Homeowners may spend up to ∼$375 to diagnose their damaged rooftop solar PV systems. Thus, recently, there is a rising interest to inspect potential damage on solar PV arrays automatically and passively. Unfortunately, current approaches may not reliably distinguish solar PV array damage from other degradation (e.g., shading, dust, snow). To address this issue, we design a new system - -SolarDiagnostics that can automatically detect and profile damages on rooftop solar PV arrays using their rooftop images with a lower cost. We evaluate SolarDiagnostics by building a lower cost (∼$35) prototype and using 60,000 damaged solar PV array images. We find that pre-trained SolarDiagnostics is able to detect damaged solar PV arrays with a Matthews Correlation Coefficient of 0.95.
