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March 3, 2026
Autonomous UAV-based pipeline monitoring with YOLOv8 for real-time surface anomaly detection
MS
Muhammad Sheraz
ZH
Zahid Hussain
Showa University
SA
Saqlain Abbas
Showa University
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Key Points
Surface anomalies were detected in real-time with high accuracy using YOLOv8.
Key evidence included a precision of 92% in identifying various surface irregularities during tests.
An automated system using UAVs and YOLOv8 transformed monitoring efficiency compared to traditional methods.
This analysis supports enhanced pipeline safety, calling for wider application of UAV technology in industrial inspections.
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Cite This Study
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Sheraz et al. (Wed,) studied this question.
synapsesocial.com/papers/69a75cefc6e9836116a2639c
https://doi.org/https://doi.org/10.1016/j.measurement.2026.120624
Autonomous UAV-based pipeline monitoring with YOLOv8 for real-time surface anomaly detection | Synapse