Talk given by Mathieu Dumoulin at Big Data Analytics Tokyo 2017 and published on February 8, 2017
Real-time IoT sensor data collected from on a working, moving robot is used to predict failure using anomaly detection with autoencoders with H2O, all running on the MapR Converged Platform and MapR Streams (a Kafka superset implementation). This drives an AR headset to visualize the results (green OK red FAILURE) on a marker attached to the robot.
Demo video: https://vimeo.com/202732221/a2966bafd8
Source code: GitHub - mdymczyk/iot-pipeline