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3D printing: Anomaly detection with STM32MP15-based IoT Gateway and AWS Greengrass

3D printing: Anomaly detection with STM32MP15-based IoT Gateway and AWS Greengrass
3D printing: Anomaly detection with the help of STM32MP15-based IoT Gateway and AWS Greengrass

The 3D printer is equipped with two acceleration sensors whose motion data is routed to two ST Nucleo boards via Wireless Bluetooth and Wireless LoRa. The NUCLEO-WB55RG is connected wirelessly to the STM32MP15-based IIoT Gateway by DH electronics with certified Greengrass 2.0 build. The machine learning algorithm for anomaly detection of NUCLEO-WB55RG is performed on the IIoT Gateway. Complementary, the machine learning algorithm to detect anomalies in the motion data from the LoRa sensor is performed on NUCLEO-WL55JC1 to reduce communication bandwidth. NUCLEO-WL55JC1 is connected to the LoRa base station and the IoT Core for LoRaWAN via the IIoT Gateway. A graphical display to show if an anomaly is detected is done on AWS cloud. The machine learning algorithm was built with the same setup in data collect mode using AWS Sagemaker, Sagemaker neo and Cube.AI.