Ahmed Arafa

Kuwait College of Science and Technology, University of Calgary

Papers

Total Citations

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About

Ahmed Arafa is a researcher whose work sits at the intersection of intelligent systems, human–machine interaction (HMI), and wireless sensor networks. His most cited paper, "Human–Machine Interaction Using Probabilistic Neural Network for Light Communication Systems" (2022, 13 citations), introduces a novel system that recognizes hand gestures by processing interrupted patterns of light within visible light communications (VLC). This work demonstrates a significant contribution to non-contact, vision-based control, offering a natural and efficient alternative for system interaction. Arafa’s earlier foundational research, "A Gaussian Model for Dead-Reckoning Mobile Sensor Position Error" (2010, 9 citations), addresses a critical challenge in wireless sensor networks: accurately estimating the position of mobile nodes. By modeling dead-reckoning errors with a Gaussian approach, his work provides a simple yet effective method to enhance network lifetime and reliability. Together, these contributions highlight Arafa’s ability to bridge theoretical modeling with practical, real-world applications in sensing and communication. His research not only advances the fields of optical wireless communication and sensor networks but also paves the way for more intuitive and robust human–machine interfaces, making him a notable figure in these converging domains.