JST Strategic Basic Research Programs CREST

A Platform for Digitalizing Knowledge of Regional Communities

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JST CREST(Strategic Basic Research Programs)
Creation of System Software for Society 5.0 by Integrating Fundamental Theories and System Platform Technologies

Abstract

In this research, we aim to digitial transformation ("DX") the "knowledge" and "data" of local communities, securely share, and utilize them in the Society 5.0 era. We are designing and developing the foundational software "TASK/OS5" for this purpose, exploring the information and communication technologies necessary for its realization.
Specifically, we are constructing methodologies for safely utilizing data and AI models, including "personal data" obtained in individual regions, in other regions. We will formally demonstrate the security of these methodologies. Additionally, we seek to implement features that make it easier for local seniors to participate in the system. Through demonstration experiments in disaster response and traffic improvement in the region, we will showcase the effectiveness of these methodologies.

What is JST CREST?

This is a network-based (team-based) research aimed at generating outstanding results that contribute to scientific and technological innovation.
https://www.jst.go.jp/kisoken/crest/en/about/index.html

Reseach Area

[S5 Infrastructure Software] Creation of foundational software for Society 5.0 through the fusion of fundamental theory and system infrastructure technology (Research Supervisor: Professor Toshio Okabe, Kyoto University).
https://www.jst.go.jp/kisoken/crest/en/research_area/ongoing/area2021-2.html

Members

Project Leader: Hirozumu Yamaguchi

(Professor, Graduate School of Information Science, The University of Osaka, RIKEN Center for Computational Science)

Specialization:

IoT/Cyber-Physical Systems (Human location behavior sensing, wireless communication and optimization, advanced traffic systems, stream processing, distributed AI, spatial computing, etc.)

Homepage:

https://mc.net.ist.osaka-u.ac.jp/people/h-yamagu/

Group Members:

Atsuo Kishimoto: Professor, Data Ability Frontier Organization, The University of Osaka
Akira Uchiyama: Associate Professor, Graduate School of Information Science, The University of Osaka
Akihiro Hiromori: Associate Professor (Concurrent), Graduate School of Information Science, The University of Osaka
Mineo Takai: Visiting Associate Professor, Graduate School of Information Science, The University of Osaka
Teruhiro Mizumoto: Associate Professor, Faculty of Information Science, Chiba Institute of Technology
Tatsuya Amano: Assistant Professor, Graduate School of Information Science, The University of Osaka
Hiroki Yoshikawa: Lecturer, Faculty of Engineering, Kyoto Tachibana University
Rizk Hamada: Associate Professor, Graduate School of Information Science, The University of Osaka
Viktor Erdélyi: Lecturer, Faculty of Digital Media, Kyoto Tachibana University
Manas Kala: Special Appointed Assistant Professor, Graduate School of Information Science, The University of Osaka
Makoto Kudo: Special Appointed Researcher, Graduate School of Information Science, The University of Osaka
Aidana Baimbetova: Special Appointed Researcher, Graduate School of Information Science, The University of Osaka
Fukuharu Tanaka: RIKEN Center for Computational Science, Visiting Researcher at The University of Osaka
Haruki Yonekura: Information Networking, Doctoral Program, Graduate School of Information Science, The University of Osaka
Ren Oseki: Information Networking, Doctoral Program, Graduate School of Information Science, The University of Osaka
Riku Nakao: Information Networking, Doctoral Program, Graduate School of Information Science, The University of Osaka

Keishin Inaba

(Professor, The University of Osaka, Graduate School of Human Sciences)

Specialization:

Symbiotic Studies / Altruism / Disaster Prevention and Cooperation in Times of Disaster / Evacuation Shelter Information / Disaster Reduction through Religious Facilities (Temples, Shrines, etc.) and Science and Technology / Civil Society Theory / Religion as Social Capital / Social Contributions of Religion

Homepage:

http://altruism.blog56.fc2.com/blog-entry-288.html

Group Members:

Ryo Kawabata: Professor, The University of Osaka, Graduate School of Human Sciences
Wenjie Wang: Assistant Professor, The University of Osaka, Graduate School of Human Sciences
Seiichiro Kojima: Representative Director, General Incorporated Association Community Information Co-creation Center
Eiichiro Mine: Vice Chairman, General Incorporated Association Community Information Co-creation Center
Hironobu Teramoto: Executive Director, Non-Profit Organization Japan Disaster Relief Volunteer Network
Ichiging Shen: Researcher, The University of Osaka, Graduate School of Human Sciences
Ziyun Chen: Doctoral Program, The University of Osaka, Graduate School of Human Sciences
Mengying Zhao: Doctoral Program, The University of Osaka, Graduate School of Human Sciences

Keita Arai

(Associate Professor, Faculty of Economics, Kinki University)

Specialization:

Regional Economic Analysis / Measurement of Spillover Effects / Evaluation of Transportation Policies in Remote Islands / Happiness Surveys / Productivity Effects and Spillover / Social Capital Development / Evaluation of Promotion and Development Plans, etc.

Homepage:

https://research.kindai.ac.jp/profile/ja.3e30c0f0d0b58263.html#URL

Group Members:

Naoki Matsuda: EXA Innovation Studio IT Director
Kristian Tosa: Lecturer, Technical University of Cluj Napoca
Elodie Castex: Professor, Université de Lille

Kentaro Yano

(Yomiuri Telecasting Corporation, Digital News Department, Chief Expert and DX Promotion Division)

Work Package:

Utilization of Digital Television

Homepage:

https://www.ytv.co.jp/index.html

Group Members:

Yuki Matsuda: Yomiuri Telecasting Corporation, Content Strategy Bureau, Data Management Department

Research Subject

The concept of "Smart City" initially envisioned the enhancement of urban environments and the construction of futuristic cities. However, the Smart City concept promoted by Society 5.0 and Super City initiatives fundamentally focuses on revitalizing and coordinating local communities. In the Smart City public-private partnership platform, desirable forms of inter-regional collaboration and the necessity of data utilization between cities are emphasized. The introduction of Urban Operating Systems (City OS), which serves as a data collaboration infrastructure, is a key priority task to achieve this.
 
The City OS aggregates various sensors, cameras, administrative data, and other resources from regions, municipalities, and the private sector. By facilitating service and data collaboration, it serves as a foundation to realize diverse applications such as disaster prevention, safety, security, and transportation. Noteworthy platforms in this context include FIWARE and the Osaka Wide-Area Data Collaboration Platform (ORDEN).
 
The current Urban Operating System (OS) is designed with the collaboration of local governments, companies, research institutions, etc., in mind, particularly in fields such as energy, transportation, healthcare, finance, telecommunications, and education. It serves as a foundation that facilitates the accumulation of vast amounts of data, enabling the construction of applications for AI analysis and utilization. Consequently, with the proliferation of Urban OS, a substantial amount of AI is expected to be generated from the extensively collected data.
Aligned with the principles of a Smart City, it is envisioned that such artificial intelligence should be leveraged beyond individual regions. In the not-too-distant future, it is hoped that local governments and communities will pool their artificial intelligence resources, fostering a collaborative approach to co-create a new society.
 
An important challenge in this context is privacy and security. For instance, training data for machine learning models that optimize local transportation may contain personal data such as residential locations and travel histories, making it unsuitable for straightforward sharing as a dataset. Machine learning models serve as query engines for datasets, and it is crucial to ensure the safety of outputs related to personal data.
 
In this research, we aim to digitize the knowledge of local communities and develop the S5 foundation software TASK/OS5 (Transformation, Adaptation, and Sharing of Knowledge for Open Society 5.0) to securely share this knowledge. We will transfer data and machine learning models with "local dependencies," obtained in individual regions, to a secured form before sharing. By formally demonstrating, through number theory, that region-specific models or data posing risks of individual identification cannot be obtained from the secured versions, we will construct a methodology for utilizing data and models, including personal data, in a secure manner.

Publications

Media Coverage