AIP Network Lab

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AIP Acceleration Research

"AIP Acceleration Research" aims to maximize the research result as an AIP Network Laboratory by supporting newly-proposed research projects based on the excellent research results among the laboratory.

AIP Acceleration Research FY 2021

Wireless and wearable monitoring system with feedback function

Research Director

Kuniharu Takei Professor, Department of Physics and Electronics, Graduate School of Engineering, Osaka Metropolitan University

Collaborators

Shin Watanabe Associate Professor, Department of Emergency and Disester Medicine, School of Medicine, Juntendo University

Description

In this study, based on the technologies developed by PRESTO research, we develop a wearable, flexible sensor system with immediate alarm function as a wireless and feedback systems when the health condition suddenly changes. In addition to the developments of an integrated multimodal flexible sensor, relationship of correlation between several vital signals detected by the sensor system from skin surface is studied to determine the health conditions. With this correlation analyses from multiple datasets, more accurate feedback output signal can be realized. As the first proof-of-concepts for the future smart city and society, the sensor system is applied to monitor “heat stroke” and “remote health condition monitoring for infection”.

Advancing statistics towards reliable data science

Research Director

Koji Tsuda Professor, Graduate School of Frontier Sciences, The University of Tokyo

Collaborators

Kenji Kadomatsu Professor, Graduate School of Medicine, Nagoya University
Jun Sese President & CEO, Humanome Lab., Inc.
Ichiro Takeuchi Professor, Department of Physical Science and Engineering, Nagoya Institute of Technology

Description

In natural sciences, the data amount and the number of variables are beyond the level that traditional statistics can cope with. The credibility of statements in academic papers is not completely assured and reproducibity is often lost. In this study, we focus on selective inference, a new paradigm in statistics, and develop new and general methods of statistical tests, thereby aim to improve reliability of natural sciences. As a proof-of-concept, we apply our methods to health sciences and cancer sciences.

Studies of CPS platform to raise big-data-driven AI agriculture

Research Director

Masayuki Hirafuji Project professor, Institute for Sustainable Agro-ecosystem Services, Graduate School of Agricultural and Life Sciences, The University of Tokyo

Collaborators

Yasuhiro Usui Principal Scientist, Central Region Agricultural Research Center, National Agriculture and Food Research Organization

Description

We will develop a CPS (Cyber Physical System) platform to raise big-data-driven AI agriculture that can adapt rapidly to climate change and diverse consumers' needs. Specifically, we will develop a high-throughput data collection system for plant phenotyping and phytobiome dynamics consisted of plants, microorganisms and environment (= physical system) using AI, and a virtual spatial model of crops (= cyber system) with VR/AR/MR.

Development of Real-time AI Technologies for Event Analysis and Autonomous Operations

Research Director

Yasuko Matsubara Associate professor, Department of Translational Datability, The Institute of Scientific and Industrial Research, Osaka University

Description

The objective of this project is to develop fundamental technologies for the real-time modeling/forecasting of IoT big data streams, and autonomous operation AI software for the social good. This research project addresses two classes of tasks, namely, (1) development of real-time forecasting technologies for IoT big data streams. Here, we collect a wide variety of IoT big data from various domains, and forecast future social activities and events. The second goal is to (2) develop an autonomous operation AI software for IoT smart services, which makes real-time forecasts and provides instant advice or suggestions to help people make better decisions or optimize their social activities.