In industrial IoT, running machine learning (ML) models on edge devices is necessary for many use cases, such as predictive maintenance, quality improvement, real-time monitoring, process optimization, and security. The energy industry, for instance, invests heavily in ML to automate power delivery, monitor consumption, optimize efficiency, and extend the lifetime of their equipment.

Wind energy is one of the most popular renewable energy sources. According to the Global Wind Energy Council, 22,893 wind turbines were installed globally in 2019, produced from 33 suppliers and accounting for over 63 GW of wind power capacity. With such scale, energy companies need an efficient platform to manage and maintain their wind turbine fleets, and the ML models running on the devices. A commercial wind turbine costs around $3–4 million. If a turbine is out of service, it costs $800–1,600 per day and results in a total loss of 7.5 megawatts, which is

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