Assessing Precision of Cloud Robotics Device by Visualization for Non-Network Expert


연구 분야: Artificial Intelligence



학회: 2024 IEEE 13th Global Conference on Consumer Electronics (GCCE)


초록

A network is a black box for its users. We can use many metrics to evaluate the network, but for application developers, it is important that the application performs with the desired accuracy, and that understanding the relationship between application behavior and network performance is not a straight forwarding task. In this paper, we developed a tool to visualize the behavior of robotics devices for network-based cloud robotics. This tool has enabled us to apply approaches with similar roles to Mean Opinion Score (MOS) for assessing underlying networks for cloud robotics.


Author Profile
Arata Koike

Faculty of Humanities Tokyo Kasei University Tokyo Japan

Japan
Author Profile
Yoshiko Sueda

School of Information Science Meisei University Tokyo Japan

Japan

📄 논문 정보

발행 연도 2024년
인용수 18
출판 국가 Japan
사이트 IEEE
좋아요 수 0

연관 논문 목록 (119건)