Fahad Arif

American University of Sharjah

Papers

1

Total Citations

72

H-Index

1

About

Fahad Arif is a robotics researcher whose work lies at the intersection of mechanical design, sensor systems, and intelligent control, with a primary focus on pipeline inspection and leak detection for the oil and gas industry. His most-cited paper, "An In-Pipe Leak Detection Robot With a Neural-Network-Based Leak Verification System" (2018, 72 citations), introduces a custom-designed robot tailored for pipes of 0.203 meters in diameter. This robot integrates onboard pressure sensors for leak detection and features a propeller-driven propulsion system, but its key innovation is the use of a neural network to verify leaks, reducing false positives and improving reliability. Arif’s contributions advance the automation of critical infrastructure monitoring, offering a practical solution for early leak detection that can prevent environmental damage and economic loss. His work demonstrates a strong command of both hardware design and machine learning, making his research highly relevant for students and engineers interested in field robotics, smart sensing, and industrial automation.

Research Focus

Key Achievements

1
H-Index
1
Papers
72
Total Citations
72
Avg Citations/Paper
🏆 Most Cited Paper
An In-Pipe Leak Detection Robot With a Neural-Network-Based Leak Verification System
72 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: American University of Sharjah

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago