| Project/Area Number |
16K00334
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Soft computing
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| Research Institution | The University of Aizu |
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Principal Investigator |
ZHAO QIANGFU 会津大学, コンピュータ理工学部, 教授 (90260421)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 人工知能 / 機械学習 / スマートホーム / 見守りシステム / プライバシー保護 / 在宅見守り / Sensor array / Smart home / Monitoring system / Privacy preserving / Senior care / Machine learning / センサーアレー / 在宅ケア / プライバシー配慮 / スマットホーム / 在宅介護 / ニューラルネットワーク / サポートベクトルマシン / 高齢者在宅ケア / センサーネットワーク |
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| Outline of Final Research Achievements |
In this research, we developed a monitoring system for taking care of elderly people who lives alone or lives with his/her spouse only. The main results obtained are as follows. 1) We have confirmed that a sparse sensor matrix can recognize the position and activity strength of the resident(s) very accurately, and we have proposed recognition methods based on machine learning; 2) We have proposed a video-based technique for automatic data labeling, and this technique makes it possible to recognition the position / activit strength in realtime; 3) To improve the usability of the sensor matrix, we have designed several sensor modules, and finally proposed a compact module that can be installed in a normal living room easily. Based on the results, we are going to commertialize the sensor module, and provide privacy preserving monitoring services.
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| Academic Significance and Societal Importance of the Research Achievements |
日本のような超高齢者社会において、効率よく高齢者を見守るためには、ＡＩが必要となる。本研究の成果は、プライバシーを守りながら、高齢者の日常活動をある程度見守ることができる。特に提案したセンサーモジュール（出願済み）は、通常の部屋に設置しやすい特徴がある。それを制御する機械学習モデルと合わせれば、近い将来の実用化が期待できる。
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