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Case Study

AI-Powered Detection of Mismatched Solar Modules

How drone imagery and AI defect detection identified mismatched PV modules at a Welsh solar farm — replacing days of manual inspection with fast, objective, engineer-ready results.

4
Mismatched Modules Found
AI
Powered Detection
0
Days Downtime

Client Challenge

A solar farm required identification of mismatched PV modules — panels differing from neighbours, indicating incorrect replacements or mixed batches.

Our Approach

High-resolution drone imagery processed through AI-powered defect detection to automatically flag mismatched modules across the array.

Results

4 mismatched modules identified | GPS-located | Audit-ready PDF reports with severity classification.

The Challenge

Identifying Mismatched Modules Across a Large Array

A solar farm in South Wales required a detailed inspection to identify mismatched PV modules — panels that differ visibly from their neighbours, often indicating incorrect replacements, mixed product batches, or warranty-relevant installation errors.

A traditional ground-based approach would have required walking every row of the array, multiple days on site with subjective visual judgement, manual GPS logging, and a high risk of missed defects across thousands of near-identical panels.

The client needed fast, accurate, and auditable results to support remedial works and asset management decisions.

Our Approach

Drone Imagery Meets AI-Powered Detection

We deployed high-resolution drone imagery across the entire site and processed the capture data through Scopito's AI-powered defect detection platform, enabling automated identification of mismatched modules.

Key elements of the delivery:

  • Full aerial coverage captured by drone with georeferenced imagery
  • AI-based detection automatically flagging mismatched modules across the array
  • Each detection tagged with severity rating, classification, and GPS coordinates
  • No disruption to site operations during the inspection
  • Elimination of subjective human judgement from the detection process
Aerial image showing AI-detected mismatched modules highlighted with bounding boxes
AI-detected mismatched modules highlighted on aerial imagery
Wide aerial view of the solar array with markers showing detected mismatched modules
Site-wide panel map with detected issues marked across the array
Results

Precise, Actionable Findings

The AI processing identified 4 mismatched modules, all classified as Severity 3. The Scopito platform delivered structured severity overviews, annotated close-up imagery, precise GPS coordinates, and altitude and timestamp metadata for a complete audit trail.

Engineers could navigate directly to the affected modules using their phones — no searching, no interpretation.

Scopito defect report showing annotated module imagery with severity and classification tags
Scopito report output with severity classification and close-up imagery
Phone showing Google Maps navigation to a detected panel at the solar farm
Phone showing close-up detection view with metadata
Mobile navigation directly to detected modules using GPS coordinates
Key Benefits

What the Client Gained

Speed

AI detection completed in a fraction of the time a manual inspection would require.

Accuracy

Every flagged module backed by high-resolution imagery and GPS evidence.

Engineer Efficiency

Direct mobile navigation to each affected panel — no searching on site.

Audit-Ready Reporting

Structured PDF output with severity ratings, metadata, and annotated imagery.

Deliverables

What the Client Received

AI Defect Report

AI Defect Report

Structured PDF with severity ratings, annotated close-up imagery, and classification tags.

Site-Wide Panel Map

Site-Wide Panel Map

Full array map with markers showing detected mismatched modules and their locations.

Annotated Imagery

Annotated Imagery

High-resolution aerial images with AI bounding boxes highlighting each detection.

GPS Navigation

GPS Navigation

Direct mobile links to each affected panel for fast on-site engineer access.

Context

Why Mismatched Module Detection Matters

Mismatched modules are often nearly invisible from ground level, especially across large arrays. They're inconsistently recorded during manual inspections and can be indicative of wider quality control or warranty issues that require documentation.

By combining drone-captured imagery with AI-powered defect detection, we transform a slow, subjective task into a fast, objective, engineer-ready dataset. This project demonstrates how automated analysis can replace days of manual inspection with structured, audit-ready reports that support warranty claims and compliance requirements.

Need AI-Powered Inspection?

Get in touch with our team to discuss how drone-based AI analysis can support your solar asset management.