Kyushu University [Shin'ichi Konomi (Professor) Faculty of Arts and Science, Division for Theoretical Natural Science]

Engaged in interdisciplinary research and education at Faculty of Arts and Science, School of Interdisciplinary Science and Innovation, and Graduate School of Information Science and Electrical Engineering.　Also, contributes to the design and the operations of the computational systems for supporting the education and learning at Kyushu University.

Research

Research Interests

Research on Human-Data Interaction
keyword : Data Science, Interaction, Network, Machine Learning, Recommendation, Ambient Intelligence, Privacy
2019.04.
Research and development of next-generation learning environments that leverage big data
keyword : Learning support, education support, learning analytics
2017.04.
Research and development of learning-support systems for adults of all ages including elderly people, with the aim to support their social participation and re-employment.
keyword : Learning support systems, learning analytics, recurrent education, adults at all ages
2017.11～2019.10.
Smartphone-based sensing of human behaviors
keyword : Smartphones, sensing, human behaviors
2017.04～2020.03.

Current and Past Project

Development of flexible techniques for collecting and updating trust networks, and its applications to information sharing systems in local communities
Proposes novel urban sensing method

Academic Activities

Books

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Norbert Streitz Shin'ichi Konomi, Distributed, Ambient and Pervasive Interactions: Understanding Humans. Proceedings of the 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Las Vegas, NV, USA, July 15-20, 2018, Part I, ISBN 978-3-319-91124-3, Springer, Berlin/Heidelberg, LNCS 10921, 469 pages., Springer, https://doi.org/10.1007/978-3-319-91125-0, 2018.07.

Norbert Streitz Shin’ichi Konomi, Distributed, Ambient and Pervasive Interactions: Technologies and Contexts. Proceedings of the 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Las Vegas, NV, USA, July 15-20, 2018, Part II, 2018, ISBN 978-3-319-91130-4, Springer, Berlin/Heidelberg, LNCS 10922, 381 pages., Springer, https://doi.org/10.1007/978-3-319-91131-1, 2018.07.

Reports

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Papers

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Shin'ichi Konomi Tomoyo Sasao Simo Hosio Kaoru Sezaki, Using Ambient WiFi Signals to Find Occupied and Vacant Houses in Local Communities, Journal of Ambient Intelligence and Humanized Computing, Springer., http://dx.doi.org/10.1007/s12652-018-0899-8, 10, 2, 779-789, 2018.12, In many countries, the population is either declining or rapidly concentrating in big cities, which causes problems in the form of vacant houses. It is often challenging to keep track of the locations and the conditions of vacant houses, and for example in Japan, costly manual field studies are employed to map the occupancy situation. In this paper, we discuss a technique to infer the locations of occupied and vacant houses based on ambient WiFi signals. Our technique collects Received Signal Strength Indicator (RSSI) data based on opportunistic smartphone sensing, constructs hybrid networks of WiFi access points, and analyzes their geospatial patterns based on statistical shape modeling. In situ experiments in two residential neighborhoods show that the proposed technique can successfully detect occupied houses and substantially outperform a simple triangulation-based method in one of the neighborhoods. We also argue that the proposed technique can significantly reduce the cost of field surveys to find vacant houses as the number of potential houses to be inspected decreases..

Tomoyo Sasao Shinichi Konomi Vassilis Kostakos Keisuke Kuribayashi Jorge Goncalves, Community Reminder
Participatory contextual reminder environments for local communities, International Journal of Human Computer Studies, 10.1016/j.ijhcs.2016.09.001, 102, 41-53, 2017.06, Many projects have looked at how communities can co-design shared online repositories, such as Wikimapia and Wikipedia. However, little work has examined how local communities can give advice and support to their members by creating context-aware reminders that may include advice, tips and small requests. We developed the Community Reminder environment, a smartphone-based platform that supports community members to design and use context-aware reminders. We have conducted a one-month field study of Community Reminder to crowdsource and deliver safety-relevant information in a local community. The results show the benefits of involving community members in reminder design and connecting different perspectives. We also show that the proposed approach can broaden participation in local communities..

Presentations

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1.	Shin'ichi Konomi, Learning Analytics for All: Opportunities and Challenges., The 7th Asian Workshop on Smart Sensor Systems, 2019.03.
2.	Shin'ichi Konomi, Technology-Enhanced Learning　Environments for Older Adults, Gerontechnology Symposium 2018, 2018.09.
3.	Shin'ichi Konomi Kohei Hatano Miyuki Inaba Misato Oi Tsuyoshi Okamoto Fumiya Okubo Atsushi Shimada Jingyun Wang Masanori Yamada Yuki Yamada, Towards Supporting Multigenerational Co-Creation and Social Activities: Extending Learning Analytics Platforms and Beyond, Distributed, Ambient, and Pervasive Interactions - Sixth International Conference, DAPI 2018, Held as Part of HCI Interational 2018. Proceedings. Lecture Notes in Computer Science, Springer., 2018.07.
4.	Simo Johannes Hosio Jaro Karppinen Esa Pekka Takala Jani Takatalo Jorge Goncalves Niels Van Berkel Shin'ichi Konomi Vassilis Kostakos, Crowdsourcing treatments for low back pain, 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018, 2018.04, Low back pain (LBP) is a globally common condition with no silver bullet solutions. Further, the lack of therapeutic consensus causes challenges in choosing suitable solutions to try. In this work, we crowdsourced knowledge bases on LBP treatments. The knowledge bases were used to rank and offer best-matching LBP treatments to end users. We collected two knowledge bases: one from clinical professionals and one from non-professionals. Our quantitative analysis revealed that non-professional end users perceived the best treatments by both groups as equally good. However, the worst treatments by nonprofessionals were clearly seen as inferior to the lowest ranking treatments by professionals. Certain treatments by professionals were also perceived significantly differently by non-professionals and professionals themselves. Professionals found our system handy for self-reflection and for educating new patients, while non-professionals appreciated the reliable decision support that also respected the non-professional opinion..

Membership in Academic Society

Association for Computing Machinery (ACM)
IEEE Computer Society
Information Processing Society of Japan (IPSJ)
The Institute of Electronics, Information, and Communication Engineers (IEICE)
The Database Society of Japan (DBSJ)
GIS Association of Japan

Awards

Best Short Paper Award of the 2017 European Conference on Ambient Intelligence (AmI 2017), 26-28,
April, 2017, Malaga, Spain: Shin’ichi Konomi, Tomoyo Sasao, Simo Hosio, Kaoru Sezaki, Exploring the
Use of Ambient WiFi Signals to Find Vacant Houses.

Educational

Educational Activities

Social

Professional and Outreach Activities

Engaged in research and development of learning-support systems in societies.

Unauthorized reprint of the contents of this database is prohibited.

https://kyushu-u.pure.elsevier.com/en/persons/shinichi-konomi Reseacher Profiling Tool Kyushu University Pure

http://lac.kyushu-u.ac.jp/e/Learning Analytics Center, Faculty of Arts and Science, Kyushu University .

http://hdi.ait.kyushu-u.ac.jp/Human Data Interaction Lab .

http://konomi.orgPersonal website .

https://kyushu-u.pure.elsevier.com/en/persons/shinichi-konomi
　Reseacher Profiling Tool　Kyushu University Pure

http://lac.kyushu-u.ac.jp/e/
Learning Analytics Center, Faculty of Arts and Science, Kyushu University .

http://hdi.ait.kyushu-u.ac.jp/
Human Data Interaction Lab .

http://konomi.org
Personal website .