Ubiquitous Computing Systems

Research Staff

  • Professor Keiichi YASUMOTO

    Keiichi YASUMOTO

  • Associate Professor Hirohiko SUWA

    Associate Professor
    Hirohiko SUWA

  • Affiliate Associate Professor Manato FUJIMOTO

    Affiliate Associate Professor
    Manato FUJIMOTO

  • Assistant Professor  Yuki MATSUDA

    Assistant Professor
    Yuki MATSUDA

Research Areas

Ubiquitous computing systems utilize various smart devices including sensors and IoT devices in a harmonious manner and efficiently provide users with sophisticated services by recognizing real-world contexts. Our lab conducts data collection, data analysis, and application development for solving the various challenging issues of real world. The main themes are as follows:

Fig.1 Lab overview

Fig.1 Lab overview

Fig.2 Smart Home

Fig.2 Smart Home

Fig.3 Smart Life

Fig.3 Smart Life

Fig.4 Smart City

Fig.4 Smart City

Smart homes

  • Recognizing and predicting daily living activities
  • Elderly monitoring and anomaly detection systems
  • Energy-aware smart appliance control
  • Context-aware smart home services
  • Easy-to-deploy and user-friendly smart home kit

Smart life

  • Sport/exercise/workout sensing and coaching
  • Estimating health status/QoL including physiological and mental states
  • Smart office for improving work-engagement
  • Tailor-made IoT based human-computer interaction
  • IoT nudge for health behavior change

Smart city

  • Participatory sensing systems
  • Behavior change for smart community
  • Dynamic video curation for smart tourism
  • Edge/fog computing based IoT platform
  • Federated learning for sightseeing objects/scenes recognition

Key Features

We are conducting research using a smart home facility built within the university. This facility provides an actual home environment where various home appliances are deployed as in an ordinary household. In addition, this facility is equipped with wireless power meters, door sensors, and others. We are collecting data while people are actually living in this facility and develop various methods including activity recognition and automatic appliance control using the collected sensor data. We are also conducting research on smart life and smart cities through development of platforms for participatory sensing and IoT data processing as well as smart IoT devices including tiny all-in-one sensor boards and smart appliances.
Each student selects research topics according to his/her own interests through several brainstorming meetings with advisers. Advisers provide students with kind and careful direction to advance their research as well as suggestions to improve their programming, writing, and presentation skills. Students receive various opportunities to present their research results at domestic/international workshops and conferences.