Mohammed A. Al-Qarni

University of Jeddah

Papers

1

Total Citations

2

H-Index

1

About

Mohammed A. Al-Qarni’s research centers on the intersection of artificial intelligence, robotics, and cybersecurity, with a particular focus on secure IoT-enabled logistics and physical security systems. His work explores how encrypted AI frameworks can enhance robotic perception and package recognition in dynamic, high-speed environments—critical for modern video surveillance and automated logistics. Despite the retraction of his most-cited paper, “Improved encrypted AI robot for package recognition in IoT logistics environment” (2022, 2 citations), this study addressed the challenge of real-time image recognition in robotic applications, proposing in-built programming functions to secure package movement data. Al-Qarni’s contributions highlight the pressing need for robust encryption in AI-driven robotic systems, where speed and accuracy must coexist with data integrity. While his citation impact remains modest, his research underscores a growing niche in secure, intelligent automation—a field vital for smart warehouses and surveillance. His work serves as a stepping stone for future investigations into resilient AI architectures for physical security, encouraging researchers to refine encryption methods for real-world robotic deployment.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
(Retracted) Improved encrypted AI robot for package recognition in IoT logistics environment
2 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Jeddah

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago