our business—trucks, drivers, trips, terminals, customers, and loads. We've extended this model with a CriticalEvents entity that records faults detected by sensors on our trucks. Using Fabric Real-Time Intelligence, we stream telematics events directly into Fabric and process them as they occur. In this demo you’ll see: • Streaming IoT telemetry into Fabric using Event Streams • Filtering mechanical fault events in real time • Saving critical events to a Lakehouse table connected to the Ontology • Triggering automated workflows using Fabric Activator • Visualizing live events moving through the system • Running analytics on streaming operational data We simulate telematics data using a Python notebook that sends events into the streaming pipeline. When critical faults are detected, Fabric both stores them for historical analysis and triggers real-time workflows. Finally, we return to the ontology to see how these real-time events become part of the enterprise data model. This architecture enables organizations to combine IoT streaming, real-time automation, and knowledge modeling in a single platform. Topics covered • Microsoft Fabric Real-Time Intelligence • Fabric Event Streams • Fabric Activator rules and workflows • Streaming IoT / telematics data • Lakehouse event storage • Ontology-driven analytics • Real-time operational monitoring