COMPUTER VISION / PREDICTIVE MAINTENANCE / ANALYTICS & SMART MONITORING

Computer Vision: Thermography in Photovoltaic Installations Using Drones

Thermal vision that powers smarter maintenance.

Computer Vision Thermography

OBJECTIVE
Implement a scalable and efficient solution for detecting thermal anomalies in photovoltaic panels. The goal was to enhance maintenance workflows, ensure plant safety, and identify generation issues caused by defective or damaged cells.

SOLUTION
Thermal imaging technology was deployed via drones to capture infrared data across extensive solar fields. The analysis identified malfunctioning cells, faulty cabling, and overheating risks, supporting proactive maintenance and operational efficiency.

KEY ACTIONS
  • Equipped drones with high-resolution thermal cameras
  • Scheduled autonomous flights over photovoltaic arrays
  • Captured and analyzed thermal patterns to detect hot spots and anomalies
  • Integrated findings into maintenance protocols for panel replacement
  • Performed system testing and thermal diagnostics
TECHNOLOGIES
  • Thermal imaging cameras (infrared sensors)
  • Autonomous drones with GPS navigation
  • Flight planning and automation software
  • Computer vision algorithms for anomaly detection
  • Data visualization and thermal mapping tools

SAVINGS & BENEFITS
  • Reduced inspection time by over 70% compared to manual methods
  • Early detection of panel defects minimized energy loss
  • Improved safety by identifying overheating risks
  • Enhanced maintenance traceability and operational oversight
  • Higher accuracy and consistency in inspection processes