NXP and Microsoft Join Forces on Edge-to-Cloud Machine Learning Solution for Predictive Maintenance

May 13, 2019 Laura Dolan

SEATTLE. NXP and Microsoft will deliver Artificial Intelligence (AI) and Machine Learning (ML) capabilities for anomaly detection to Azure IoT users.

The solution includes a small form factor, low power System-on-Module (SOM) based on NXP’s 600 MHz i.MX RT106C Crossover Processors, an array of sensors, and an Anomaly Detection Toolbox. The Anomaly Detection Toolbox employs different local and cloud-based machine learning algorithms such as Random Forest and Support Vector Machines (SVMs) to identify anomalous system behavior.

The combined solution requires significantly lower cost and cloud bandwidth while providing persistent connectivity to the Azure IoT Cloud for data logging and processing. Applications include predictive maintenance, presence detection, and intrusion detection.  

“Preventing failures and reducing downtime are key to enhance productivity and system safety,” said NXP’s executive director and general manager of IoT and Security Solutions, Denis Cabrol. “We partnered with Microsoft to combine the power of Azure IoT with local intelligence running on NXP’s embedded technology to unlock innovation for the IoT – as part of our continued efforts to bring cognitive services down to the silicon.”

“We are proud to expand our collaboration with NXP to include the new Azure IoT and i.MX RT106C Anomaly Detection Solution,” said Microsoft’s VP of IoT Sales, Rodney Clark. “Solutions like this from NXP empower developers with products, tools, and services to accelerate development of complete edge to cloud solutions.”

Find out more at www.nxp.com.

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