Kyushu University Academic Staff Educational and Research Activities Database
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Arakawa Yutaka Last modified date:2022.07.04

Graduate School
Undergraduate School

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SIG - Applied Human Information Systems (Arakawa-Mine-Fukushima Laboratory): For research on human information systems, we collaborate with Associate Professor Mine (recommendation systems, data analysis on education and ITS), and Associate Professor Fukushima (various information presentation technologies such as AR/VR and tactile sensation) . .
Academic Degree
Doctor of Engineering, Ph.D
Country of degree conferring institution (Overseas)
Field of Specialization
Sensors, IoT(Internet of Things), Activity recognition, Behavior Change Support System, ICT service, networking
ORCID(Open Researcher and Contributor ID)
Total Priod of education and research career in the foreign country
Outline Activities
Main research topics are kind of cyber-physical systems (CPS: Cyber-Physical Systems) that improves human life, where real-world sensing technology, cloud data processing technology, networking technology, and a variety of information technologies are combined dynamically. We call such a system as Humanophilic systems. Humanophilic is a coined word that combines the suffix “philic”, which means human-friendly. In the laboratory, we are focusing on the research on the behavior recognition of people using sensors (IoT) and machine learning (AI), and we are conducting a wide range of applications from the development of new sensors to the implementation of applications in order to realize the humanophilic systems.

In addition to the sensing of human external states (behavior and activity), the recognization of human internal states (emotions and stress) becomes a part of topics. We always consider and discuss what kind of sensors can be used, what kind of algorithms are most suitable. In recent years, as research ahead of behavior recognition, we start to focus on the behavior change support system (BCSS) because information technology can change our behavior better.
Research Interests
  • Behavior Change Support System
    keyword : Adaptive notification, Context-aware Dialog System, ICT-based gimmick
  • Learning Activity Recognition and Intervention
    keyword : Eye Tracking, Web control analytics, Confidence estimation
  • Internal State Sensing by sensors
    keyword : Stress Estimation, Emotion Estimation, Wearable
  • Energy Harvest Place Recognition
    keyword : Energy Harvesting, Solar, Localization
  • Activity Recognition by sensors
    keyword : Activity Recognition,Wearable
Academic Activities
1. Masaki Gogami, Yuki Matsuda, Yutaka Arakawa, Keiichi Yasumoto, Detection of Careless Responses in Online Surveys Using Answering Behavior on Smartphone, IEEE Access, 10.1109/access.2021.3069049, 9, 53205-53218, 2021.05.
2. Zhihua Zhang, Juliana Miehle, Yuki Matsuda, Manato Fujimoto, Yutaka Arakawa, Keiichi Yasumoto, Wolfgang Minker, Exploring the Impacts of Elaborateness and Indirectness in a Behavior Change Support System, IEEE Access, 10.1109/access.2021.3079473, 9, 74778-74788, 2021.05.
3. Mohamed A. Abdelwahab, Shizuo Kaji, Maiya Hori, Shigeru Takano, Yutaka Arakawa, Rin-Ichiro Taniguchi, Measuring “Nigiwai” From Pedestrian Movement, IEEE Access, 10.1109/ACCESS.2021.3056698, 9, 24859-24871, 2021.02, The analysis of the movement of people in a shopping area with the aim of improving marketing is an important research topic. Many conventional methods are dependent on the density of people in the area, which is easily estimated by counting the people entering or exiting the area. However, a high density does not always mean an increase in activity, as certain people are simply passing the area at a given time. The primary goal of this study was to introduce a set of indicators for measuring the bustle of the area, which we call 'Nigiwai,' from pedestrian movement by using an analogy from classical kinematics. Such indicators can be used to measure the impact of promotional events and to optimize the design of the area. Our novel indicators were evaluated with simulated pedestrian scenarios and were demonstrated to distinguish shopping scenarios from those in which people move around without shopping successfully, even when the latter scenarios had much higher densities. The indicators were computed solely from the pedestrian trajectory, which can easily be obtained from ordinary sensors using deep learning-based techniques. As a demonstration with real data, we applied our method to a video of a street and provided a visualization of the indicators..
4. Hiroyuki Miyagi, Masahiro Hayashitani, Daisuke Ishii, Yutaka Arakawa and Naoaki Yamanaka,, Advanced Wavelength Reservation Method based on Deadline-Aware Scheduling for Lambda Grid Networks, Journal of Lightwave Technology, Vol. 25, No. 10, pp. 2904-2910, 2007.10.
5. Yutaka Arakawa and Naoaki Yamanaka,, QoS Differentiation Scheme with Multiple Burst Transmission and Virtual Resource Reservation for Optical Burst Switching Networks, Journal of Optical Networking, Vol. 6, Issue. 8, pp. 1003-1013, 2007.07.
Works, Software and Database
1. .
Membership in Academic Society
  • IEEE
  • ACM
  • Association for Computing Machinery
  • The Institute of Electrical and Electronics Engineers, Inc.
  • Information Processing Society of Japan
  • The Institute of Electronics, Information and Communication Engineers
  • Honorable Mention Award
  • 山下記念研究賞
  • Ando Incentive Prize for the Study of Electronics
  • Mobile App Competition 2nd place
  • 長尾真記念特別賞
  • 研究者特別賞
  • Noguchi Award
  • センサアプリケーションアイデアコンテスト テクニカル賞
  • Best Demo Award
  • IPSJ/IEEE-CS Young Computer Researcher Award
  • Best Teaching Award
  • Best Demonstration Award
Educational Activities
- Special Lecture on Designing Social Infrastructure based on ICT
- Operating System