Our research concerns 2 topics. First is to consider the support of the creative social activities, which utilize network, and the creation of new application. The other is to operate the network element, system technology and system development of various applications
Prospective students and researchers are always welcome to join our team.
Wataru Sasaki, Yuuki Nishiyama, Tadashi Okoshi, Jin Nakazawa: Investigating the occurrence of selfie-based emotional contagion over social network. In: Social Network Analysis and Mining, 11 , pp. 8, 2021, ISSN: 1869-5450.
Our paper “SelfGuard: Semi-Automated Activity Tracking for Enhancing Self-Protection against the COVID-19 Pandemic” is accepted by ACM SenSys2020 (COVID-19 Pandemic Response session). Yuuki Nishiyama (Assistant Professor), Takuro Yonezawa (Associate Professor from Nagoya University), and Kaoru Sezaki (Professor) wrote the paper.
Yuuki Nishiyama, Takuro Yonezawa, Kaoru Sezaki: SelfGuard: Semi-Automated Activity Tracking for Enhancing Self-Protection against the COVID-19 Pandemic. In: the 18th ACM Conference on Embedded Networked Sensor Systems (SenSys '20), COVID-19 Pandemic Response, Virtual Event, Japan , pp. 780–781, Association for Computing Machinery, New York, NY, USA, 2020, ISBN: 978-1-4503-7590-0/20/11.
Abstract
Contagious diseases like COVID-19 spread periodically and threaten our lives. Self-protection, such as washing hands, wearing a mask, and staying home, are simple and practical solutions to safeguard against these diseases. Most governments and health departments recommend that people maintain self-protection. Although continuous self-protection effectively prevents the spread of infection, only the intent to self-protect is unsustainable in the long term. In this study, we design, develop, and deploy an application to track users' daily activities semi-automatically and enhance self-protection behavior using mobile sensing and gamified feedback techniques. Currently, more than 324 people have installed the app via AppStore, and 52 users have shared their activity data to our research group.
Detect environment and human/people behavior by using hardware, software and human sensors on smartphones/wearable devices
Wireless Sensor Network
Optimization of wireless sensor network routing, computational processing, and power consumption through simulation and real-world measurement experiments
Spatical Analytics
Collection and analysis of location information and related data. Mainly, assessing and predicting the impact of MaaS on cities.
Behavior Change & Well-being
Context awareness and information providing methods for promoting human behavioral change and realizing Well-being by using information technologies