These connected devices include OPC UA enabled sources such as most SCADA systems that support the MQTT protocol for data transfer.Īt the plant level, another component of the Azure IoT architecture, which is built on top of the IoT Hub – IoT Edge – handles certain workloads within the plant network itself for situations where latency is critical. Clue is designed to fit seamlessly into Azure’s reference architecture thereby easing the integration process.Ĭonnecting the plant to the cloud, the Azure IoT Hub acts as a bi-directional communications brain for all connected IoT devices – managing data transfers, updates, setting up credentials for every device, and defining access control policies. This valuable operational data is supplied to Clue’s powerful AI engine by leveraging Microsoft Azure’s IoT infrastructure.
How Falkonry leverages Azure IoTįalkonry Clue applies advanced analytics to multivariate time-series data to discover meaningful patterns. This allows for real-time condition discovery, classification, root cause explanations, reporting and visualization, all under a simple and intuitive interface with Falkonry Clue.Īnd the best way to put Clue to work is via Azure IoT. The analytics capabilities of these digital twins are augmented by Operational AI and learning mechanisms – essentially adding a “predictive” element to the digital twins. Digital twins create virtual abstractions of real world assets or processes together with all their associated granular data for applying analytics. This is where Falkonry’s predictive digital twins come in. Even more challenging is the complex AI modelling needed to gain meaningful insights from integrating these various components. Integrating assembly lines, IoT devices, data, analytics and finally people is always a challenge.
While this sounds promising, implementing such a digital transformation is often impeded by a number of hurdles.
The Industry 4.0 model of manufacturing extracts greater efficiencies from plant operations by infusing smart technologies.