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About

Atushi Toyama is a researcher focused on advancing wireless mesh networks (WMNs) through the innovative use of mobile robotics. His work centers on the development and optimization of Moving Omnidirectional Access Point (MOAP) robots—autonomous platforms that enhance network coverage and connectivity in dynamic environments. Toyama’s key contributions include the design and implementation of a real-time indoor position detecting system that leverages mean BLE RSSI to track moving MOAP robots, enabling precise localization for adaptive network management. He has also developed control interfaces that allow for seamless robot operation, bridging hardware and software for practical deployment. His research on determining the optimal number of MOAP robots in a WMN, using Elbow and Silhouette theories, provides a data-driven framework for network scalability and efficiency. With his most-cited papers accumulating over 30 citations, Toyama’s work is recognized for its practical impact on robotics-assisted wireless communication. His achievements demonstrate a strong commitment to solving real-world connectivity challenges, making his research valuable for students and engineers exploring the intersection of robotics, IoT, and network optimization.