Sezaki & Nishiyama Laboratory
Institute of Industrial Science / Center for Spatial Information Science in The University of Tokyo
Institute of Industrial Science / Center for Spatial Information Science in The University of Tokyo
Yutong Feng, Akihito Taya, Yuuki Nishiyama, Kaoru Sezaki, Jun Liu
Compressive Detection of Stochastic Sparse Signals With Unknown Sparsity Degree Journal Article To Appear
In: IEEE Signal Processing Letters, pp. 1-5, 2023.
Abstract | BibTeX | Tags: | Links:
@article{10285002,
title = {Compressive Detection of Stochastic Sparse Signals With Unknown Sparsity Degree},
author = {Yutong Feng and Akihito Taya and Yuuki Nishiyama and Kaoru Sezaki and Jun Liu},
doi = {10.1109/LSP.2023.3324573},
year = {2023},
date = {2023-10-15},
urldate = {2023-10-15},
journal = {IEEE Signal Processing Letters},
pages = {1-5},
abstract = {In this letter, we investigate the problem of detecting compressed stochastic sparse signals with unknown sparsity degree under Bernoulli–Gaussian model. In addition to the generalized likelihood ratio test (GLRT) proposed in [1], the corresponding Rao test and Wald test are derived in this letter. By observing that obtaining their analytical performance is challenging, we further propose a new probability constraint estimator (PCE) of the unknown sparsity degree. Interestingly, by adopting the PCE, the GLRT, Rao and Wald tests are shown to be statistically equivalent and reduce to a new detector (i.e., the detector with PCE) with a simple structure. The analytical performance of the detector with PCE is thus derived, which is verified by Monte Carlo simulations. Finally, numerical experiments illustrate that the proposed Rao test and the detector with PCE outperform the original GLRT.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Shota Ono, Taku Yamazaki, Takumi Miyoshi, Akihito Taya, Yuuki Nishiyama, Kaoru Sezaki
AMoND: Area-Controlled Mobile Ad-hoc Networking with Digital Twin Journal Article Open Access
In: IEEE Access, pp. 1-1, 2023.
Abstract | BibTeX | Tags: | Links:
@article{10214544,
title = {AMoND: Area-Controlled Mobile Ad-hoc Networking with Digital Twin},
author = {Shota Ono and Taku Yamazaki and Takumi Miyoshi and Akihito Taya and Yuuki Nishiyama and Kaoru Sezaki},
doi = {10.1109/ACCESS.2023.3304374},
year = {2023},
date = {2023-08-01},
urldate = {2023-08-01},
journal = {IEEE Access},
pages = {1-1},
abstract = {Future smart cities are expected to provide intelligent services such as predictions, detections, and automation through digital twins. However, the creation of digital twins requires the processing of an enormous amount of data, thereby leading to an increase in mobile network traffic. This traffic is produced by applications in user devices and city services, which engage in local consumption at the city scale through sensor and camera devices using mobile networks. Such increased traffic can compromise the communication speed and stability. To alleviate this burden, traffic offloading becomes a crucial consideration in the beyond-5G era. This paper presents a scheme known as Area-Controlled Mobile Ad-Hoc Networking (AMoND). AMoND uses a hierarchical structure of a location layer and an ad-hoc layer to construct area-controlled mobile ad-hoc networks (MANETs) for mutual support of the digital twin and MANETs. AMoND effectively suppresses mobile network traffic by harnessing the digital twin to assist the MANETs during data collection for the digital twin construction. Importantly, the digital twin used in AMoND focuses on the management of node location information and does not need to reproduce the real space on a computer fully. AMoND is not dependent on a specific MANET protocol and can be used as an add-on. AMoND exhibits the ability to reduce traffic volumes by up to approximately 65%, while maintaining arrival rates that are comparable to existing MANET protocols under certain conditions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
王振博, 田谷昭仁, 加藤貴昭, 瀬崎薫, 西山勇毅
学生アスリートの行動データを用いた心身のストレス・回復状態の検知に向けて:行動データと心理尺度との関係分析 Conference To Appear
研究報告ユビキタスコンピューティングシステム(UBI), 2023-UBI-80 , 2023.
@conference{ubi80_alife,
title = {学生アスリートの行動データを用いた心身のストレス・回復状態の検知に向けて:行動データと心理尺度との関係分析},
author = {王振博 and 田谷昭仁 and 加藤貴昭 and 瀬崎薫 and 西山勇毅},
year = {2023},
date = {2023-11-01},
urldate = {2023-11-01},
booktitle = {研究報告ユビキタスコンピューティングシステム(UBI)},
volume = {2023-UBI-80},
pages = {1 - 8},
abstract = {競技と学業の両立を目指す学生アスリートにとって,自らの心身の心理的ストレスと回復状況の精緻
な把握は極めて重要である.既存研究においては,身体活動や心身健康の調査は主に主観的な報告に依存
しており,持続的で客観的なデータのサポートが不足しているため,ある程度の偏りと制限性が存在する.
さらに,学生アスリートの特有のニーズやライフスタイルに対する研究は相対的に不足している.そこで
本研究では,スマートフォン・ウェアラブルデバイスに搭載されたセンサを活用して,学生アスリートの競
技中の行動データを途切れることなく継続的に追跡する.多角的なデータ分析を通じて,学生アスリート
の行動データと心身のストレス・回復状態との関連性を分析する.また,競技中のアスリートの運動量,各
睡眠ステージの時間,各異なる時間帯のデータと心身のストレス・回復状態との関連性を詳細に分析する.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
北森迪耶, 坪内孝太, 西尾信彦, 西山勇毅, 下坂正倫
ハンズフリーのデバイス操作のための汎用イヤラブルデバイスのIMUセンサーを用いた表情認識手法 Conference To Appear
研究報告ユビキタスコンピューティングシステム(UBI), 2023-UBI-80 , 2023.
BibTeX | Tags:
@conference{ubi80_earable,
title = {ハンズフリーのデバイス操作のための汎用イヤラブルデバイスのIMUセンサーを用いた表情認識手法},
author = {北森迪耶 and 坪内孝太 and 西尾信彦 and 西山勇毅 and 下坂正倫},
year = {2023},
date = {2023-11-01},
urldate = {2023-11-01},
booktitle = {研究報告ユビキタスコンピューティングシステム(UBI)},
volume = {2023-UBI-80},
pages = {1 - 8},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
小野翔多, 山崎託, 三好匠, 田谷昭仁, 西山勇毅, 瀬崎薫
ユーザの移動性を活用した地域連携型連合学習における学習モデル統合手法の評価 Conference To Appear
第31回 マルチメディア通信と分散処理ワークショップ (DPSWS2023), 富山, 2023.
Abstract | BibTeX | Tags: | Links:
@conference{dpsws_ono,
title = {ユーザの移動性を活用した地域連携型連合学習における学習モデル統合手法の評価},
author = {小野翔多 and 山崎託 and 三好匠 and 田谷昭仁 and 西山勇毅 and 瀬崎薫},
url = {https://www.dpsws.org/2023/},
year = {2023},
date = {2023-10-25},
urldate = {2023-10-25},
booktitle = {第31回 マルチメディア通信と分散処理ワークショップ (DPSWS2023)},
address = {富山},
abstract = {近年,クラウドやエッジなどの計算施設でセンサシングデータを分析することは多様なサービス提供に利用されているが,設備コストや電力消費の増加が問題となっている.
これに対処するため,高性能な市販デバイスを活用し,モバイルデバイス同士で学習を協力して実行する連合学習が提案されている.
連合学習は大規模施設の設置費用や消費電力を削減でき,ユーザのプライバシーも保護できる.
さらに,地域特有のデータ特性を考慮に入れた地域限定型連合学習も提案されているが,これは特定の地域を一つだけに限定して実行され,地域間の連携は考慮されていない.
そこで,本稿では,ユーザの移動性を活用して,地域ごとの学習モデルを統合する地域連携型連合学習を提案する.
この手法は,特定の地域で学習されたモデルを他の地域と統合し,それによって学習モデルの性能を向上させることを目指す.
提案手法により,地域ごとに特性のあるモデルを作成しつつ,必要に応じて地域間での学習モデルの統合が可能となり,学習モデルの性能向上が期待できる.
評価の結果,学習モデルの統合は一時的に学習精度が低下するが,追加学習によってモデルの精度が向上することが確認された.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
伊藤愛香, 厚見昴, Wang Zhenbo, Gu Xiuwen, 田谷昭仁, 西山勇毅, 瀬崎薫
対話中の非言語行動と大規模言語モデルを活用したシームレスな質疑応答補助システムの提案 Conference
第31回 マルチメディア通信と分散処理ワークショップ (DPSWS2023), 富山, 2023.
BibTeX | Tags: | Links:
@conference{dpsws2023_ito,
title = {対話中の非言語行動と大規模言語モデルを活用したシームレスな質疑応答補助システムの提案},
author = {伊藤愛香 and 厚見昴 and Wang Zhenbo and Gu Xiuwen and 田谷昭仁 and 西山勇毅 and 瀬崎薫},
url = {https://www.dpsws.org/2023/},
year = {2023},
date = {2023-10-25},
urldate = {2023-10-25},
booktitle = {第31回 マルチメディア通信と分散処理ワークショップ (DPSWS2023)},
address = {富山},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
細沼恵里, 山崎託, 三好匠, 田谷昭仁, 西山勇毅, 瀬崎薫
領域的情報と説明的情報を用いた生成型画像圧縮伝送に関する初期検討 Conference
2023年電子情報通信学会通信ソサイエティ大会, 名古屋, 2023.
Abstract | BibTeX | Tags: | Links:
@conference{ubi78_nishiyamae,
title = {領域的情報と説明的情報を用いた生成型画像圧縮伝送に関する初期検討},
author = {細沼恵里 and 山崎託 and 三好匠 and 田谷昭仁 and 西山勇毅 and 瀬崎薫},
url = {https://www.ieice.org/jpn_r/activities/taikai/society/2023/assets/pdf/program2023s.pdf},
year = {2023},
date = {2023-09-12},
urldate = {2023-09-12},
booktitle = {2023年電子情報通信学会通信ソサイエティ大会},
address = {名古屋},
abstract = {空間内を撮影した画像をネットワークを介して伝送するシステムは多々存在する.しかし,将来的な通信端末数の増加に伴い,今後,多地点で撮影した画像を同時に伝送することが困難になる可能性がある.これに対し,様々な画像圧縮技術が提案されているが,これらの手法は画像内の全情報を維持したまま圧縮を行う.しかし,場面によっては,画像内の全情報を維持して圧縮することが冗長となる可能性がある.そこで,画像から特定の情報を抽出して伝送し,受信端末が画像を再生成することでデータ量を削減できると考えられる.本稿では,画像から特定の情報を抽出して伝送し,受信端末が画像生成モデルを用いて画像を復元する手法を提案する.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
小野翔多, 山崎託, 三好匠, 田谷昭仁, 西山勇毅, 瀬崎薫
連合学習におけるスマートフォンの電力消費量の調査 Conference Award
2023年電子情報通信学会通信ソサイエティ大会, 名古屋, 2023.
Abstract | BibTeX | Tags: | Links:
@conference{society2023_ono,
title = {連合学習におけるスマートフォンの電力消費量の調査},
author = {小野翔多 and 山崎託 and 三好匠 and 田谷昭仁 and 西山勇毅 and 瀬崎薫},
url = {https://www.ieice.org/jpn_r/activities/taikai/society/2023/assets/pdf/program2023s.pdf},
year = {2023},
date = {2023-09-12},
urldate = {2023-09-12},
booktitle = {2023年電子情報通信学会通信ソサイエティ大会},
address = {名古屋},
abstract = {集中管理型の連合学習では,学習のための計算量が大規模サーバやデータセンタなどの中央サーバに集中するとともに,データ集約のための通信量が増加する問題がある.
そこで,学習クライアントとしてモバイルデバイスを用いるユーザ参加型連合学習が提案されている.
本手法により,前述の計算量と通信量の問題を解決できるが,モバイルデバイスの電力消費量の増加が懸念される.モバイルデバイスは通常,電源に接続されておらずバッテリー駆動であることが多いため,学習に参加する際,電力消費量とバッテリー残量を考慮する必要がある.
本稿では,モバイルデバイスとしてスマートフォンを用い,ユーザ参加型連合学習のアプリケーションを実装して,電力消費量とバッテリー残量が学習性能に与える影響を評価する.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
大塚理恵子, 伊藤昌毅, 太田恒平, 瀬崎薫
ユーザ識別子付きスマホ位置情報を用いた大規模事業所の出勤時刻分析-時差出勤エリアマネジメントの実現に向けて- Conference
第67回土木計画学研究発表会・春大会(自由投稿型), 2023.
Abstract | BibTeX | Tags: area management, big data in urban transport, commuter's trip, location data with user-ID, staggered commuting | Links:
@conference{jsce_otsuka2023,
title = {ユーザ識別子付きスマホ位置情報を用いた大規模事業所の出勤時刻分析-時差出勤エリアマネジメントの実現に向けて-},
author = {大塚理恵子 and 伊藤昌毅 and 太田恒平 and 瀬崎薫},
url = {https://jsce-ip.org/2022/12/15/ip67/},
year = {2023},
date = {2023-06-03},
urldate = {2023-06-03},
booktitle = {第67回土木計画学研究発表会・春大会(自由投稿型)},
abstract = {近年,地方都市では地域公共交通利用者が減少し,交通事業者の経営が悪化している.地域公共交通を維持していくためには個々の事業者や個別路線の改善にとどまらず,地域全体の移動需要を把握し,その地域の事情を考慮した施策の検討が必要である.本研究では日々,一定の移動需要を生み出すセグメントの代表的存在である通勤者を取り上げ,地方都市の通勤行動分析に取り組む.地域全体の移動実態を俯瞰できるデータソースとしてユーザ識別子付きのスマホ位置情報に着目し,熊本県内の大規模事業所を対象に通勤者の出勤時刻分布について分析した.複数事業所を対象とした時差出勤エリアマネジメント施策の検討材料としての活用が期待できる.},
keywords = {area management, big data in urban transport, commuter's trip, location data with user-ID, staggered commuting},
pubstate = {published},
tppubtype = {conference}
}
石岡陸, 坪内孝太, 西山勇毅, 瀬崎薫
異なる環境条件におけるGNSS信号強度とUVインデックスの関係 Conference
研究報告ユビキタスコンピューティングシステム(UBI), 2023-UBI-78 , 2023.
@conference{ubi78_ishioka,
title = {異なる環境条件におけるGNSS信号強度とUVインデックスの関係},
author = {石岡陸 and 坪内孝太 and 西山勇毅 and 瀬崎薫},
year = {2023},
date = {2023-05-24},
urldate = {2023-05-24},
booktitle = {研究報告ユビキタスコンピューティングシステム(UBI)},
volume = {2023-UBI-78},
pages = {1 - 8},
abstract = {近年,個人の浴びる紫外線(UV)量の推定手法として,スマートフォンの衛星測位システム(GNSS)センサを用いる方法が研究され始めた.GNSS による推定は,ユーザの負担なくUV 量を推定できる可能性があるという原理的な利点を持っている一方で,十分な有効性が示されている環境は限定的である.そこで,本研究では,実際のユースケースに近い形でデータを収集できるシステムを考案し,そのシステムを用いて,3 つの地域・2 つの時期・4 つの収集形態(頭の上・ポケットの中・リュックの中・地面に固定)でデータを収集した.さらに,収集したデータを用いて,UV 量推定に向けた基礎的検討として,衛星の信号強度とUV インデックスの相関を計算し,異なる条件下での相関の違いについて比較を行った.分析結果のうち,特に,スマートフォンがリュックの中にあっても相関があること,衛星によって相関の強さが大きく異なることは,今後のGNSS によるUV 量推定の精度改善につながると期待される.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
西山勇毅, 加藤貴昭, 瀬崎薫
パッシブモバイルセンシングを用いた学生アスリートのコンディション検知に向けた基礎調査 Conference
研究報告ユビキタスコンピューティングシステム(UBI), 2023-UBI-78 , 2023.
@conference{ubi78_nishiyama,
title = {パッシブモバイルセンシングを用いた学生アスリートのコンディション検知に向けた基礎調査},
author = {西山勇毅 and 加藤貴昭 and 瀬崎薫},
year = {2023},
date = {2023-05-24},
urldate = {2023-05-24},
booktitle = {研究報告ユビキタスコンピューティングシステム(UBI)},
volume = {2023-UBI-78},
pages = {1 - 8},
abstract = {学生アスリートにとって心身のストレスとその回復状態を手軽に認識できることは,競技と学業生活を健康に過ごす上で非常に重要である.既存研究では,アンケート調査や血液検査,高性能な生体センサを用いて心身のストレス状態の計測が行われているが,計測負荷が大きく継続利用は難しい.そこで本研究では,市販のスマートフォン・ウェアラブルデバイスに搭載されたセンサを活用し,低負荷にアスリートのコンディションを検出するシステムを開発する.特に本稿では,アスリートのコンディション検知に向けて,データ収集基盤の設計と実装する.さらにデータ収集実験を実施し,収集データからコンディション検知に機構に向けた基礎的な調査を行う.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
牛島秀暢, 石岡陸, 田谷昭仁, 西山勇毅, 瀬崎薫
自動運転車と歩行者間の合意形成手法の基礎的検討 Conference
電子情報通信学会 総合大会, 2023.
@conference{ieice2023_ushijima,
title = {自動運転車と歩行者間の合意形成手法の基礎的検討},
author = {牛島秀暢 and 石岡陸 and 田谷昭仁 and 西山勇毅 and 瀬崎薫},
year = {2023},
date = {2023-03-27},
urldate = {2023-03-27},
booktitle = {電子情報通信学会 総合大会},
abstract = {自動運転社会の到来から、これまで運転者と歩行者が暗黙的に行ってきた合意形成が行われなくなる事から、これまで起き得なかったような事故やトラブルが発生すると考えられている。そのため、新しい自動運転車と歩行者間での合意形成手法が必要となる。本研究では、狭路の一方通行における追い越し場面を想定し、音声情報と視覚情報を複合的に組み合わせた自動運転車と歩行者との合意形成手法の基礎的検討をした。},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
細沼恵里, 三好匠, 山崎託, 西山勇毅, 瀬崎薫
LPWAによる屋内空間の混雑領域推定に向けた検討 Conference
2023年電子情報通信学会総合大会, 2023.
@conference{ubi78_nishiyamab,
title = {LPWAによる屋内空間の混雑領域推定に向けた検討},
author = {細沼恵里 and 三好匠 and 山崎託 and 西山勇毅 and 瀬崎薫},
year = {2023},
date = {2023-03-24},
urldate = {2023-03-24},
booktitle = {2023年電子情報通信学会総合大会},
abstract = {空間内に設置した無線センサノードが送受信する信号の受信信号強度(RSSI: Received Signal Strength Indication)に基づき混雑度を推定する手法が提案されている.これらの手法では,室内やイベント会場内などの開けた領域にセンサノードを設置し,定期的に制御メッセージを交換することで,各ノードが受信したメッセージのRSSIに基づき領域内の滞在人数を推定する.
しかし,これらの手法によって,上述する領域が複数存在する建物のフロア全体など,広域な屋内空間内の混雑領域を推定するためには,各領域内に多数のノードを設置する必要がある.そこで,本稿では,低消費電力かつ広域通信が可能な無線通信規格であるLPWA(Low Power Wide Area)を用いた低コストかつ様々な広域屋内環境に適用可能な混雑領域推定手法の実現に向けて,LPWAノードを用いたRSSIの計測実験を行う.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
細沼恵里, 山崎託, 三好匠, 田谷昭仁, 西山勇毅, 瀬崎薫
広域屋内空間における人の滞在が受信信号強度に与える影響の解析 Conference
電子情報通信学会 情報通信マネジメント研究会(ICM), 沖縄, 2023.
Abstract | BibTeX | Tags: LPWA, 受信信号強度, 屋内空間, 混雑領域推定 | Links:
@conference{ubi78_nishiyamac,
title = {広域屋内空間における人の滞在が受信信号強度に与える影響の解析},
author = {細沼恵里 and 山崎託 and 三好匠 and 田谷昭仁 and 西山勇毅 and 瀬崎薫},
url = {https://ken.ieice.org/ken/program/index.php?tgs_regid=4f1b43d5391165137a938d73306c6d65ed10411e4ef8561f3b1839e6d46826f0&tgid=IEICE-ICM},
year = {2023},
date = {2023-03-17},
urldate = {2023-03-17},
booktitle = {電子情報通信学会 情報通信マネジメント研究会(ICM)},
address = {沖縄},
abstract = {快適かつ安全な都市空間を維持するため,空間内の混雑度を推定する様々な手法が提案されている.
特に,導入コストやプライバシの観点から,無線センサノード同士が送受信するメッセージの受信信号強度の変化を基に空間内の滞在人数を推定する手法が提案されている.しかし,従来手法は,一つの部屋やイベント会場など,ある特定の空間内での利用を想定している.
そのため,建物のフロア全体などの広域な屋内空間内の混雑度とその領域を推定するためには,各部屋に多数のノードを設置する必要がある.そこで,著者らは,広域通信が可能なLPWA(Low Power Wide Area)を用いることにより,少ないノード台数で混雑領域を推定する手法の実現を目指している.本稿では,混雑領域の推定に利用可能な指標を調査するため,広域屋内空間における人の滞在場所がLPWAノードの受信信号強度に与える影響を実験により解析する.},
keywords = {LPWA, 受信信号強度, 屋内空間, 混雑領域推定},
pubstate = {published},
tppubtype = {conference}
}
小野翔多, 山崎託, 三好匠, 田谷昭仁, 西山勇毅, 瀬崎薫
[奨励講演] スポット型連合学習におけるユーザ滞在時間が学習性能に与える影響の評価 Conference
電子情報通信学会 情報通信マネジメント研究会(ICM), 沖縄, 2023.
Abstract | BibTeX | Tags: 連合学習,スポット,位置情報 | Links:
@conference{nokeyc,
title = {[奨励講演] スポット型連合学習におけるユーザ滞在時間が学習性能に与える影響の評価},
author = {小野翔多 and 山崎託 and 三好匠 and 田谷昭仁 and 西山勇毅 and 瀬崎薫},
url = {https://ken.ieice.org/ken/program/index.php?tgs_regid=4f1b43d5391165137a938d73306c6d65ed10411e4ef8561f3b1839e6d46826f0&tgid=IEICE-ICM},
year = {2023},
date = {2023-03-17},
urldate = {2023-03-17},
booktitle = {電子情報通信学会 情報通信マネジメント研究会(ICM)},
address = {沖縄},
abstract = {連合学習では,モデルの更新のたびに通信が発生し,モバイルネットワークの通信量が増加する.そこで, 人が集まりやすい特定のスポットに着目し,そこに集まる人たちのみでデバイス間直接通信を用いて学習するスポッ ト型連合学習を提案する.提案手法は,特定のスポットに適したデータを学習し,周辺ユーザに対してサービスを提 供できるが,移動によってスポットに存在するユーザ数が変動する.本稿では,実装実験によってユーザの滞在時間 が学習に与える影響を評価した.実験の結果,デバイスの離脱が学習性能を低下させる傾向があることが確認できた.},
key = {連合学習,スポット,位置情報},
keywords = {連合学習,スポット,位置情報},
pubstate = {published},
tppubtype = {conference}
}
小野翔多, 山崎託, 三好匠, 田谷昭仁, 西山勇毅, 瀬崎薫
無線アドホックネットワークにおけるユーザ参加型連合学習の実装実験 Conference
2023 電子情報通信学会総合大会, 埼玉, 2023.
BibTeX | Tags: MANET, モバイルネットワーク, 位置情情報, 負荷分散
@conference{nokey,
title = {無線アドホックネットワークにおけるユーザ参加型連合学習の実装実験},
author = {小野翔多 and 山崎託 and 三好匠 and 田谷昭仁 and 西山勇毅 and 瀬崎薫},
year = {2023},
date = {2023-03-07},
urldate = {2023-03-07},
booktitle = {2023 電子情報通信学会総合大会},
address = {埼玉},
keywords = {MANET, モバイルネットワーク, 位置情情報, 負荷分散},
pubstate = {published},
tppubtype = {conference}
}
小野寺文香, 石岡陸, 西山勇毅, 瀬崎薫
ウェアラブルデバイスを用いた乳幼児コンテクストの検知に向けた一検討 Conference
情報処理学会 第85回全国大会(電気通信大学), 情報処理学会, 2023.
BibTeX | Tags: | Links:
@conference{ipsj2023_onodera,
title = {ウェアラブルデバイスを用いた乳幼児コンテクストの検知に向けた一検討},
author = {小野寺文香 and 石岡陸 and 西山勇毅 and 瀬崎薫},
url = {https://www.ipsj.or.jp/event/taikai/85/index.html},
year = {2023},
date = {2023-03-02},
urldate = {2023-03-02},
booktitle = {情報処理学会 第85回全国大会(電気通信大学)},
publisher = {情報処理学会},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Suxing Lyu, Yuuki Nishiyama, Kaoru Sezaki, Takahiko Kusakabe
Generic Trip Purpose Inference Modelling on Trip Chain Conference
研究報告ユビキタスコンピューティングシステム(UBI):博士論文セッション, 2023-UBI-77 , 2023.
@conference{ubi77_SuxingLyu,
title = {Generic Trip Purpose Inference Modelling on Trip Chain},
author = {Suxing Lyu and Yuuki Nishiyama and Kaoru Sezaki and Takahiko Kusakabe},
year = {2023},
date = {2023-02-01},
urldate = {2023-02-01},
booktitle = {研究報告ユビキタスコンピューティングシステム(UBI):博士論文セッション},
volume = {2023-UBI-77},
pages = {1 - 2},
abstract = {Urban transportation systems are under increasing pressure from rapid population growth. At the same time, urban functions are becoming complex and diversified. In this context, the rapid transformation of cities has long promoted the demand for human mobility (travel behavior) analysis. Trip purpose, one of the behavioral factors, is crucial to understanding human mobility generation. But keeping track of trip purpose is not easy. Nowadays, there is a huge volume of human mobility data passively collected by mobile devices. Trip purpose is right the missing item form the data. The more reliable we are in the inference of the missing items, the more beneficial we can get from the data. A generic trip purpose inference can bring semantic information to human mobility. Consequently, the decision of urban transportation and urban infrastructure development will be improved and supported based on the understanding of human mobility generation. The doctoral study reports the findings on developing the generic privacy-insensitive trip purpose inference for one-day travel (trip chain).},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Akihito Taya, Yuuki Nishiyama, Kaoru Sezaki
Convergence Visualizer of Decentralized Federated Distillation with Reduced Communication Costs Inproceedings To Appear
In: Proceedings of IEEE Global Communications (GLOBECOM) 2023, IEEE, Kuala Lumpur, Malaysia, 2023.
@inproceedings{Globecom2023_Taya,
title = {Convergence Visualizer of Decentralized Federated Distillation with Reduced Communication Costs},
author = {Akihito Taya and Yuuki Nishiyama and Kaoru Sezaki},
year = {2023},
date = {2023-12-04},
urldate = {2023-12-04},
booktitle = {Proceedings of IEEE Global Communications (GLOBECOM) 2023},
publisher = {IEEE},
address = {Kuala Lumpur, Malaysia},
series = {GLOBECOM 2023},
abstract = {Federated learning (FL) achieves collaborative learning without the need for data sharing, thus preventing privacy leakage. To extend FL into a fully decentralized algorithm, researchers have applied distributed optimization algorithms to FL by considering machine learning (ML) tasks as parameter optimization problems. Conversely, the consensus-based multi-hop federated distillation (CMFD) proposed in the authors' previous work makes neural network (NN) models get close with others in a function space rather than in a parameter space. Hence, this study solves two unresolved challenges of CMFD: (1) communication cost reduction and (2) visualization of model convergence. Based on a proposed dynamic communication cost reduction method (DCCR), the amount of data transferred in a network is reduced; however, with a slight degradation in the prediction accuracy. In addition, a technique for visualizing the distance between the NN models in a function space is also proposed. The technique applies a dimensionality reduction technique by approximating infinite-dimensional functions as numerical vectors to visualize the trajectory of how the models change by the distributed learning algorithm.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Junya Maruyama, Yudai Honma, Yuuki Nishiyama, Yoshihiro Kawahara
A Trajectory Estimation Method from Spatially Sparse and Noisy Beacon Data Based on Spring Dynamics Inproceedings To Appear
In: Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, pp. 286–287, Association for Computing Machinery, Istanbul, Turkey, 2023, ISBN: 9798400702303.
Abstract | BibTeX | Tags: Architectural Space, Building corridor Network, Human trajectory | Links:
@inproceedings{10.1145/3600100.3626263,
title = {A Trajectory Estimation Method from Spatially Sparse and Noisy Beacon Data Based on Spring Dynamics},
author = {Junya Maruyama and Yudai Honma and Yuuki Nishiyama and Yoshihiro Kawahara},
url = {https://doi.org/10.1145/3600100.3626263
https://buildsys.acm.org/2023/},
doi = {10.1145/3600100.3626263},
isbn = {9798400702303},
year = {2023},
date = {2023-11-15},
urldate = {2023-11-15},
booktitle = {Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation},
pages = {286–287},
publisher = {Association for Computing Machinery},
address = {Istanbul, Turkey},
series = {BuildSys '23},
abstract = {Analysis of trajectory data within buildings offers insights for optimizing environmental design and habitability. However, data from indoor location sensors tend to be sparse and noisy. This makes it difficult for conventional route estimation models to be applied effectively. Our study seeks to derive detailed, temporally, and spatially rich trajectory data from this compromised sensor information. We achieve this by interpreting trajectories as continuous stay points. To facilitate this, we introduce a building corridor network that conceptualizes buildings as a series of points. Routes are inferred using a sequence estimation model applied to this network. This approach employs spring dynamics, which balance the resistance to staying with the attraction to specific beacons, via mathematical optimization. Notably, our model can deduce a trajectory of 131 points from only 15 beacons with, an accuracy rate of 87. Our method presents a promising avenue for capturing extensive route data.},
keywords = {Architectural Space, Building corridor Network, Human trajectory},
pubstate = {published},
tppubtype = {inproceedings}
}
Yuuki Nishiyama, Kaoru Sezaki
Smartwatch-Based Sensing Framework for Continuous Data Collection: Design and Implementation Inproceedings
In: Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2023 ACM International Symposium on Wearable Computers, Association for Computing Machinery, Cancun, Mexico, 2023.
@inproceedings{UbiComp2023_Nishiyama,
title = {Smartwatch-Based Sensing Framework for Continuous Data Collection: Design and Implementation},
author = {Yuuki Nishiyama and Kaoru Sezaki},
year = {2023},
date = {2023-10-08},
urldate = {2023-10-08},
booktitle = {Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2023 ACM International Symposium on Wearable Computers},
publisher = {Association for Computing Machinery},
address = {Cancun, Mexico},
series = {UbiComp-ISWC '23},
abstract = {Smartwatches are an increasingly popular technology that employs advanced sensors (e.g., location, motion, and microphone) comparable to those used by smartphones. Passive mobile sensing, a method of acquiring human behavior data from mobile and wearable devices inconspicuously, is widely used in research fields related to behavior analysis. In combination with machine learning, passive mobile sensing can be used to interpret various human and environmental contexts without requiring user intervention. Because smartwatches are always worn on the wrist, they have the potential to collect data that cannot be collected by smartphones. However, the effective use of smartwatches as platforms for passive mobile sensing poses challenges in terms of battery life, storage, and communication. To address these challenges, we designed and implemented a tailored framework for off-the-shelf smartwatches. We evaluated power consumption under eight different sensing conditions using three smartwatches. The results demonstrate that the framework can collect sensor data with a battery life of 16-31 h depending on the settings. Finally, we considered potential future solutions for optimizing power consumption in passive sensing with off-the-shelf smartwatches.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Ayaka Onodera, Riku Ishioka, Yuuki Nishiyama, Kaoru Sezaki
Assessing Infant and Toddler Behaviors through Wearable Inertial Sensors: A Preliminary Investigation Inproceedings
In: Proceedings of the 20th ACM International Conference on Multimodal Interaction, pp. xx-xx, Association for Computing Machinery, Paris, France, 2023.
@inproceedings{imci2023_onodera,
title = {Assessing Infant and Toddler Behaviors through Wearable Inertial Sensors: A Preliminary Investigation},
author = {Ayaka Onodera and Riku Ishioka and Yuuki Nishiyama and Kaoru Sezaki},
year = {2023},
date = {2023-10-01},
urldate = {2023-10-01},
booktitle = {Proceedings of the 20th ACM International Conference on Multimodal Interaction},
pages = {xx-xx},
publisher = {Association for Computing Machinery},
address = {Paris, France},
series = {ICMI '23},
abstract = {Accurately assessing a child’s health status and taking appropriate action in case of illness or other emergencies is crucial to recording and sharing a childcare situation, such as sleeping hours, amount of exercise, and timing of meals.
Although numerous applications and systems have been proposed to assist in recording and sharing these records, the process is still performed manually, representing a significant burden for parents. Therefore, automatic recording of infants' and toddlers' daily activities is required.
Moreover, existing automatic infant behavior recognition methods have significant limitations on the space and target of application.
In this study, we implement a machine-learning model to investigate and propose a method to classify typical daily behaviors of infants and toddlers using a chest-mounted low-sampling rate accelerometer.
In particular, the proposed method classifies eight activities: sleeping, crawling, walking, standing, sitting, drinking milk, eating baby food, and holder by a caregiver.
As a dataset, we collected accelerometer data for nearly 18 hours with reference videos from ten infants and toddlers between 6 and 24 months. Based on the data, we extracted 60 time- and frequency-domain features calculated from the single accelerometer and a user feature to recognize the target daily activities. In the best case of our performance evaluation with different window sizes and machine learning models, our classification model reaches nearly 80% accuracy.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Zengyi Han, Xuefu Dong, Yuuki Nishiyama, Kaoru Sezaki
HeadSense: Visual Search Monitoring and Distracted Behavior Detection for Bicycle Riders Inproceedings
In: 2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), pp. 281-289, Boston, Massachusetts, 2023, ISBN: 979-8-3503-3165-3.
Abstract | BibTeX | Tags: Head Movement Detection, Human Activity recognition, Mobile sensing | Links:
@inproceedings{wowmon2023_han,
title = {HeadSense: Visual Search Monitoring and Distracted Behavior Detection for Bicycle Riders},
author = {Zengyi Han and Xuefu Dong and Yuuki Nishiyama and Kaoru Sezaki},
url = {https://coe.northeastern.edu/Groups/wowmom2023/index.html},
doi = {10.1109/WoWMoM57956.2023.00043},
isbn = {979-8-3503-3165-3},
year = {2023},
date = {2023-07-12},
urldate = {2023-07-12},
booktitle = {2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)},
pages = {281-289},
address = {Boston, Massachusetts},
abstract = {Distracted riding behavior is one of the main causes of bicycle-related traffic accidents, resulting in a large number of casualties and economic losses every year. There is an urgent need to address this problem by accurately detecting distracted riding behaviors. Inspired by the observation that distracted riding behaviors induce unique head motion features that respond to the rider's attention, we present the HeadSense, a helmet-based system that not only monitors the visual search episode of the rider but also detects distracted riding behaviors. Specifically, HeadSense leverages the inertial motion unit (IMU) to recognize distracted behaviors such as using smartphones, attracting to the roadside element, and abreast riding. We designed, implemented, and evaluated HeadSense through extensive experiments. We conducted experiments with 19 participants inside the university's campus. The experimental results show that HeadSense can achieve an overall accuracy of 86.14% while monitoring visual search episodes. Moreover, HeadSense can detect the occurrence of distracted riding behaviors with an average precision of up to 85.04%.},
keywords = {Head Movement Detection, Human Activity recognition, Mobile sensing},
pubstate = {published},
tppubtype = {inproceedings}
}
Zengyi Han, Liqiang Xu, Xuefu Dong, Yuuki Nishiyama, Kaoru Sezaki
HeadMon: Head Dynamics Enabled Riding Maneuver Prediction Inproceedings
In: IEEE International Conference on Pervasive Computing and Communications (PerCom), pp. 22–31, IEEE, Atlanta, USA, 2023, ISBN: 978-1-6654-5378-3.
Abstract | BibTeX | Tags: Head Movement, Human Activity Prediction, mobile computing | Links:
@inproceedings{percom2023_han,
title = {HeadMon: Head Dynamics Enabled Riding Maneuver Prediction},
author = {Zengyi Han and Liqiang Xu and Xuefu Dong and Yuuki Nishiyama and Kaoru Sezaki},
url = {https://www.percom.org/PerCom2023/},
doi = {10.1109/PERCOM56429.2023.10099215},
isbn = {978-1-6654-5378-3},
year = {2023},
date = {2023-03-13},
urldate = {2023-03-13},
booktitle = {IEEE International Conference on Pervasive Computing and Communications (PerCom)},
pages = {22--31},
publisher = {IEEE},
address = {Atlanta, USA},
abstract = {Although micro-mobility brings convenience to modern cities, they also cause various social problems, such as traffic accidents, casualties, and substantial economic losses. Wearing protective equipment has become the primary recommendation for safe riding. However, passive protection cannot prevent the occurrence of accidents. Thus, timely predicting the rider's maneuver is essential for active protection and providing more time to avoid potential accidents from happening. Through the qualitative study, we argue that we can use the rider's head dynamic as an information source to predict the rider's following maneuvers. We accordingly present HeadMon, a riding maneuver prediction system for safe riding. HeadMon utilizes the head dynamics of a rider by installing an inertial measurement unit on the helmet. It uses the extracted head dynamics features as the input of the deep learning architecture to achieve prediction. We implemented the HeadMon prototype on Android smartphone as a proof of concept. Through comprehensive experiments with 20 participants, the result demonstrates the excellent performance of HeadMon: not only could it achieve an overall precision of at least 85% for maneuver prediction under a 4s prediction time gap, but it also could keep a high accuracy under a low sampling rate. The low-cost feature of HeadMon allows it to be readily deployable and towards more safety riding.},
keywords = {Head Movement, Human Activity Prediction, mobile computing},
pubstate = {published},
tppubtype = {inproceedings}
}
Haoyu Zhuang, Liqiang Xu, Yuuki Nishiyama, Kaoru Sezaki
Detecting Hand Hygienic Behaviors In-the-Wild Using a Microphone and Motion Sensor on a Smartwatch Inproceedings
In: Streitz, Norbert A.; Konomi, Shiníchi (Ed.): Distributed, Ambient and Pervasive Interactions, pp. 470–483, Springer Nature Switzerland, Cham, 2023, ISBN: 978-3-031-34609-5.
Abstract | BibTeX | Tags: Audio, Hygiene behaviors detection, IMU, Multimodal Fusion, Wearable device | Links:
@inproceedings{10.1007/978-3-031-34609-5_34,
title = {Detecting Hand Hygienic Behaviors In-the-Wild Using a Microphone and Motion Sensor on a Smartwatch},
author = {Haoyu Zhuang and Liqiang Xu and Yuuki Nishiyama and Kaoru Sezaki},
editor = {Norbert A. Streitz and Shiníchi Konomi},
doi = {10.1007/978-3-031-34609-5_34},
isbn = {978-3-031-34609-5},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
booktitle = {Distributed, Ambient and Pervasive Interactions},
pages = {470--483},
publisher = {Springer Nature Switzerland},
address = {Cham},
abstract = {In recent years, the emergence of the COVID-19 pandemic has led to new viral variants, such as Omicron. These variants are more harmful and impose more restrictions on people’s daily hygiene habits. Therefore, during the COVID-19 pandemic, it is logical to automatically detect epidemic protective behaviors without user intent. In this study, we used multiple sensor data from an off-the-shelf smartwatch to detect several defined behaviors. To increase the utility and generalizability of the research results, we collected audio and inertial measurement unit (IMU) data from eight participants in real environments over a long period. In the model-building process, we first created a binary classification between hand hygiene behaviors(hand washing, disinfection, and face-touching) and daily behavior. Then, we distinguished between specific hand hygiene behaviors based on audio and IMU. Ultimately, our model achieves 93% classification accuracy for three behaviors(Hand washing, face touching, and disinfection). The results prove that the accuracy of the classification of behaviors has improved remarkably, which also emphasizes the feasibility of recognizing hand hygiene behaviors using inertial acoustic data.},
keywords = {Audio, Hygiene behaviors detection, IMU, Multimodal Fusion, Wearable device},
pubstate = {published},
tppubtype = {inproceedings}
}
Eri Hosonuma, Yuuki Nishiyama, Kaoru Sezaki, Takumi Miyoshi, Taku Yamazaki
Enabling Block Transmission on Backoff-based Opportunistic Routing Inproceedings
In: 2023 IEEE 20th Annual Consumer Communications & Networking Conference (IEEE CCNC 2023), 2023.
BibTeX | Tags: | Links:
@inproceedings{published_papers/40226623,
title = {Enabling Block Transmission on Backoff-based Opportunistic Routing},
author = {Eri Hosonuma and Yuuki Nishiyama and Kaoru Sezaki and Takumi Miyoshi and Taku Yamazaki},
doi = {10.1109/CCNC51644.2023.10059637},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
booktitle = {2023 IEEE 20th Annual Consumer Communications & Networking Conference (IEEE CCNC 2023)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Shota Ono, Taku Yamazaki, Takumi Miyoshi, Yuuki Nishiyama, Kaoru Sezaki
Cooperative Local Distributed Machine Learning Considering Communication Latency and Power Consumption Inproceedings
In: 2023 IEEE 20th Annual Consumer Communications & Networking Conference (IEEE CCNC 2023), 2023.
BibTeX | Tags: | Links:
@inproceedings{published_papers/40226624,
title = {Cooperative Local Distributed Machine Learning Considering Communication Latency and Power Consumption},
author = {Shota Ono and Taku Yamazaki and Takumi Miyoshi and Yuuki Nishiyama and Kaoru Sezaki},
doi = {10.1109/CCNC51644.2023.10060678},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
booktitle = {2023 IEEE 20th Annual Consumer Communications & Networking Conference (IEEE CCNC 2023)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Takahiro Yabe, Kota Tsubouchi, Toru Shimizu, Yoshihide Sekimoto, Kaoru Sezaki, Esteban Moro, Alex Pentland
Metropolitan Scale and Longitudinal Dataset of Anonymized Human Mobility Trajectories Miscellaneous Open Access
arXiv, 2023.
Abstract | BibTeX | Tags: | Links:
@misc{yabe2023metropolitan,
title = {Metropolitan Scale and Longitudinal Dataset of Anonymized Human Mobility Trajectories},
author = {Takahiro Yabe and Kota Tsubouchi and Toru Shimizu and Yoshihide Sekimoto and Kaoru Sezaki and Esteban Moro and Alex Pentland},
doi = {10.48550/arXiv.2307.03401},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
abstract = {Modeling and predicting human mobility trajectories in urban areas is an essential task for various applications. The recent availability of large-scale human movement data collected from mobile devices have enabled the development of complex human mobility prediction models. However, human mobility prediction methods are often trained and tested on different datasets, due to the lack of open-source large-scale human mobility datasets amid privacy concerns, posing a challenge towards conducting fair performance comparisons between methods. To this end, we created an open-source, anonymized, metropolitan scale, and longitudinal (90 days) dataset of 100,000 individuals' human mobility trajectories, using mobile phone location data. The location pings are spatially and temporally discretized, and the metropolitan area is undisclosed to protect users' privacy. The 90-day period is composed of 75 days of business-as-usual and 15 days during an emergency. To promote the use of the dataset, we will host a human mobility prediction data challenge (`HuMob Challenge 2023') using the human mobility dataset, which will be held in conjunction with ACM SIGSPATIAL 2023.},
howpublished = {arXiv},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Helinyi Peng, Yuuki Nishiyama, Kaoru Sezaki
Assessing environmental benefits from shared micromobility systems using machine learning algorithms and Monte Carlo simulation Journal Article Open Access
In: Sustainable Cities and Society, pp. 104207, 2022, ISSN: 2210-6707.
Abstract | BibTeX | Tags: Big data, environmental impacts, Greenhouse gas (GHG) emission, Machine learning, shared micromobility | Links:
@article{PENG2022104207,
title = {Assessing environmental benefits from shared micromobility systems using machine learning algorithms and Monte Carlo simulation},
author = {Helinyi Peng and Yuuki Nishiyama and Kaoru Sezaki},
url = {https://www.sciencedirect.com/science/article/pii/S2210670722005157},
doi = {https://doi.org/10.1016/j.scs.2022.104207},
issn = {2210-6707},
year = {2022},
date = {2022-10-01},
urldate = {2022-01-01},
journal = {Sustainable Cities and Society},
pages = {104207},
abstract = {Shared micromobility systems (SMSs) are paving the way for new, more convenient travel options while also lowering transportation-related greenhouse gas (GHG) emissions. However, few studies have used real-world trip data to estimate SMSs' environmental benefits, especially for dockless scooter-sharing services. To this end, we proposed a system to estimate the GHG emission reduction effected by SMSs. First, several machine learning (ML) algorithms were utilized to identify citizens' travel mode choice preferences, and then the mode substituted by each shared micromobility trip was estimated. We compared the ML algorithms' estimation results and selected those from the random forest, lightGBM, and XGBoost model for further estimating GHG reductions. Second, the Monte Carlo simulations were used to simulate the substituted mode at the trip level to improve the reliability of the final GHG reduction estimation. Finally, the environmental benefits were calculated based on the trip distances and the travel modes that were substituted. Instead of estimating a specific number, we obtained a probabilistic outcome for the environmental benefits while considering the level of uncertainty. Our results suggest that SMSs have positive environmental impacts and have the potential to facilitate the decarbonization of urban transport. According to these findings, implications and suggestions on extending SMSs' environmental benefits are proposed.},
keywords = {Big data, environmental impacts, Greenhouse gas (GHG) emission, Machine learning, shared micromobility},
pubstate = {published},
tppubtype = {article}
}
佐々木航, 柿野優衣, 中縁嗣, 野田悠加, 羽柴彩月, 山田佑亮, 西山勇毅, 大越匡, 中澤仁, 森将輝, 水鳥寿思, 塩田琴美, 永野智久, 東海林祐子, 加藤貴昭
SFC GO: 学生同士の繋がりを支援するオンライン体育授業サポートシステム Journal Article Open Access
In: 情報処理学会論文誌デジタルプラクティス(TDP), 3 (1), pp. 19 - 33, 2022, ISSN: 2435-6484.
Abstract | BibTeX | Tags: COVID-19, モバイルセンシング, 歩数, 行動認識, 身体活動量分析 | Links:
@article{sasaki2021_sfcgo,
title = {SFC GO: 学生同士の繋がりを支援するオンライン体育授業サポートシステム},
author = {佐々木航 and 柿野優衣 and 中縁嗣 and 野田悠加 and 羽柴彩月 and 山田佑亮 and 西山勇毅 and 大越匡 and 中澤仁 and 森将輝 and 水鳥寿思 and 塩田琴美 and 永野智久 and 東海林祐子 and 加藤貴昭},
url = {http://id.nii.ac.jp/1001/00215701/
https://ipsj.ixsq.nii.ac.jp/ej/?action=repository_uri&item_id=215809&file_id=1&file_no=1},
issn = {2435-6484},
year = {2022},
date = {2022-01-01},
urldate = {2021-10-01},
journal = {情報処理学会論文誌デジタルプラクティス(TDP)},
volume = {3},
number = {1},
pages = {19 - 33},
abstract = {COVID-19感染拡大の影響を受け,慶應義塾大学では2020年春学期のすべての授業が,体育も含めてオンライン開催となった.特に大学新入生が全員履修する「体育1」は身体運動体験を通じたクラスメート同士のコミュニケーションの場であり,オンライン授業においてもその機会の損失を防ぐことが求められた.そこで我々は情報系教員・学生と体育教員の知見を融合させた,オンライン体育授業サポートシステム「SFC GO」を1ヶ月で構築し運用した.SFC GOではスマートフォン内蔵センサを用いた身体運動の記録や振り返りが可能であり,出題される課題に則した運動記録をタイムラインへ投稿できる.また,クラスメートの投稿を閲覧することや投稿へコメントすることなどのソーシャルネットワーク機能を有する.そして,バックグラウンドで定常的にセンサデータを収集することによって,家事や散歩などの授業時間以外の日常的な運動の記録や振り返りができる.体育1を履修した学生を対象に学生自身のスマートフォンに本アプリケーションをインストールし,2020年5月から7月のオンライン体育授業で使用した.本稿では,実施期間で収集された運動記録のデータ,テクニカルサポート対応事例やスマートフォンを活用した本実施の経験などから導かれる知見について考察を行う.
All classes including physical education were held online in the 2020 spring semester at Keio University due to the spread of the COVID-19 virus. In particular, “Physical Education 1” required for all first year university students, served as a place for communication between classmates. Therefore, it was crucial that such a place of communication was still available, even as an online course. Thus, we constructed the online physical education class support system “SFC GO”, which combines the knowledge of informatics teachers/students and physical education teachers. SFC GO can record and help the users reflect back on the physical exercises conducted using the sensors built in the smartphone, and it is possible to post the exercise record on the timeline according to the task. It also has social network functions such as viewing and commenting on posts made by classmates. By constantly collecting sensor data in the background, SFC GO can record and reflect back on daily exercises such as housework and walks. For students who took Physical Education 1, this system was installed on their own smartphones and was used in online physical education classes from May to July 2020. In this paper, we show the findings derived from the exercise record data collected, technical support cases, and the experience of this implementation using smartphones.},
keywords = {COVID-19, モバイルセンシング, 歩数, 行動認識, 身体活動量分析},
pubstate = {published},
tppubtype = {article}
}
笠原有貴, 関本義秀, 樫山武浩, 瀬崎薫
ベクトルタイル技術を用いた全国規模の人流データの効率的な可視化 Conference
30 (2), 2022.
Abstract | BibTeX | Tags: ベクトルタイル, 人流データ, 全国規模, 可視化 | Links:
@conference{kasahara2022_GIS-理論と応用b,
title = {ベクトルタイル技術を用いた全国規模の人流データの効率的な可視化},
author = {笠原有貴 and 関本義秀 and 樫山武浩 and 瀬崎薫},
url = {https://www.gisa-japan.org/publications/about.html},
year = {2022},
date = {2022-12-01},
urldate = {2022-12-01},
journal = {GIS-理論と応用},
volume = {30},
number = {2},
pages = {85-90},
abstract = {In recent years, it has become important to understand people flow in various fields. However, most of the methods to understand people flow are limited to urban areas, and there are few studies that have been conducted on a nationwide scale using pseudo people flow data. In addition, by using vector tiling technology in data visualization and changing the granularity of the data according to the zoom level, the amount of data can be saved and the processing speed can be improved. Therefore, in this study, we created pseudo people flow data covering about 120 million people on a nationwide scale using the vector tiling technology, and visualized the data to understand the actual situation. As a result, the amount of data has been reduced to about 57%, and efficient visualization can be performed with the necessary information displayed according to the zoom level, including rural areas.},
keywords = {ベクトルタイル, 人流データ, 全国規模, 可視化},
pubstate = {published},
tppubtype = {conference}
}
大塚理恵子, 伊藤昌毅, 太田恒平, 瀬崎薫
複数の交通ビッグデータを組み合わせた地方都市における通勤者の交通利用状況分析 Conference
第66回土木計画学研究発表会・秋大会(企画提案型), 2022.
Abstract | BibTeX | Tags: big data in urban transport, commuter’s trip, use of transport modes | Links:
@conference{jsce_otsuka2022,
title = {複数の交通ビッグデータを組み合わせた地方都市における通勤者の交通利用状況分析},
author = {大塚理恵子 and 伊藤昌毅 and 太田恒平 and 瀬崎薫},
url = {https://jsce-ip.org/2022/05/06/第66回土木計画学研究発表会・秋大会/},
year = {2022},
date = {2022-11-13},
urldate = {2022-11-13},
booktitle = {第66回土木計画学研究発表会・秋大会(企画提案型)},
abstract = {パーソントリップ調査には交通量の他に移動目的や交通手段別の情報が含まれており,従来から都市交通計画の分野で広く用いられている.しかし,実施頻度が低いため,輸送オペレーションの改善を目的とした活用手段としては不向きである.本研究では,輸送オペレーション業務への活用が期待できるデータソースとして交通ビッグデータに着目し,地方都市における通勤者の公共交通機関利用比率の向上をめざし,自宅と通勤先間の交通利用状況を分析した.具体的には熊本県内を対象に,2021 年秋に取得した複数の交通ビッグデータを用いて通勤者のトリップ数や移動時間,交通手段別の利用状況を集計し,2012 年のパーソントリップ調査との比較を通して活用可能性について考察した.公共交通機関の分担率変化の観測や分担率向上のための施策検討材料といった応用が考えられる.},
keywords = {big data in urban transport, commuter’s trip, use of transport modes},
pubstate = {published},
tppubtype = {conference}
}
石岡陸, 坪内孝太, 西山勇毅, 瀬崎薫
スマートフォンのGNSSセンサを用いたUVインデックス推定 Conference Award
研究報告ユビキタスコンピューティングシステム(UBI), 2022-UBI-76 (20), 情報処理学会, 2022, ISSN: 2188-8698.
Abstract | BibTeX | Tags: | Links:
@conference{weko_222066_1,
title = {スマートフォンのGNSSセンサを用いたUVインデックス推定},
author = {石岡陸 and 坪内孝太 and 西山勇毅 and 瀬崎薫},
url = {http://id.nii.ac.jp/1001/00221996/},
issn = {2188-8698},
year = {2022},
date = {2022-11-01},
urldate = {2022-11-01},
booktitle = {研究報告ユビキタスコンピューティングシステム(UBI)},
volume = {2022-UBI-76},
number = {20},
pages = {1 - 7},
publisher = {情報処理学会},
abstract = {個人の紫外線被曝量モニタリングは,個々人が最適な量の紫外線を浴びることを目的に,盛んに研究されてきた.先行研究では,スマートフォンのカメラや光センサ,ウェアラブルUVセンサを用いた UV 量の推定が提案されてきた.我々は,スマートフォンの GNSS センサを活用した世界初の UV インデックス推定手法を提案する.カメラや光センサを継続的に露出させなければならないような手法と比較して,GNSS を用いた方法は,普段のようにスマートフォンを身につけるだけで推定を可能にするという原理的な利点がある.GNSS による推定の第一歩として,1 つの地域の 3 ヶ所において GNSS データを収集し,OpenUV というAPI をベースラインとして用い,提案手法の有効性を検証した.提案手法は,平均絶対誤差(MAE)0.1523 を達成し,ベースラインを圧倒的に上回った.本研究によって実際のデータに対して提案システムの有効性が証明されたことは,人々が容易に日々の UV 被曝量を把握できるような未来への大きな一歩となることが期待される.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
笠原有貴, 龐岩博, 樫山武浩, 関本義秀, 瀬崎薫
擬似人流データにおける時刻表を考慮した自治体全域の交通手段の推計 ー静岡県裾野市を対象にー Conference
地理情報システム学会 第31回学術研究発表大会(沖縄), 2022.
Abstract | BibTeX | Tags: GTFS, 交通手段選択, 人流データ | Links:
@conference{gis_kasahara2022,
title = {擬似人流データにおける時刻表を考慮した自治体全域の交通手段の推計 ー静岡県裾野市を対象にー},
author = {笠原有貴 and 龐岩博 and 樫山武浩 and 関本義秀 and 瀬崎薫},
url = {https://www.gisa-japan.org/conferences/},
year = {2022},
date = {2022-10-29},
urldate = {2022-10-29},
booktitle = {地理情報システム学会 第31回学術研究発表大会(沖縄)},
abstract = {In recent years, it has become important to understand people flow in various fields such as infectious disease control, and there are various types of means of understanding people flow, such as GPS data and person-trip survey data. However, these data are difficult to share due to privacy protection issues. Based on this, Kashiyama et al. have developed simulations using statistical data to create pseudo-people flow data, which can be shared. Although this data is highly accurate, it does not take into account timetables in terms of people's traffic behavior, which would improve the accuracy by reproducing traffic behavior according to timetables. In this study, we evaluated the accuracy of the pseudo-people flow data created by Kashiyama et al. for Susono City, Shizuoka Prefecture, by estimating the transportation modes with timetables taken into account.},
keywords = {GTFS, 交通手段選択, 人流データ},
pubstate = {published},
tppubtype = {conference}
}
Haoyu Zhuang, Liqiang Xu, Yuuki Nishiyama, Kaoru Sezaki
A preliminary study for monitoring hygiene behaviors by using multiple sensors on a wrist Conference Self Archive
研究報告ユビキタスコンピューティングシステム(UBI), 2022-UBI-75 (27), 2022, ISSN: 2188-8698.
Abstract | BibTeX | Tags: | Links:
@conference{ubi75_zhuang,
title = {A preliminary study for monitoring hygiene behaviors by using multiple sensors on a wrist},
author = {Haoyu Zhuang and Liqiang Xu and Yuuki Nishiyama and Kaoru Sezaki},
url = {http://id.nii.ac.jp/1001/00219769/
https://www.mcl.iis.u-tokyo.ac.jp/wp-content/uploads/2022/12/IPSJ-UBI22075027.pdf},
issn = {2188-8698},
year = {2022},
date = {2022-08-29},
urldate = {2022-08-29},
booktitle = {研究報告ユビキタスコンピューティングシステム(UBI)},
volume = {2022-UBI-75},
number = {27},
pages = {1--7},
abstract = {Under the epidemic of COVID-19, it is important to automatically detect epidemic protective behaviors without a user's intention. Existing studies utilized only sensor data from IMU for detecting epidemic protection behaviors. However, the performance of the classification for similar behaviors could be unsatisfactory due to the single data dimension. It is well known that washing hands and hand sterilization are essential personal hygiene behaviors. In this paper, we use multiple sensor data from an off-the-shelf smartwatch and smartphone for detecting these three behaviors. Our performance evaluation indicated that our proposed method has improved accuracy for classifying the target epidemic protective behaviors over previous methods. Furthermore, for applying our method in reality, we developed a prototype for detecting these behaviors on a wearable device, which allows us to utilize our method widely in health habits monitoring.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
荘昊昱, 韓増易, 西山勇毅, 瀬崎薫
Face-Touch Detection with Smartwatch by CNN: An Experimental Lab Study Conference
電子情報通信学会ソサイエティ大会, オンライン, 2022.
BibTeX | Tags:
@conference{ieice2022_zhuang,
title = {Face-Touch Detection with Smartwatch by CNN: An Experimental Lab Study},
author = {荘昊昱 and 韓増易 and 西山勇毅 and 瀬崎薫},
year = {2022},
date = {2022-06-30},
urldate = {2022-06-30},
booktitle = {電子情報通信学会ソサイエティ大会},
address = {オンライン},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
細沼恵里, 三好匠, 山崎託, 西山勇毅, 瀬崎薫
LPWAによる屋内混雑度推定に向けた基礎検討 Conference
電子情報通信学会ソサイエティ大会, オンライン, 2022.
BibTeX | Tags:
@conference{ieice2022_hosonuma,
title = {LPWAによる屋内混雑度推定に向けた基礎検討},
author = {細沼恵里 and 三好匠 and 山崎託 and 西山勇毅 and 瀬崎薫},
year = {2022},
date = {2022-06-30},
urldate = {2022-06-30},
booktitle = {電子情報通信学会ソサイエティ大会},
address = {オンライン},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
小野翔多, 三好匠, 山崎託, 西山勇毅, 瀬崎薫
無線マルチホップ連合学習へ向けた実装実験 Conference
電子情報通信学会ソサイエティ大会, オンライン, 2022.
BibTeX | Tags:
@conference{ieice2022_ono,
title = {無線マルチホップ連合学習へ向けた実装実験},
author = {小野翔多 and 三好匠 and 山崎託 and 西山勇毅 and 瀬崎薫},
year = {2022},
date = {2022-06-30},
urldate = {2022-06-30},
booktitle = {電子情報通信学会ソサイエティ大会},
address = {オンライン},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
下条和暉, 西山勇毅, 瀬崎薫
イアラブルデバイスを用いた街歩き時におけるユーザの道迷い状態の検知 Conference
研究報告ユビキタスコンピューティングシステム(UBI), 2022-UBI-74 , 2022.
Abstract | BibTeX | Tags: イアラブルデバイス, ナビゲーション, 行動認識 | Links:
@conference{ubi74_shimojo,
title = {イアラブルデバイスを用いた街歩き時におけるユーザの道迷い状態の検知},
author = {下条和暉 and 西山勇毅 and 瀬崎薫},
url = {https://www.ipsj.or.jp/kenkyukai/event/ubi74.html},
year = {2022},
date = {2022-06-06},
urldate = {2022-06-06},
booktitle = {研究報告ユビキタスコンピューティングシステム(UBI)},
volume = {2022-UBI-74},
pages = {1 - 6},
abstract = {街歩きにおいて,ユーザの迷い状態を検知できれば効率的で安全な道案内が実現出来る.イアラブルデバイスは,耳に装着するウェアラブルデバイスであり,搭載された行動認知機構や音声インターフェスによってユーザの状態を把握することが出来る.イアラブルデバイスを活用することえユーザの街中における道迷い状態を検知し,音声案内が可能になると考えられるが,その手法についてはまだ明らかになっていない.そこで本研究では,イアラブルデバイスに搭載されているモーションセンサから収集したデータを用いることで,ユーザの道迷い状態を検知する手法を提案する.},
keywords = {イアラブルデバイス, ナビゲーション, 行動認識},
pubstate = {published},
tppubtype = {conference}
}
小野翔多, 西山勇毅, 瀬崎薫
スマートウォッチを用いたマスク装着の促進手法 Conference
情報処理学会 IoT行動変容学研究グループ キックオフシンポジウム, 2022.
Abstract | BibTeX | Tags: Activity Recognition, behavior change, Wearable sensing | Links:
@conference{ipsjbit-onob,
title = {スマートウォッチを用いたマスク装着の促進手法},
author = {小野翔多 and 西山勇毅 and 瀬崎薫},
url = {http://www.sig-bti.jp/event/kickoffinfo.html
http://www.sig-bti.jp/event/img/Proceedings%20of%20%20IPSJBTI%20Kickoff%20Symposium.pdf},
year = {2022},
date = {2022-04-16},
urldate = {2022-04-16},
booktitle = {情報処理学会 IoT行動変容学研究グループ キックオフシンポジウム},
pages = {56--57},
abstract = {新型コロナウイルス感染症が世界的に蔓延しており,感染拡大を予防するために,マスクの装着などの飛沫感染のリスクを下げる行動が求められている [1].感染リスクを低下させるためには、常時マスクを装着することが望ましいが,無意識のうちにマスク非装着のまま行動してしまうことがしばしば発生する.マスク装着を効果的に促すためには,個々人のマスク装着状態を自動検知し,その状態に応じてユーザに行動変容を促すことが求められる.しかし,これまでのところ,マスク装着状態を市販の端末のみを用いて常時検出する手法はまだ提案されていない.本稿では,スマートウォッチに搭載されている複数のセンサを用いてマスク装着状態を自動検知し,マスク非装着のユーザに通知することで,マスク装着の行動を促進させる手法を提案する.},
keywords = {Activity Recognition, behavior change, Wearable sensing},
pubstate = {published},
tppubtype = {conference}
}
小野翔多, 西山勇毅, 瀬崎薫
ウェアラブルデバイスのマイクを用いたマスク装着状態の検知に向けて Conference
第102回MBL・第73回UBI合同研究発表会, online, 2022.
Abstract | BibTeX | Tags: スマートウォッチ, マスク装着情報, 感染症予防, 機械学習, 音声データ | Links:
@conference{nokeyb,
title = {ウェアラブルデバイスのマイクを用いたマスク装着状態の検知に向けて},
author = {小野翔多 and 西山勇毅 and 瀬崎薫},
url = {https://www.ipsj.or.jp/kenkyukai/event/mbl102ubi73.html},
year = {2022},
date = {2022-03-07},
urldate = {2022-03-07},
booktitle = {第102回MBL・第73回UBI合同研究発表会},
address = {online},
abstract = {感染症予防において,マスクの装着は飛沫による感染症への感染リスクを低下させる有効な手段の一つである.日常生活中におけるマスク装着の有無やその種類を自動的に検出できれば,感染リスクの判定やJust-in-Timeでの注意喚起,行動記録など様々な応用サービスが実現可能になる.しかし,映像処理や専用機器を用いずに,日常生活中において自動的にマスクの装着状態を検知する手法はまだ提案されていない.本研究では,市販のスマートウォッチの内蔵マイクのみを用いてマスクの装着状態を検出する.マスク装着時の音声特性調査とマスク装着状態判定モデルの評価実験から,マスク装着時・未装着時の音声データと機械学習を用いてマスク装着状態を検知できる可能性が示唆された.},
keywords = {スマートウォッチ, マスク装着情報, 感染症予防, 機械学習, 音声データ},
pubstate = {published},
tppubtype = {conference}
}
牛島秀暢, 西山勇毅, 瀬崎薫
タクシー車両を用いたマイクロモビリティ再配置 Conference Award
情報処理学会 第84回全国大会(愛媛大学), 情報処理学会, 2022.
BibTeX | Tags: | Links:
@conference{ipsj2022_ushijima,
title = {タクシー車両を用いたマイクロモビリティ再配置},
author = {牛島秀暢 and 西山勇毅 and 瀬崎薫},
url = {https://www.ipsj.or.jp/event/taikai/84/index.html},
year = {2022},
date = {2022-03-05},
urldate = {2022-03-05},
booktitle = {情報処理学会 第84回全国大会(愛媛大学)},
publisher = {情報処理学会},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
小松勇輝, 下条和暉, 西山勇毅, 瀬崎薫
腕時計型ウェアラブルデバイスを用いた会話時間計測手法の構築に向けて Conference Award
情報処理学会 第84回全国大会(愛媛大学), 情報処理学会, 2022.
BibTeX | Tags: | Links:
@conference{ipsj2022_komatsu,
title = {腕時計型ウェアラブルデバイスを用いた会話時間計測手法の構築に向けて},
author = {小松勇輝 and 下条和暉 and 西山勇毅 and 瀬崎薫},
url = {https://www.ipsj.or.jp/event/taikai/84/index.html},
year = {2022},
date = {2022-03-05},
urldate = {2022-03-05},
booktitle = {情報処理学会 第84回全国大会(愛媛大学)},
publisher = {情報処理学会},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
小野翔多, 山崎託, 三好匠, 西山勇毅, 瀬崎薫
[奨励講演] 移動体通信併用型MANETにおける端末密度を用いた中継領域制御 Conference
電子情報通信学会 情報通信マネジメント研究会(ICM), online, 2022.
Abstract | BibTeX | Tags: MANET, モバイルネットワーク, 中継領域, 通信負荷 | Links:
@conference{nokey,
title = {[奨励講演] 移動体通信併用型MANETにおける端末密度を用いた中継領域制御},
author = {小野翔多 and 山崎託 and 三好匠 and 西山勇毅 and 瀬崎薫},
url = {https://www.ieice.org/ken/program/index.php?tgs_regid=55edfba9b2118ae5769f94e16eeacecd10dd08f2d3aaa7122a8fb958ddce74ee&tgid=IEICE-ICM},
year = {2022},
date = {2022-03-04},
urldate = {2022-03-04},
booktitle = {電子情報通信学会 情報通信マネジメント研究会(ICM)},
address = {online},
abstract = {Mobile ad-hoc network(MANET)は,端末間の通信のみで自律分散的にネットワークを構築できる.
しかし,通信ネットワーク構築時に制御メッセージを全方位にフラッディングするため,通信資源を過剰に消費する.
位置情報を収集できる端末が通信ネットワーク構築に参加する環境では,端末の位置情報を組み合わせることで,より効率的なフラッディングが可能になると考えられる.
本稿では,端末の位置情報に基づいて仮想通信領域を作成し,その領域内の端末にのみフラッディングすることで,経路探索を効率化する手法を提案する.
シミュレーションによる評価の結果,提案手法は仮想通信領域を柔軟に作成し,過剰な通信資源消費の抑制と通信遅延の削減を実現できることが分かった.},
key = {MANET,位置情報,モバイルネットワーク,中継領域},
keywords = {MANET, モバイルネットワーク, 中継領域, 通信負荷},
pubstate = {published},
tppubtype = {conference}
}
西山勇毅, 瀬崎薫
スマートフォンを用いたベビーカーのコンテキスト検知に向けた一検討 Conference
電子情報通信学会総合大会(オンライン), 電子情報通信学会, 2022.
Abstract | BibTeX | Tags: Activity Recognition, context-awareness, Mobile sensing | Links:
@conference{ieice2022,
title = {スマートフォンを用いたベビーカーのコンテキスト検知に向けた一検討},
author = {西山勇毅 and 瀬崎薫},
url = {https://www.ieice-taikai.jp/2022general/jpn/index.html},
year = {2022},
date = {2022-03-01},
urldate = {2022-03-01},
booktitle = {電子情報通信学会総合大会(オンライン)},
publisher = {電子情報通信学会},
abstract = {ベビーカーは,子供がいる家庭の約70%が所有し,週に一回以上利用する家庭は73.8%であると報告されるなど,保有率・利用率ともに高い.ベビーカーは乳幼児を運搬するため,安全性と快適性が高く求められるが,街中・施設内において安全・快適な走行・滞在可能なルートや場所,時間を手軽に知ることは難しい.これらの情報を検知することで,様々な応用アプリケーションを実現できる.そこで本稿では,スマートフォンを用いたベビーカー移動時の急停止や段差との衝突,路面状態といったベビーカー移動に関するコンテキスト検知の可能性を調査し,その結果を報告する.},
keywords = {Activity Recognition, context-awareness, Mobile sensing},
pubstate = {published},
tppubtype = {conference}
}
笠原有貴, 西山勇毅, 瀬崎薫
ウェアラブルデバイスを用いた子育てコンテキストの検知に向けて Conference
研究報告ヒューマンコンピュータインタラクション研究会(CHI), 情報処理学会, 石垣島, 2022.
Abstract | BibTeX | Tags: モバイル・ウェアラブルセンシング, 子育てコンテキスト, 行動認識 | Links:
@conference{jchi2022_kasahara,
title = {ウェアラブルデバイスを用いた子育てコンテキストの検知に向けて},
author = {笠原有貴 and 西山勇毅 and 瀬崎薫},
url = {http://www.sighci.jp/events/sig/196},
year = {2022},
date = {2022-01-11},
urldate = {2022-01-11},
booktitle = {研究報告ヒューマンコンピュータインタラクション研究会(CHI)},
publisher = {情報処理学会},
address = {石垣島},
abstract = {女性の社会進出や核家族化,産後うつ問題など,子育て環境は大きく変化しており,子育ての効率
化や子育て支援は社会的に大きな課題となっている.本研究では,近年普及傾向にあるウェアラブルデバイスを用いて,ミルクやオムツ替え,お散歩など「親」が「乳幼児」に行う子育て行動の検知技術の開発を行う.子育て中のモーションデータを腕時計型のウェアラブルデバイスに搭載されたモーションセンサを用いて収集し,収集データと機械学習を用いて子育てコンテキストの検知モデルを構築する.本稿では,9種類の子育てコンテキストを定義し,子育てコンテキストの検知モデルの構築とその精度評価を行なった.},
keywords = {モバイル・ウェアラブルセンシング, 子育てコンテキスト, 行動認識},
pubstate = {published},
tppubtype = {conference}
}
Zengyi Han, Xuefu Dong, Yuuki Nishiyama, Kaoru Sezaki
Preliminary Study for Classifying Baby Stroller-related Parenting using Smartphones Book Chapter
In: Ahad, Md Atiqur Rahman; Inoue, Sozo; Roggen, Daniel; Fujinami, Kaori (Ed.): Activity and Behavior Computing, Springer Singapore, UK, 2022.
Abstract | BibTeX | Tags: | Links:
@inbook{abc2022_han,
title = {Preliminary Study for Classifying Baby Stroller-related Parenting using Smartphones},
author = {Zengyi Han and Xuefu Dong and Yuuki Nishiyama and Kaoru Sezaki},
editor = {Md Atiqur Rahman Ahad and Sozo Inoue and Daniel Roggen and Kaori Fujinami},
url = {https://abc-research.github.io/ },
year = {2022},
date = {2022-10-27},
urldate = {2022-10-27},
booktitle = {Activity and Behavior Computing},
publisher = {Springer Singapore},
address = {UK},
abstract = {The stroller, as a necessary tool for parents' daily lives of infant care, is rich in information about babysitting-related, however, they are unexplored. Existing stroller studies usually focus on the hardware aspects such as automatic braking and self-propelling, leaving less attention on infant mobility. Nevertheless, such potential information might open up new perspectives to urban studies, physiology studies, and studies in other fields. Therefore, to extract the potential information from everyday stroller usage, we proposed the idea of leveraging ubiquitous devices such as smartphones to automatically monitor different stroller-related behaviors. Two built-in inertial measurement units (IMU) could enable a daily stroll-related interaction log, analysis, and eventually better parenting.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
Issey Sukeda, Hiroaki Murakami, Yuuki Nishiyama, Hiroaki Murakami, Yoshihiro Kawahara
Poster abstract: Recursive Queueing Estimation Using Smartphone-based Acoustic Ranging Inproceedings
In: Proceedings of the 20th Conference on Embedded Networked Sensor Systems, Boston, USA, Association for Computing Machinery, New York, NY, USA, 2022.
BibTeX | Tags: Acoustic sensing, Mobile sensing, queueing
@inproceedings{sensys2022_sukeda,
title = {Poster abstract: Recursive Queueing Estimation Using Smartphone-based Acoustic Ranging},
author = {Issey Sukeda and Hiroaki Murakami and Yuuki Nishiyama and Hiroaki Murakami and Yoshihiro Kawahara},
year = {2022},
date = {2022-11-06},
urldate = {2022-11-06},
booktitle = {Proceedings of the 20th Conference on Embedded Networked Sensor Systems, Boston, USA},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {SenSys '22},
keywords = {Acoustic sensing, Mobile sensing, queueing},
pubstate = {published},
tppubtype = {inproceedings}
}
Ryoto Suzuki, Yuuki Nishiyama, Hiroaki Murakami, Yoshihiro Kawahara, Kaoru Sezaki
Poster abstract: Room Scale Localization Improvement Utilizing Stay Time Characteristics of Each Room Inproceedings
In: Proceedings of the 20th Conference on Embedded Networked Sensor Systems, Boston, USA, Association for Computing Machinery, New York, NY, USA, 2022.
BibTeX | Tags: Bluetooth low energy, iBeacon, Indoor localization, Received signal strength indicator
@inproceedings{sensys2022_suzuki,
title = {Poster abstract: Room Scale Localization Improvement Utilizing Stay Time Characteristics of Each Room},
author = {Ryoto Suzuki and Yuuki Nishiyama and Hiroaki Murakami and Yoshihiro Kawahara and Kaoru Sezaki},
year = {2022},
date = {2022-11-06},
urldate = {2022-11-06},
booktitle = {Proceedings of the 20th Conference on Embedded Networked Sensor Systems, Boston, USA},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {SenSys '22},
keywords = {Bluetooth low energy, iBeacon, Indoor localization, Received signal strength indicator},
pubstate = {published},
tppubtype = {inproceedings}
}
Liqiang Xu, Yuuki Nishiyama, Masamichi Shimosaka, Kota Tsubouchi, Kaoru Sezaki
Poster abstract: Convolutional Compressed Sensing for Smartphone Acceleration Data Compression Inproceedings
In: Proceedings of the 20th Conference on Embedded Networked Sensor Systems, Boston, USA, Association for Computing Machinery, New York, NY, USA, 2022.
BibTeX | Tags: Acceleration data, Compressed sensing, Convolutional neural network, Smartphone sensor
@inproceedings{sensys2022_xu,
title = {Poster abstract: Convolutional Compressed Sensing for Smartphone Acceleration Data Compression},
author = {Liqiang Xu and Yuuki Nishiyama and Masamichi Shimosaka and Kota Tsubouchi and Kaoru Sezaki},
year = {2022},
date = {2022-11-06},
urldate = {2022-11-06},
booktitle = {Proceedings of the 20th Conference on Embedded Networked Sensor Systems, Boston, USA},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {SenSys '22},
keywords = {Acceleration data, Compressed sensing, Convolutional neural network, Smartphone sensor},
pubstate = {published},
tppubtype = {inproceedings}
}