Key Points:

• • Bridge structural health monitoring requires continuous analysis of vibration data to detect potential damage early.
• • Deep learning models can process raw accelerometer data directly at the edge without complex preprocessing.
• • WaveNet achieves 99% accuracy in classifying 15 different damage states while requiring only 92.5MB of memory.
• • The solution can be deployed on affordable edge devices like Raspberry Pi with inference times of a few seconds.