Image Captured and Module Defects Recognized by Ai
With AeroOwl and InsightMind, image data collected from sites pushes through deep learning algorithms to autoidentify defects (eg. hotspot, microcrack, obstructions)
Tri-Spectral Image Defects Marking and Module Rati
Based on the visible, infrared and nearinfrared image comparison and health rating system. Modules are graded into different class
Module Life Expectancy and Asset Valuation
By integrating power generation data with module health classification,the system formulates maintenance plan and evaluates asset value
Power Generation and O&M Cost Forecasting in Ope
Leveraging big data and machine learning, TyShine dynamically adjusts parameters by integrating laboratory and real experience data to analyze O&M costs