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KAKEN_19H04099seika.pdf
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クラウド側とエッジ側機器の動的な協調に基づく自律分散共進化AI基盤技術の研究開発
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クラウドガワ ト エッジガワ キキ ノ ドウテキナ キョウチョウ ニ モトズク ジリツ ブンサン キョウシンカ AI キバン ギジュツ ノ ケンキュウ カイハツ
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Kuraudogawa to ejjigawa kiki no dōtekina kyōchō ni motozuku jiritsu bunsan kyōshinka AI kiban gijutsu no kenkyū kaihatsu
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Research and development of autonomous distributed co-evolutionary AI infrastructure technology based on dynamic coordination between cloud-side and edge-side devices
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中澤, 仁
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ナカザワ, ジン
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Nakazawa, Jin
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慶應義塾大学・環境情報学部 (藤沢) ・教授
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Research team head
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科研費研究者番号 : 80365486
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宮前 (岸野), 泰恵
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ミヤマエ (キシノ), ヤスエ
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Kishino, Yasue
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日本電信電話株式会社NTTコミュニケーション科学基礎研究所・協創情報研究部・主任研究員
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Research team member
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科研費研究者番号 : 20466410
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須山, 敬之
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スヤマ, タカユキ
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Suyama, Takayuki
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大阪工業大学・情報科学部・教授
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Research team member
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科研費研究者番号 : 80396134
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2023
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科学研究費補助金研究成果報告書
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2022
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クラウド側とエッジ側機器の動的な協調に基づく自律分散共進化AI基盤技術を構築した。同基盤技術では、深層学習モデルをエッジ側で駆動して動画像からリアルタイムに特定の物体を検出し、検出結果を出力可能である。このためにまず知的処理をエッジ側のセンサと計算機内でリアルタイムに自律分散して実行する。また、エッジ側での知的センシングを常に最適な状態に保つために、クラウド側との協調によるエッジ側を最適化する。これらにより、実空間内の多数のエッジ側センサノードが新たなモデルに基づくセンシングを行い、またクラウド側計算機はそのセンシング結果を用いて次世代の学習を行ってその結果をエッジ側へ転移可能となった。
Autonomous distributed co-evolutional AI infrastructure technology based on dynamic coordination between cloud-side and edge-side devices has been developed. This platform technology can detect specific objects from video images in real time by driving deep learning models at the edge and output the detection results. For this purpose, intelligent processing is first performed autonomously and distributed in real time within the sensor and computer on the edge side. In addition, to keep the intelligent sensing at the edge in an optimal state at all times, the edge side is optimized in cooperation with the cloud side. As a result, a large number of sensor nodes at the edge in real space perform sensing based on a new model, and the cloud-side computer can use the sensing results to learn the next generation and transfer the results to the edge side.
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研究種目 : 基盤研究 (B) (一般)
研究期間 : 2019～2022
課題番号 : 19H04099
研究分野 : 情報学
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