About

Mohammad S. Obaidat is a prolific researcher whose work spans the intersections of Internet of Things (IoT), blockchain security, cloud robotics, and intelligent healthcare systems. With a career marked by consistent innovation across emerging technologies, Obaidat has made significant strides in advancing secure, reliable, and intelligent networked environments. Among his most impactful contributions is his pioneering research on fault diagnosis in industrial robotics using IoRT and hybrid deep learning techniques, which has already garnered 125 citations since its 2024 publication — a testament to its immediate relevance to the field. His blockchain-driven intelligent telesurgery framework, earning 70 citations, demonstrates his forward-thinking approach to integrating 6G, tactile internet, and distributed ledger technologies to revolutionize remote healthcare delivery. Obaidat's research portfolio also reflects a deep commitment to cybersecurity, evidenced by his work on blockchain-based mutual authentication for decentralized healthcare and malware detection protocols for industrial IoT environments. His contributions to cloud robotic networks, including energy-efficient computation offloading and QoS-driven resource allocation, further highlight his multidisciplinary reach. From precision agriculture sensor systems to underwater wireless networks, Obaidat's work consistently bridges theoretical rigor with real-world applications, making him an essential reference for researchers navigating the convergence of connectivity, automation, and security.

Research Focus

Key Achievements

9
H-Index
18
Papers
430
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Online Fault Diagnosis of Industrial Robot Using IoRT and Hybrid Deep Learning Techniques: An Experimental Approach
125 citations · 2024
📈 Most Prolific Year: 2024 (4 Papers)
🤝 Key Collaborators: 44
🏛 Institutions: University of Jordan, University of Science and Technology Beijing, University of Sharjah, The University of Texas of the Permian Basin

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago