Mohamed M. Abdelsalam
Papers
2
Total Citations
34
H-Index
2
About
Mohamed M. Abdelsalam is a rising researcher at the forefront of the Internet of Robotic Things (IoRT) and intelligent robotic network optimization. His work focuses on solving critical challenges in autonomous systems, particularly the energy constraints and operational inefficiencies that limit real-world robotic deployments. In his most-cited paper, "Energy-efficient computation offloading using hybrid GA with PSO in internet of robotic things environment" (2023, 31 citations), Abdelsalam pioneered a novel hybrid genetic algorithm and particle swarm optimization approach. This work addresses the pressing need for smart connectivity and real-time communication in IoRT systems, demonstrating how intelligent computation offloading can dramatically reduce power consumption while maintaining performance. His subsequent research, "An effective robot selection and recharge scheduling approach for improving robotic networks performance" (2024), extends this work by tackling the practical challenges of managing mobile robot fleets, including power management and human-robot interaction delays. Abdelsalam’s contributions are particularly significant as they bridge the gap between theoretical optimization algorithms and practical robotic network management, offering tangible solutions for industries relying on autonomous systems. His work is already influencing how researchers approach energy-aware task allocation in distributed robotic environments, marking him as an emerging authority in IoRT and swarm robotics optimization.
Research Focus
Key Achievements
Top Papers
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