Extraction of tacit knowledge by multi-layered mining combining collective intelligence method and mathematical modeling method

2016 Fiscal Year Final Research Report

• Project/Area Number: 26240032
• Research Category: Grant-in-Aid for Scientific Research (A)
• Allocation Type: Single-year Grants
• Section: 一般
• Research Field: Intelligent informatics
• Research Institution: The University of Electro-Communications
• Principal Investigator: Kurihara Satoshi 電気通信大学, 大学院情報理工学研究科, 教授 (30397658)
• Co-Investigator(Kenkyū-buntansha): 淺井 義之 沖縄科学技術大学院大学, その他の研究科, 研究員 (00415639) ; 鳥海 不二夫 東京大学, 工学(系)研究科(研究院), 准教授 (30377775) ; 我妻 広明 九州工業大学, 生命体工学研究科(研究院), 准教授 (60392180) ; 諏訪 博彦 奈良先端科学技術大学院大学, 情報科学研究科, 助教 (70447580) ; 菊池 康紀 東京大学, 学内共同利用施設等, 講師 (70545649) ; 篠田 孝祐 電気通信大学, その他の研究科, 助教 (90533191)
• Project Period (FY): 2014-04-01 – 2017-03-31
• Keywords: 農作業暗黙知 / ビッグデータマイニング / データサイエンス / 視線計測 / 熟練農家 / パタンマイニング / 気づき / 環境データ

Outline of Final Research Achievements

This research is aimed at extracting tacit knowledge of skilled farmers with high added value vegetable and fruit production know-how from big data composed of various data such as agricultural workers' actions, agricultural crop conditions, soil, temperature and weather.
As result, we were also working on extracting tacit knowledge from agricultural work data, predicting growth of agricultural crops from environmental data, and extracting tacit knowledge by gaze measurement, and we were able to actually discover differences in working style between experienced farmers and general farmers .

Free Research Field

人工知能，複雑ネットワーク，ユビキタスコンピューティング