Solar Panel Thermal Hotspot Inspection and Yield Optimization.

Dependency of drone-based inspections on wind conditions and inability of fixed cameras to cover millions of panels.

REF: ENR-01
Energy & Infrastructure

Operational
Mechanism.

Technical details of field integration, data flow, and autonomous decision algorithms.

Edge Hardware

FLIR Radiometric Thermal Camera
RTK-GPS Module
5G Edge Transmitter
LiDAR L2

Artificial Intelligence

Navigation (SLAM)

RTK-GPS assisted autonomous row-by-row driving between panel rows

Perception & Analysis

Thermal Anomaly Segmentation and PV Cell Hotspot Classification (YOLOv8-thermal)

Autonomous Workflow

The robot patrols autonomously along panel rows in the solar farm; positioned with centimeter precision via RTK-GPS.

The FLIR thermal camera scans each panel, segmenting hotspots, diode failures, and overheating zones caused by micro-cracks.

Detected anomalies are instantly transmitted to the SCADA system via API with panel coordinates, risk score, and thermal imagery.

Automatic work orders are opened for maintenance teams; yield loss (in kWh) of faulty panels is reported for prioritization.

Operational ROI.
Strategic Decision.

EXPECTED BALANCE IMPACT

Annual $58,000 energy yield gain and maintenance optimization. ROI: 2.9x | Payback: 1.5 Years.

Reduces the average 3-week late detection of faulty panels to hours; decreases yield loss by 12%.

Review Architecture
Plans with
Professional Presentation.

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