End User
ELES
Description
This service enables processing and analysis of drone-acquired imagery using AI to detect transmission system assets, support inventory identification, and identify potential physical anomalies. By automating visual inspection of power lines and towers, the service reduces the workload of field experts who currently perform inspections manually and enhances asset management databases with detected inventory data.
Core Capabilities
Monitoring & Anomaly Detection
Business Need
Physical inspection of transmission line infrastructure is currently performed manually by field experts walking along corridors, a process that is time-intensive, operationally costly, and limited in coverage frequency. Detecting early-stage physical anomalies or degradation before they cause outages requires more frequent and detailed inspection than manual methods can sustain. Drone-based AI inspection dramatically increases inspection coverage and frequency while reducing operational costs.
Key Performance Indicators
Classification accuracy: correct detection and classification of physical anomalies or degradation
Number of newly detected physical anomalies not previously captured by manual inspection
Number of detected assets/inventory items identified within imagery
Image quality feedback rate: proportion of images flagged as insufficient for reliable processing
Data Provided
Structured outputs per analysed image: identified inventory references with location information
Image-based localisation of detected physical anomalies or degradation
Classification of findings by anomaly type
Note: Service for internal ELES use only; representative datasets may be made available to EnerTEF stakeholders under controlled access
TEF
TEF TSO