About This Training
Learn how vibration, ultrasonic or audio sensors can be paired with a low-cost MCU to detect anomalies
that predict and identify the root cause of industrial machine failures. After a self-learning procedure,
the system transforms multi-sensor data into a small signature capable of identifying anomalies or drifts,
which can then generate alerts or alarms. Very low bandwidth, low-power and long-range networks can be used
to send this data to the cloud or a remote server for remote equipment monitoring. The battery-powered
reference system can run for 5 years on two AA batteries.