BLE based Audio Platform for Condition Monitoring Applications

Industry 4.0 has driven the adoption of smart, connected Internet of Things (IoT) devices, facilitating the widespread application of condition monitoring and predictive maintenance techniques. This work focuses on developing an IoT sensor device capable of wirelessly transmitting a stereo microphone data stream and vibration measurements over Bluetooth Low Energy. The acquired sensor signals are received and stored on a PC application, where they are subsequently analyzed. The recorded measurements serve to develop machine learning algorithms to predict the condition of monitored assets. The system can transmit two audio data streams with a sampling frequency of 8 kHz and bit-depth of 16 bit, alongside a vibration data stream from a six-axis inertial measurement unit and temperature readings at a 1 kHz rate. In an example application, the functionality of the developed sensor system is evaluated, demonstrating its suitability for remotely monitoring the mechanical condition of machines or equipment by acquiring, wirelessly transmitting, and providing real-time sound and vibration emission data with high temporal resolution for higher-level analysis systems.