Solar Panels Inspection Using Drones

Ongoing maintenance and malfunction detection.

DRL Team
AI R&D Center
15 May 2020
5 min read
Solar Panels Inspection Using Drones


  • With the solar industry growing exponentially, the need for solar panels ongoing maintenance and malfunction detection surges proportionally. As solar panels break frequently, plant and facility managers are seeking efficient, safe, and inexpensive ways to detect solar panel faults. Drones like no other technology offer an efficient solution for panel inspection.
  • While many market players offer solar panels inspection, only a handful process video from drones and provide reports on breakdowns, coordinates, energy and money losses. Our client's goal is to build the first full-cycle solar panel inspection service.
  • Together with our client, we have built the first full-cycle solution powered by Computer Vision technologies enabling timely defect detection and functioning analytics for solar panels providers and customers.

Tech Stack



1 week
Data Labelling and Processing
Data Engineer
1 week
Solution Architecture Design
Solution Architect
2 weeks
Hypothesis Generation & Validation
Deep Learning Researcher
1 week
Architecture Modelling
Deep Learning Researcher
3 weeks
Training & Tuning Cycle pt.1
Deep Learning Researcher
4 weeks
Training & Tuning Cycle pt.2
Deep Learning Researcher
3 weeks
Video Streaming Backend Development
Backend Developer
Data Engineer
3 weeks
Web Platform Development
Backend Developer
Frontend Developer
1 week
Integration & Deployment
Dev Ops

Tech Challenge

  • Real-time binary segmentation of solar panels from the video.
  • Choosing the "moment" of the panel classification at the right angle.
  • Mapping the corresponding panel to its position on the map.
  • Creation of interactive report with different view parameters.
  • Creation of corresponding .kmz file with coordinates mapping.
  • Creation of energy and money loss analytics based on classification results.


  • Segmentation and tracking of panels based on TRGB video data.
  • Optimization of processing with TensorRT.
  • Using U-net for binary segmentation.


  • data root labs have built a web service that allows performing one-time and routine drone inspections.
  • The service also makes it possible to download and upload external video for analysis.
  • Based on the video from the drones, users receive a detailed interactive report in .kmz format as well as an analytical summary highlighting potential defects, energy and money losses.

Have an idea? Let's discuss!

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Yuliya Sychikova
Yuliya Sychikova
COO @ DataRoot Labs
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