Takuya Sunakawa

Papers

Total Citations

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About

Takuya Sunakawa’s research lies at the intersection of ubiquitous computing, intelligent robotics, and smart home systems, with a focus on practical sensing and human-object interaction. His most cited work, “ZigBee based wireless indoor localization with sensor placement optimization towards practical home sensing” (2016, 13 citations), addresses a key challenge in indoor localization: optimizing sensor placement to improve accuracy for real-world home environments. By leveraging statistical machine learning and wireless communication technologies, Sunakawa’s approach enhances the reliability of location-aware systems, supporting applications in robotics and ambient intelligence. In another notable contribution, “TansuBot: A drawer-type storage system for supporting object search with contents’ photos and usage histories” (2013, 5 citations), he tackles the everyday problem of locating household objects. This system integrates a smart device interface with a physical drawer, allowing users to review photos and usage logs to quickly find stored items. Sunakawa’s work demonstrates a thoughtful blend of hardware design and user-centered software, aiming to reduce non-creative search tasks at home. Though his citation counts are modest, his contributions offer practical, scalable solutions for smart living environments, making his research relevant for students and engineers interested in IoT, human-robot interaction, and context-aware systems.