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Beyond the flight: simplifying solar defect detection with AI

Published in: Solar, Corporate Focus, Exclusive Articles

Beyond the flight: simplifying solar defect detection with AI image

SkyVisor explores how drone thermography and AI are redefining how solar inspections are performed, delivering faster results, sharper insights and greater operational control. But let’s be clear: this is not marketing hype. We’re talking about field-proven AI powered by deep learning algorithms that deliver measurable outcomes. Safeguarding your solar investment with scalable intelligence.

Today’s solar farms often reach several hundred megawatts, with some now approaching gigawatt scale. As site complexity increases, even small design or performance flaws can have outsized impacts, affecting millions of modules, and potentially costing thousands of euros over the asset’s lifespan.

To meet these challenges, many operators now rely on drones for inspections. Yet gathering aerial or thermal data alone is insufficient. The rise of drone inspections has created sprawling ‘data lakes’, massive collections of raw images with limited practical use unless processed.

Without a structured approach, these data lakes can become chaotic, full of duplicates, undocumented workflows, and fragmented information that hinder rather than help decision making.

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