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
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. xx–xx, Boston, Massachusetts, 2023.
Abstract | BibTeX | Tags: | 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},
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 = {xx--xx},
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 = {},
pubstate = {published},
tppubtype = {inproceedings}
}
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－ Inproceedings
In: 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:
@inproceedings{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},
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 = {inproceedings}
}
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 Inproceedings
In: 研究報告ユビキタスコンピューティングシステム（UBI）, pp. 1 - 8, 2023.
@inproceedings{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 = {inproceedings}
}
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 Inproceedings
In: 研究報告ユビキタスコンピューティングシステム（UBI）, pp. 1 - 8, 2023.
@inproceedings{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 = {inproceedings}
}
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 Inproceedings
In: 電子情報通信学会 総合大会, 2023.
@inproceedings{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 = {inproceedings}
}
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 Inproceedings
In: 2023年電子情報通信学会総合大会, 2023.
@inproceedings{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 = {inproceedings}
}
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 Inproceedings
In: 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:
@inproceedings{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 = {inproceedings}
}
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 Inproceedings
In: 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:
@inproceedings{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 = {2022-03-17},
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 = {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), IEEE, Atlanta, USA, 2023.
Abstract | BibTeX | Tags: | 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/},
year = {2023},
date = {2023-03-13},
urldate = {2023-03-13},
booktitle = {IEEE International Conference on Pervasive Computing and Communications (PerCom)},
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 = {},
pubstate = {published},
tppubtype = {inproceedings}
}
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 Inproceedings
In: 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
@inproceedings{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},
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 = {inproceedings}
}
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 Inproceedings
In: 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:
@inproceedings{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 = {inproceedings}
}
Suxing Lyu, Yuuki Nishiyama, Kaoru Sezaki, Takahiko Kusakabe
Generic Trip Purpose Inference Modelling on Trip Chain Inproceedings
In: 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, pp. 1 - 2, 2023.
@inproceedings{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 = {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:
@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},
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}
}
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:
@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},
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}
}
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 Journal Article
In: GIS-理論と応用, 30 (2), pp. 85-90, 2022.
Abstract | BibTeX | Tags: ベクトルタイル, 人流データ, 全国規模, 可視化 | Links:
@article{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},
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 = {article}
}
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}
}
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}
}
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 Inproceedings
In: 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:
@inproceedings{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 = {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}
}
Riku Ishioka, Yuuki Nishiyama, Kota Tsubouchi, Kaoru Sezaki
Poster abstract: UV index estimation leveraging GNSS sensors on smartphones 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: GNSS, Passive mobile sensing, smartphone, UV index estimation
@inproceedings{sensys2022_ishioka,
title = {Poster abstract: UV index estimation leveraging GNSS sensors on smartphones},
author = {Riku Ishioka and Yuuki Nishiyama 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 = {GNSS, Passive mobile sensing, smartphone, UV index estimation},
pubstate = {published},
tppubtype = {inproceedings}
}
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}
}
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}
}
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 Inproceedings Award
In: 研究報告ユビキタスコンピューティングシステム（UBI）, pp. 1 - 7, 情報処理学会, 2022, ISSN: 2188-8698.
Abstract | BibTeX | Tags: | Links:
@inproceedings{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 = {inproceedings}
}
Suxing Lyu, Tianyang Han, Yuuki Nishiyama, Kaoru Sezaki, Takahiko Kusakabe
A Plug-in Memory Network for Trip Purpose Classification Inproceedings Open Access
In: Proceedings of the 30th International Conference on Advances in Geographic Information Systems, Association for Computing Machinery, Seattle, Washington, 2022, ISBN: 9781450395298.
Abstract | BibTeX | Tags: Human mobility, matrix factorization, memory network, trip purpose | Links:
@inproceedings{10.1145/3557915.3560969,
title = {A Plug-in Memory Network for Trip Purpose Classification},
author = {Suxing Lyu and Tianyang Han and Yuuki Nishiyama and Kaoru Sezaki and Takahiko Kusakabe},
url = {https://doi.org/10.1145/3557915.3560969},
doi = {10.1145/3557915.3560969},
isbn = {9781450395298},
year = {2022},
date = {2022-11-01},
urldate = {2022-11-01},
booktitle = {Proceedings of the 30th International Conference on Advances in Geographic Information Systems},
publisher = {Association for Computing Machinery},
address = {Seattle, Washington},
series = {SIGSPATIAL '22},
abstract = {Trip purpose plays a critical role in reflecting human mobility behavior. However, it is relatively difficult to determine. With the rapid growth of urban mobility and big mobile data, utilizing these data for trip purpose classification has been a long-term objective to enhance travel demand and behavior models used in urban planning. Although studies on this topic have been extensively conducted, most past research preferred relying on traveler attributes or long-term travel histories to achieve accurate results. These data could be privacy sensitive and often do not satisfy real-world scenarios. This study addresses the problem of classifying trip purpose by only space activity information to avoid privacy conflict. 1) External memories are collected from factorized components based on the non-negative Tucker decomposition scheme. 2) These memories are extended by the cross-attention mechanism to achieve feature augmentation. 3) Subsequently, a novel concept called "latent mode alignment" is proposed. By leveraging the linear characteristics of external memories, geographic contextual latent modes are represented and matched with travel activities; this procedure is called älignment." 4) The gate mechanism controls the eventual outputs for update. The proposed plug-in memory network (PMN), combined with baseline models, effectively outperforms the original settings. Moreover, combination models are validated with strong tolerance through missing data tests, which are common and problematic in real-world scenarios. The proposed PMN is a plug-and-play design that is easy to combine with newly developed classification models, and other memory collection methods can be expected.},
keywords = {Human mobility, matrix factorization, memory network, trip purpose},
pubstate = {published},
tppubtype = {inproceedings}
}
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 Inproceedings
In: 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:
@inproceedings{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 = {inproceedings}
}
Yuuki Nishiyama, Hiroaki Murakami, Ryoto Suzuki, Kazusato Oko, Issey Sukeda, Kaoru Sezaki, Yoshihiro Kawahara
MOCHA: Mobile Check-in Application for University Campuses Beyond COVID-19 Inproceedings Open Access
In: The Twenty-third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, ACM, Seoul, Republic of Korea, 2022, ISBN: 978-1-4503-9165-8/22/10.
Abstract | BibTeX | Tags: Bluetooth beacon, COVID-19, Mobile sensing, Shared space management, Social Implementation | Links:
@inproceedings{mobicovid22_nishiyama,
title = {MOCHA: Mobile Check-in Application for University Campuses Beyond COVID-19},
author = {Yuuki Nishiyama and Hiroaki Murakami and Ryoto Suzuki and Kazusato Oko and Issey Sukeda and Kaoru Sezaki and Yoshihiro Kawahara},
doi = {10.1145/3492866.3557736},
isbn = {978-1-4503-9165-8/22/10},
year = {2022},
date = {2022-10-18},
urldate = {2022-10-18},
booktitle = {The Twenty-third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing},
volume = {MobiHoc '22},
publisher = {ACM},
address = {Seoul, Republic of Korea},
abstract = {Users and operators of shared spaces must ensure safety in such areas to prevent the spread of COVID-19. Although each organization has operated a variety of safety-related systems, including contact tracing, congestion monitoring, and check-in services, it is unclear what elements, such as privacy protection level, benefits, and permission procedures, have promoted the usage of these systems. In this study, we created MOCHA, a platform for sharing and tracking room-level locations. This platform automatically detects visited places by scanning Bluetooth beacons in each room using smartphones and shares location data according to predefined user settings. The collected data is used for room-level contact tracing, congestion monitoring, and reservation services. According to >6,500 users' usage data for a year in a university, outlining the advantages of utilizing the app encouraged people to install the app, and reinforced connections in small private groups are encouraged to use the app continuously.},
keywords = {Bluetooth beacon, COVID-19, Mobile sensing, Shared space management, Social Implementation},
pubstate = {published},
tppubtype = {inproceedings}
}
Xuefu Dong, Zengyi Han, Yuuki Nishiyama, Kaoru Sezaki
DoubleCheck: Single-Handed Cycling Detection with a Smartphone Inproceedings
In: 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 268-274, 2022.
Abstract | BibTeX | Tags: | Links:
@inproceedings{smc2022_dong,
title = {DoubleCheck: Single-Handed Cycling Detection with a Smartphone},
author = {Xuefu Dong and Zengyi Han and Yuuki Nishiyama and Kaoru Sezaki},
doi = {10.1109/SMC53654.2022.9945380},
year = {2022},
date = {2022-10-09},
urldate = {2022-10-09},
booktitle = {2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)},
pages = {268-274},
abstract = {Riding bicycles with only one hand on the handlebar can severely undermine the operator’s steering capability and threaten road and transportation safety. Prior studies have exploited motion sensors to detect riding contexts and recognize related behaviors. Nevertheless, they fail to integrate a scheme to account for single-handed riding with elements crucial to danger prevention: awareness of the surroundings, response to danger, and convenient adoption. In this work, we proposed, designed, and implemented DoubleCheck: a smartphone-based real-time framework for cycling hand detection and distraction recognition. The method monitors handlebar holding on different road surfaces and recognizes hazardous distraction activities related to single-handed cycling using motion signals captured by a built-in inertial measurement unit in a handlebar-borne smartphone. It was designed on the premise that single-handed cycling enabled operators to adapt their body movements to different (often distracting) activities. We conducted an evaluation experiment using 22 participants on asphalt and pavement. The results indicate that DoubleCheck achieves an F1-score of 0.96 for hand detection and 0.69 for distraction recognition, demonstrating its efficacy as a candidate rider-safety precautionary measure.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Zengyi Han, Yuuki Nishiyama, Kaoru Sezaki
A Micro-mobility Sensing System to Portray Riding Styles Inproceedings
In: Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers, pp. 19–20, Association for Computing Machinery, USA and UK, 2022.
@inproceedings{ubicomp2022_han,
title = {A Micro-mobility Sensing System to Portray Riding Styles},
author = {Zengyi Han and Yuuki Nishiyama and Kaoru Sezaki},
year = {2022},
date = {2022-09-12},
urldate = {2022-09-12},
booktitle = {Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers},
pages = {19–20},
publisher = {Association for Computing Machinery},
address = {USA and UK},
series = {UbiComp '22},
abstract = {Riding style concerns the way a micro-mobility rider chooses to ride, and it plays a significant role in traffic safety. Portraying a rider’s
riding style is a useful way to guide them towards safer riding behaviors, and offer fine-grained information for insurance companies
and bike-sharing companies to provide better services. To this end, we propose a micro-mobility sensing system to portray riding
styles. Utilizing helmet-mounted and bicycle handle-mounted inertial sensors, our sensing system is able to monitor the micro-mobility
movement status, detect the maneuver behaviors, and the safety check condition of riders. With 10 participants’ experimental data,
we present the feasibility of detecting maneuver behavior and recording the data that characterize the rider’s riding style with our
sensing system, and therefore make it a viable addition to the micro-mobility.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Kazuki Shimojo, Zengyi Han, Yuuki Nishiyama, Kaoru Sezaki
A Preliminary Study for Detecting Visual Search Behaviors During Street Walking Using Earable Device Inproceedings
In: Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers, pp. 19–20, Association for Computing Machinery, USA and UK, 2022.
@inproceedings{ubicomp2022_shimojo,
title = {A Preliminary Study for Detecting Visual Search Behaviors During Street Walking Using Earable Device},
author = {Kazuki Shimojo and Zengyi Han and Yuuki Nishiyama and Kaoru Sezaki},
year = {2022},
date = {2022-09-12},
urldate = {2022-09-12},
booktitle = {Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers},
pages = {19–20},
publisher = {Association for Computing Machinery},
address = {USA and UK},
series = {UbiComp '22},
abstract = {Map applications on smartphones are powerful navigation tools for walking among places to visit for the first time and are used widely. On the other hand, checking the application tend to cause trouble on the road such as collisions with people, cars, and objects. To prevent the troubles, we need to detect the walker’s context regarding visual search behaviors and provide appropriate navigation information for the walker. In this paper, we propose a method to detect a walker’s context regarding visual search behaviors by using motion sensors on an earable device. We collected and investigated motion and gaze data from an earable device and gaze tracker respectively during street walking from five participants. Based on the investigation, we create a machine learning model for detecting looking around, smartphone, or normal during walking
and stopping conditions. Our evaluations show that our models can detect more than 95% of walking and stopping conditions, and 71% of three details conditions during walking, respectively},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Haoyu Zhuang, Liqiang Xu, Yuuki Nishiyama, Kaoru Sezaki
A preliminary study for monitoring hygiene behaviors by using multiple sensors on a wrist Inproceedings Self Archive
In: 研究報告ユビキタスコンピューティングシステム（UBI）, pp. 1–7, 2022, ISSN: 2188-8698.
Abstract | BibTeX | Tags: | Links:
@inproceedings{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 = {inproceedings}
}
荘昊昱, 韓増易, 西山勇毅, 瀬崎薫
Face-Touch Detection with Smartwatch by CNN: An Experimental Lab Study Inproceedings
In: 電子情報通信学会ソサイエティ大会, オンライン, 2022.
BibTeX | Tags:
@inproceedings{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 = {inproceedings}
}
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 Inproceedings
In: 電子情報通信学会ソサイエティ大会, オンライン, 2022.
BibTeX | Tags:
@inproceedings{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 = {inproceedings}
}
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 Inproceedings
In: 電子情報通信学会ソサイエティ大会, オンライン, 2022.
BibTeX | Tags:
@inproceedings{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 = {inproceedings}
}
Zengyi Han, Xuefu Dong, Yuuki Nishiyama, Kaoru Sezaki
Poster: Head Dynamics Enabled Riding Maneuver Prediction Inproceedings
In: Proceedings of the 20th Annual International Conference on Mobile Systems, Applications, and Services, Association for Computing Machinery, Portland, Oregon, 2022.
Abstract | BibTeX | Tags: Activity Recognition, Mobile sensing, Wearable sensing | Links:
@inproceedings{mobisys2022_han,
title = {Poster: Head Dynamics Enabled Riding Maneuver Prediction},
author = {Zengyi Han and Xuefu Dong and Yuuki Nishiyama and Kaoru Sezaki},
url = {https://www.sigmobile.org/mobisys/2022/},
year = {2022},
date = {2022-06-27},
urldate = {2022-06-27},
booktitle = {Proceedings of the 20th Annual International Conference on Mobile Systems, Applications, and Services},
publisher = {Association for Computing Machinery},
address = {Portland, Oregon},
series = {MobiSys '22},
abstract = {While micro-mobility brings convenience to the modern city, they also cause various social problems such as traffic accidents, casualties, and huge economic losses. Wearing protective equipment has become the primary recommendation for safe riding, but passive protection cannot prevent accidents from happening after all. Thus, timely predicting the rider's maneuver is essential for more active protection and buying more time to avoid potential accidents from happening. In this poster, we explore the feasibility of using riders’ head dynamics to predict their riding maneuvers. Through ten participants’ preliminary study, we observed that not only do riders’ head movements appear ahead of their maneuvers but also head movement patterns are distinct with different maneuver intentions. We then construct a deep learning network using Long Short Term Memory, achieving 89% of accuracy on maneuver prediction.},
keywords = {Activity Recognition, Mobile sensing, Wearable sensing},
pubstate = {published},
tppubtype = {inproceedings}
}
Yuki Komatsu, Kazuki Shimojo, Yuuki Nishiyama, Kaoru Sezaki
Toward Measuring Conversation Duration Using a Wristwatch-type Wearable Device Inproceedings
In: 2022 IEEE International Conference on Smart Computing (SMARTCOMP), IEEE Computer Society, Espoo, Finland, 2022.
BibTeX | Tags: Context-recognition, Conversation Events, Edge Processing, Sound Classification, Wearable Computing
@inproceedings{smartcomp2022_komatsu,
title = {Toward Measuring Conversation Duration Using a Wristwatch-type Wearable Device},
author = {Yuki Komatsu and Kazuki Shimojo and Yuuki Nishiyama and Kaoru Sezaki},
year = {2022},
date = {2022-06-24},
urldate = {2022-06-24},
booktitle = {2022 IEEE International Conference on Smart Computing (SMARTCOMP)},
publisher = {IEEE Computer Society},
address = {Espoo, Finland},
keywords = {Context-recognition, Conversation Events, Edge Processing, Sound Classification, Wearable Computing},
pubstate = {published},
tppubtype = {inproceedings}
}
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 Inproceedings
In: 研究報告ユビキタスコンピューティングシステム（UBI）, pp. 1 - 6, 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:
@inproceedings{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 = {inproceedings}
}
Liqiang Xu, Yuuki Nishiyama, Kaoru Sezaki
Enhancing Self-Protection: What Influences Human’s Epidemic Prevention Behavior during the COVID-19 Pandemic Inproceedings
In: Distributed, Ambient and Pervasive Interactions. Smart Living, Learning, Well-Being and Health, Art and Creativity: 10th International Conference, DAPI 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Virtual Event, June 26 – July 1, 2022, Proceedings, Part II, pp. 336–351, Springer-Verlag, Berlin, Heidelberg, 2022, ISBN: 978-3-031-05430-3.
Abstract | BibTeX | Tags: COVID-19, Infection prevention, Mobile sensing, Persuasive technology., Self-protection behavior, Self-Tracking | Links:
@inproceedings{10.1007/978-3-031-05431-0_23,
title = {Enhancing Self-Protection: What Influences Human’s Epidemic Prevention Behavior during the COVID-19 Pandemic},
author = {Liqiang Xu and Yuuki Nishiyama and Kaoru Sezaki},
url = {https://doi.org/10.1007/978-3-031-05431-0_23},
doi = {10.1007/978-3-031-05431-0_23},
isbn = {978-3-031-05430-3},
year = {2022},
date = {2022-06-01},
urldate = {2022-01-01},
booktitle = {Distributed, Ambient and Pervasive Interactions. Smart Living, Learning, Well-Being and Health, Art and Creativity: 10th International Conference, DAPI 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Virtual Event, June 26 – July 1, 2022, Proceedings, Part II},
pages = {336–351},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
abstract = {Under the circumstance of the rapid spread of the COVID-19 pandemic, enhancing human’s awareness of self-protection is one practical method to slow down the epidemic. In this study, we utilize mobile sensing to track human activity and guide human’s epidemic prevention behavior by gamified feedback techniques by our developed application. Virtually, human’s self-protection awareness is affected by many factors and the measures to enhance people’s self-protection behavior against the epidemic COVID-19 has always been an unresolved issue. In order to search for factors that influence human’s self-protection behavior, we analyzed the relationships between various human activities and the percentage complete of human’s self-protection behavior and we have extracted some more general conclusions from the results. Based on our data analysis results, we also made some proposals to enhance self-protection behavior. Meanwhile, our study illustrates the effectiveness of the method that analyzes human self-protection behavior through mobile sensing. Our study also validates the effectiveness of persuasive technology on human’s self-protection behavior against the COVID-19 pandemic and therefore we advocate enhancing human’s self-protection awareness through external intervention and guidance by smart device.},
keywords = {COVID-19, Infection prevention, Mobile sensing, Persuasive technology., Self-protection behavior, Self-Tracking},
pubstate = {published},
tppubtype = {inproceedings}
}
Yuki Kasahara, Yuuki Nishiyama, Kaoru Sezaki
Detecting Childcare Activities Using an Off-the-shelf Smartwatch Inproceedings
In: 2022 IEEE International Conference on Smart Computing (SMARTCOMP), IEEE Computer Society, Espoo, Finland, 2022.
BibTeX | Tags: Activity Recognition, Childcare Activity, Wearable sensing
@inproceedings{smartcomp2022_kasahara,
title = {Detecting Childcare Activities Using an Off-the-shelf Smartwatch},
author = {Yuki Kasahara and Yuuki Nishiyama and Kaoru Sezaki},
year = {2022},
date = {2022-06-01},
urldate = {2022-06-01},
booktitle = {2022 IEEE International Conference on Smart Computing (SMARTCOMP)},
publisher = {IEEE Computer Society},
address = {Espoo, Finland},
keywords = {Activity Recognition, Childcare Activity, Wearable sensing},
pubstate = {published},
tppubtype = {inproceedings}
}
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 Inproceedings
In: 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, pp. 56–57, 2022.
Abstract | BibTeX | Tags: Activity Recognition, behavior change, Wearable sensing | Links:
@inproceedings{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 = {inproceedings}
}
Xuefu Dong, Zengyi Han, Yuuki Nishiyama, Kaoru Sezaki
DoubleCheck: Detecting Single-Hand Cycling with Inertial Measurement Unit of Smartphone Inproceedings
In: IEEE International Conference on Pervasive Computing and Communications (PerCom), IEEE, Pisa, Italy, 2022, ISBN: 978-1-6654-1648-1.
Abstract | BibTeX | Tags: | Links:
@inproceedings{percom2022_dong,
title = {DoubleCheck: Detecting Single-Hand Cycling with Inertial Measurement Unit of Smartphone},
author = {Xuefu Dong and Zengyi Han and Yuuki Nishiyama and Kaoru Sezaki},
doi = {10.1109/PerComWorkshops53856.2022.9767429},
isbn = {978-1-6654-1648-1},
year = {2022},
date = {2022-03-21},
urldate = {2022-03-21},
booktitle = {IEEE International Conference on Pervasive Computing and Communications (PerCom)},
publisher = {IEEE},
address = {Pisa, Italy},
abstract = {Riding bikes with only one hand on the handlebar can severely undermine the steering capability of riders and risk road safety. In this study, we propose a first detection framework for monitoring single-hand cycling on bicycle travel, called DoubleCheck. It is based on the premise that riders adapt their body movement during single-hand cycling, which is distinguishable to the sensors even amid noise from the exasperate road surface. The system can detect handlebar-holding under different road conditions using motion signals from a built-in inertial measurement unit (IMU) in a handlebar-mounted smartphone. We implemented the system and invited 10 participants for our evaluation experiment. Our results show that DoubleCheck achieved an F1-score of 0.94 for hand detection, proving its efficacy for real-life implementation to improve road safety.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
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 Inproceedings
In: 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:
@inproceedings{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},
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 = {inproceedings}
}
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 Inproceedings Award
In: 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:
@inproceedings{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 = {inproceedings}
}
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 Inproceedings Award
In: 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:
@inproceedings{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 = {inproceedings}
}
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 Inproceedings
In: 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:
@inproceedings{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 = {inproceedings}
}
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 Inproceedings
In: 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:
@inproceedings{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 = {inproceedings}
}
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 Inproceedings
In: 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:
@inproceedings{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 = {inproceedings}
}
Shota Ono, Yuuki Nishiyama, Kaoru Sezaki
Detecting Face-Mask Wearing Status Using Motion Sensors in Commercially Available Smartwatches Inproceedings
In: 2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom), pp. 107-112, 2022.
BibTeX | Tags: | Links:
@inproceedings{9982766,
title = {Detecting Face-Mask Wearing Status Using Motion Sensors in Commercially Available Smartwatches},
author = {Shota Ono and Yuuki Nishiyama and Kaoru Sezaki},
doi = {10.1109/HealthCom54947.2022.9982766},
year = {2022},
date = {2022-01-01},
booktitle = {2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)},
pages = {107-112},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
西山勇毅, 柿野優衣, 中縁嗣, 野田悠加, 羽柴彩月, 山田佑亮, 佐々木航, 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
感染症流行時におけるスマートフォンを用いた 大学生の身体活動量分析 Journal Article
In: 情報処理学会論文誌 [特集：ユビキタスコンピューティングシステム（X）] , 62 (10), pp. 1630–1643, 2021.
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{nishiyama2021_sfcgo_ipsj,
title = {感染症流行時におけるスマートフォンを用いた 大学生の身体活動量分析},
author = {西山勇毅 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 佐々木航 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/1001/00213189/},
doi = {10.20729/00213189},
year = {2021},
date = {2021-10-01},
journal = {情報処理学会論文誌 [特集：ユビキタスコンピューティングシステム（X）] },
volume = {62},
number = {10},
pages = {1630--1643},
abstract = { 新型コロナウイルス感染症（COVID-19）の世界的な感染拡大にともない，多くの大学ではキャンパス内での感染予防のために，キャンパスの封鎖とインターネット越しに授業を配信するオンライン授業が導入され，学生たちは自宅から授業に参加している．このような在宅中心の新しい生活様式は，感染予防効果が見込める一方で，運動不足による二次的な健康被害が懸念される．新しい生活様式における大学生の身体活動の実態，特に学生の属性や時間帯ごとの身体活動量とその内容を明らかにすることは，二次的な健康被害を予防するうえで必要不可欠である．そこで本研究では，日常生活中の身体活動データ（歩数と6種類の行動種別）を大学生が所有するスマートフォンを用いて自動収集し，大学生の身体活動量を明らかにする．身体活動データは，必修の体育授業を履修する大学1年生305名から10週間収集した．その結果，通学（7時から10時）や教室での授業，課外活動（11時から24時）の時間帯における歩数の減少と静止時間の長時間化が明らかになった．本結果は，新しい生活様式における大学生活が平日の身体活動量の低下を招く可能性を示唆する．
With the spreading of the new coronavirus infection (COVID-19) worldwide, several universities have closed their campuses to prevent the spread of infection. Consequently, university classes are being held over the Internet, and students attend these classes from their homes. While the COVID-19 pandemic is expected to be prolonged, the online-centric lifestyle has raised concerns about secondary health issues caused by reduced physical activity (PA). However, the actual status of PA among college students has not yet been examined in Japan. Hence, in this study, we collected daily PA data (including the data corresponding to the number of steps taken and the data associated with six types of activities) by employing off-the-shelf smartphones and thereby analyzing the PA changes of college students. The PA data were collected over a period of ten weeks from 305 first-year college students who were attending a mandatory class of physical education at the university. The obtained results indicate that the decrease in commuting time (7 AM to 10 AM), classroom time, and extracurricular activity time (11 AM to 12 AM) has led to a decrease in PA on weekdays owing to reduced unplanned exercise opportunities. The results suggest that college life in an online-centric lifestyle may lead to a decrease in PA on weekdays.},
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}
}
西山勇毅, 川原圭博, 瀬崎薫
MOCHA: Bluetoothビーコンを用いた学内位置情報サービスの開発・運用 Journal Article Open Access
In: 画像電子学会誌, 50 (3), pp. 459-461, 2021, (ウィズコロナ・アフターコロナに向けた安心・安全・便利なキャンパスを目指して).
Abstract | BibTeX | Tags: Bluetoothビーコン, COVID-19, アフターコロナ, ウィズコロナ, 位置情報サービス, 学内システム, 開発・運用 | Links:
@article{iieej2021_mocha,
title = {MOCHA: Bluetoothビーコンを用いた学内位置情報サービスの開発・運用},
author = {西山勇毅 and 川原圭博 and 瀬崎薫},
url = {https://www.iieej.org/journal-of-the-society/},
year = {2021},
date = {2021-08-01},
journal = {画像電子学会誌},
volume = {50},
number = {3},
pages = {459-461},
publisher = {画像電子学会},
abstract = {新型コロナウイルス感染症（COVID-19）の世界的な感染拡大により，感染症予防策の一つとして多くの大学では，オンライン授業や対面とオンライン授業を併用するハイブリッド授業を用いて教育・研究機会を提供してきた．2021年に入ってからは，多くの大学では，完全オンライン授業からハイブリッド・対面授業に移行しつつある．しかし，COVID-19 は常に変異しており，感染症の再流行も懸念されている．本格的な対面授業や研究活動の再開に向けて，学内管理施設における安心・安全の確保のためには，施設内における人々の滞在状況や人流・接触状況などを把握できることが望ましい．また，これらの情報は，アフターコロナにおいても，部屋の予約や道案内，場所に応じたリマインド機能などの DX 基盤としても活用できる．一方で，位置情報利用におけるプライバシーの確保やインセンティブ設計，開発・運用体制など実現には，技術以外にも多くの課題が存在する．},
note = {ウィズコロナ・アフターコロナに向けた安心・安全・便利なキャンパスを目指して},
keywords = {Bluetoothビーコン, COVID-19, アフターコロナ, ウィズコロナ, 位置情報サービス, 学内システム, 開発・運用},
pubstate = {published},
tppubtype = {article}
}