1. Problem: Fault localization in complex low-voltage networks is hindered by heterogeneous measurement data. 

2. Method & Results: An AI framework employs normalized feature extraction, PCA-based dimensionality reduction, and hyperparameter-optimized models trained through cross-validation. 

3. Goal: A long-term research effort enabling early fault identification, predictive maintenance, and enhanced network reliability.