DeepEcho: Industrial Audio Anomaly Detection (In Development)

An end-to-end MLOps pipeline designed for predictive maintenance in industrial environments. DeepEcho leverages unsupervised deep learning to monitor the “health” of pump machines by analyzing acoustic signatures.

The system transforms raw audio signals into Mel-Spectrograms, treating anomaly detection as a computer vision problem. By training Convolutional Autoencoders on normal operating sounds, the model identifies potential mechanical failures through reconstruction error analysis—triggering alerts before critical breakdowns occur.