Ubiquitous Computing Systems

Research Staff

  • Prof. Keiichi Yasumoto

    Keiichi Yasumoto

  • Assoc.Prof. Hirohiko Suwa

    Hirohiko Suwa

  • Assist.Prof. Manato Fujimoto

    Manato Fujimoto

  • Assist.Prof. Yuki Matsuda

    Yuki Matsuda

  • Assist.Prof. Yugo Nakamura

    Yugo Nakamura

E-mail { yasumoto, h-suwa, manato, yukimat, y-nakamura }[at] is.naist.jp

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:

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.

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