Rapid Digital Twin Cities Construction Project (Digital City)

1.1 Data Processing Infrastructure (Cloud, Large-Scale Data Processing Systems, Machine Learning Frameworks, Databases, Data Structure)
1.2 Cyber-Physical System (Sensor Network, IoT, Real-time Data Processing)
1.4 Visualization, Visual Analytics
1.5 Data Sharing, Data Co-Creation (Search, Data Linkage, Data Authoring. Meta-data Creating)
2.4 Smart City (Transportation, Town Planning, Living Environment, Crime Prevention)
2.5 Geospatial Information (Remote Sensing, People Flow)
2.6 Market of Data (Data Trading, Data-driven Value Co-Creation)
2.7 Disaster Prevention, Reconstruction (Earthquake, Tsunami, Volcano, Meteorology, Flood, Natural Disaster)
2.12 Social Science (Digital Archive, Social Investigation, Sociology, Economics, Social Informatics)
2.13 Public Policy, Economy (Policy Evaluation, Finance, Real Estate, Insurance)
2.15 Humanities（Religion, Literature, Linguistics, History, Archeology, Cultural Anthropology, Geography, Area Studies, Tourism, Museology, Art, etc)

Yoshihide Sekimoto

Center for Spatial Information Science

Professor Project Professor, Institute of Industrial Science

The Digital City project aims to develop a digital twin city environment by combining a 3-D urban environment dataset and visualization environment with local digital city activities with the objective of constructing a hot standby environment. The progress was demonstrated through a series of events organized in Susono City, Shizuoka, and Chiba City, Chiba during January, 2021.

Digital Susono interface
Sekimoto Laboratory, University of Tokyo

Digital Chiba Interface
Sekimoto Laboratory, University of Tokyo

Research collaborators

Association for Promotion of Infrastructure Geospatial Information Distribution

Related publications

Seto, T., Sekimoto, Y., Asahi, K. and Endo, T.: Constructing a Digital City on a Web-3D Platform: Simultaneous and consistent generation of metadata and tile data from a multi-source raw dataset. Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Advances on Resilient and Intelligent Cities (ARIC'20), 9 pages, 2020.11

Seto, T., Urban Space Datalization and Geospatial Information, The Journal of the Institute of Electrical Engineers of Japan, 141 (1), pp.23-26, 2021.01. (In Japanese)

Maeda, H., Sekimoto, Y., Seto, T., Kashiyama, T., and Omata, H., A framework for Clack detection and maintenance criteria extraction using machine learning and smartphone camera,JSTE Journal of Traffic Engineering, 2018, Vol. 4, No. 3, p. A_1-A_8 (In Japanese)