Artificial intelligence can identify landslides and other geological changes that threaten electricity transmission towers, potentially allowing operators to intervene before infrastructure fails. The findings come from a study published in the International Journal of Power and Energy Conversion.
The research demonstrates how machine learning algorithms can analyze terrain data to spot subtle ground movements near power lines. Early detection of such hazards could prevent costly outages and improve grid reliability in mountainous or unstable regions where towers are vulnerable.
Details on specific performance metrics or test results were not disclosed in the source material. The study provides proof that AI-based monitoring systems can detect geological risks that might go unnoticed by traditional inspection methods.
Utilities could integrate these AI tools into their maintenance workflows to prioritize inspections and repairs. Widespread adoption would depend on further validation and the cost of deploying such systems across large transmission networks.
The research adds to a growing body of work applying AI to infrastructure monitoring, though field trials and real-world deployment remain necessary to confirm scalability and reliability.