Sami Moussiou

Papers

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About

Sami Moussiou is a researcher focused on advancing indoor localization technologies, with a particular emphasis on cost-effective, vision-based solutions. His most cited work, "Towards Low-Cost Indoor Localisation Using a Multi-camera System" (2019), addresses a critical challenge in pervasive computing: achieving accurate positioning in environments where GPS fails. By leveraging multi-camera setups, Moussiou explores how to reduce hardware expenses while maintaining reliable spatial awareness—a contribution that holds promise for applications in robotics, smart buildings, and augmented reality. Though his citation count is modest, with this paper garnering four citations, his work represents a foundational step toward democratizing indoor navigation systems. Moussiou’s research sits at the intersection of computer vision, sensor fusion, and embedded systems, aiming to bridge the gap between high-cost commercial solutions and accessible, scalable alternatives. His efforts are particularly notable for their practical orientation, targeting real-world deployment constraints such as power consumption and computational efficiency. As indoor localization continues to grow in importance for IoT and autonomous systems, Moussiou’s contributions offer a valuable blueprint for future low-cost, multi-camera architectures.