Development of an Embedded IoT Platform for Acoustic Emission Monitoring in Industry 4.0

This work presents a system combining hardware and embedded software to simplify the acquisition of acoustic emission signals using a wireless IoT sensor. Integrated into a larger ecosystem, this system supports fault diagnosis, feature extraction, pattern classification, and a cloud interface. It consolidates complex apparatus into a single tool, enabling remote sensor configuration during tests. The system also incorporates computational models for feature extraction and failure analysis, organizing tests through forms without needing external computers. This innovation advances the use of acoustic emission sensors in line with Industry 4.0, enhancing IoT sensor applications and improving manufacturing process efficiency.