Tough Cyberphysical AI Research Center

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Research DivisionResearch Division

Social implementation of traffic flow control, infrastructure inspection
and assessment, and healthcare

Through development of tough algorithms and AI to detect and infer anomalies in healthcare, traffic, and infrastructures by way of learning, modeling, and databasing of the ordinaries based on comprehensive sensing and environmental data, we conduct social implementation of services that intervene and provide feedback to the real world.

Research Topics Division Head: Prof. Makoto Hisada

Infrastructure
Anomaly Detection

Implementation support for the developed technology and registration of collected information into database

Support for implementation and operation of the developed technologies and registration of collected information into database through the Tohoku Infrastructure Management Platform, which aims to extend infrastructure maintenance and management technologies through industry-academia-government collaboration.

Implementation Support of Advanced Technologies Organized Information Infrastructure
Anomaly Detection In Traffic And Logistics

Realization of advanced urban mobility management by integration, analysis, and visualization of sensor data and spatio-temporal information

  • Weather Disaster Risk SNS Disaster Area Image Traffic vehicle detectors and probes and GIS geographic information
    Aggregation, partitioning, compression, and transmission of a large amount of data
  • JOSE Japan-wide Orchestrated Smart / Sensor Environment NICT (National Institute of Information and Communications Technology)
    Synergy of traffic flow theory and machine learning Analysis and visualization through data fusion technology
  • Augmented Reality and Visualization
    Estimation of unobserved sections for alerting
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