Noha El Menbawy

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About

Noha El Menbawy is a leading researcher at the intersection of the Internet of Robotic Things (IoRT), fog computing, and energy-efficient systems. Her work focuses on the critical challenge of integrating autonomous robots with IoT infrastructure, ensuring intelligent connectivity while optimizing computational resources. Her most impactful contribution, "Energy-efficient computation offloading using hybrid GA with PSO in internet of robotic things environment" (2023, 31 citations), introduces a novel hybrid optimization algorithm that combines Genetic Algorithms (GA) with Particle Swarm Optimization (PSO) to minimize energy consumption during task offloading in IoRT environments—a breakthrough for real-time, battery-constrained robotic systems. El Menbawy further advanced the field with her foundational study "Studying and Analyzing the Fog-based Internet of Robotic Things" (2020, 8 citations), which systematically examines how fog computing can reduce latency and improve adaptability for robots facing unpredictable conditions. Her work is pivotal for enabling scalable, intelligent IoRT ecosystems, directly impacting applications from industrial automation to smart cities. By bridging theoretical frameworks with practical optimization, El Menbawy’s research continues to shape the future of autonomous, connected robotic systems.