IIoT Workloads at the Smart Device Edge’s Predictive Maintenance blueprint is a complete solution that allows users to monitor and analyze data coming from a thermal imaging camera or vibration sensors at the edge and then send the data to the cloud of the user’s choice. This blueprint uses LF Edge’s Project EVE to secure and control a remote IoT Gateway, while using LF Edge’s Fledge to process the data at the smart device edge.
While the solution is complete, it is designed as lighthouse project that can be modified to receive data from various protocols including Modbus, OPC-UA, MQTT, CoAP, etc and send data to onsite historians or to any public cloud provider.
Features
- LF Edge’s Project EVE as an OS to provide remote management, Zero Trust security (physical and software)
- LF Edge’s Fledge as an IIoT framework for sensors, historians, DCS (Distributed Control Systems, PLC’s, and SCADA systems and connectivity to public or private clouds
- Remote monitoring and updating of applications, without bricking the device
- AI Models, real time data capture, and cleansing at the device edge
- Sample application that can be customized to meet many different Use Cases
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