{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T08:03:03Z","timestamp":1773734583106,"version":"3.50.1"},"reference-count":44,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T00:00:00Z","timestamp":1671580800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP21H03428, JP21H05299, and JP21J10059"],"award-info":[{"award-number":["JP21H03428, JP21H05299, and JP21J10059"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2022,12,21]]},"abstract":"<jats:p>Indoor pedestrian dead reckoning (PDR) using embedded inertial sensors in smartphones has been actively studied in the ubicomp community. However, PDR relying only on inertial sensors suffers from the accumulation of errors from the sensors. Researchers have employed various indoor landmarks detectable by smartphone sensors such as magnetic fingerprints caused by elevators and Bluetooth signals from beacons with known coordinates to compensate for the errors. This study proposes a new type of indoor landmark that does not require additional device installation, e.g., beacons, and training data collection in a target environment, e.g., magnetic fingerprints, unlike existing landmarks. This study proposes the use of GPS signals received by a smartphone to correct the accumulated errors of the PDR. While it is impossible to locate the smartphone indoors using GPS satellites, the smartphone can receive signals at a window-side area through windows from satellites aligned with the orientation of the window normal. Based on this idea, we design a machine-learning-based module for detecting the proximity of a user to a window and the orientation of the window, which enables us to roughly determine the absolute coordinates of the smartphone and to correct the accumulated errors by referring to positions of window-side areas found in the floor plan of the environment. A key technical contribution of this study is designing the module, such that it can be trained based on data from environments other than the target environment yet work in any environment by extracting GPS-related information independent of wall orientation. We evaluated the effectiveness of the proposed method using sensor data collected in real environments.<\/jats:p>","DOI":"10.1145\/3569467","type":"journal-article","created":{"date-parts":[[2023,1,11]],"date-time":"2023-01-11T15:34:01Z","timestamp":1673451241000},"page":"1-36","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["GPS-assisted Indoor Pedestrian Dead Reckoning"],"prefix":"10.1145","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7259-6673","authenticated-orcid":false,"given":"Heng","family":"Zhou","sequence":"first","affiliation":[{"name":"Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7227-580X","authenticated-orcid":false,"given":"Takuya","family":"Maekawa","sequence":"additional","affiliation":[{"name":"Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,1,11]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2015.2478451"},{"key":"e_1_2_1_2_1","volume-title":"Ortega","author":"Abyarjoo Fatemeh","year":"2015","unstructured":"Fatemeh Abyarjoo, Armando Barreto, Jonathan Cofino, and Francisco R. Ortega. 2015. Implementing a sensor fusion algorithm for 3D orientation detection with inertial\/magnetic Sensors. In Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering, Vol. 305--310. Springer International Publishing, Cham."},{"key":"e_1_2_1_3_1","volume-title":"2010 International Conference on Indoor Positioning and Indoor Navigation. 1--5.","author":"Ascher Christian","unstructured":"Christian Ascher, Christoph Kessler, Matthias Wankerl, and Gert F. Trommer. 2010. Dual IMU indoor navigation with particle filter based map-matching on a smartphone. In 2010 International Conference on Indoor Positioning and Indoor Navigation. 1--5."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12102"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2966773"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/s150924595"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.3390\/s150100715"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2021.3102916"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPIN.2015.7346954"},{"key":"e_1_2_1_10_1","volume-title":"Pedestrian tracking using inertial sensors. Journal of Physical Agents (01","author":"Feliz Raul","year":"2009","unstructured":"Raul Feliz, Eduardo Zalama, and Jaime G\u00f3mez-Garc\u00eda-Bermejo. 2009. Pedestrian tracking using inertial sensors. Journal of Physical Agents (01 2009)."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCG.2005.140"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/GCCE.2016.7800337"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3408308.3427981"},{"key":"e_1_2_1_14_1","unstructured":"Google. 2018. ARCore. https:\/\/developers.google.com\/ar\/."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2989501"},{"key":"e_1_2_1_16_1","volume-title":"Activity recognition and semantic description for indoor mobile localization. Sensors 17 (03","author":"Guo Sheng","year":"2017","unstructured":"Sheng Guo, Xiong Hanjiang, Xianwei Zheng, and Yan Zhou. 2017. Activity recognition and semantic description for indoor mobile localization. Sensors 17 (03 2017), 649."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/78.978396"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPIN.2012.6418932"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/1839294.1839306"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/IC3TSN.2017.8284455"},{"key":"e_1_2_1_21_1","volume-title":"Design and implementation of pedestrian dead reckoning system on a mobile phone. IEICE Trans. Inf. Syst. 94-D","author":"Kamisaka Daisuke","year":"2011","unstructured":"Daisuke Kamisaka, Shigeki Muramatsu, Takeshi Iwamoto, and Hiroyuki Yokoyama. 2011. Design and implementation of pedestrian dead reckoning system on a mobile phone. IEICE Trans. Inf. Syst. 94-D (2011), 1137--1146."},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2014.2382568"},{"key":"e_1_2_1_23_1","volume-title":"Eung Ju Kim, and Jin Woo Song.","author":"Kim Yong Hun","year":"2019","unstructured":"Yong Hun Kim, Min Jun Choi, Eung Ju Kim, and Jin Woo Song. 2019. Magnetic-map-matching-aided pedestrian navigation using outlier mitigation based on multiple sensors and roughness weighting. Sensors 19, 21 (2019)."},{"key":"e_1_2_1_24_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-12654-3_3"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2639108.2639109"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3191749"},{"key":"e_1_2_1_28_1","volume-title":"6th World Multiconference on Systemics, Cybernetics and Information, Orlando, USA.","author":"Ladetto Quentin","unstructured":"Quentin Ladetto and Bertrand Merminod. 2002. An alternative approach to vision techniques-pedestrian navigation system based on digital magnetic compass and gyroscope integration. In 6th World Multiconference on Systemics, Cybernetics and Information, Orlando, USA."},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPIN.2017.8115887"},{"key":"e_1_2_1_30_1","first-page":"175","article-title":"Pedstrian Dead Reckoning---A solution to navigation in GPS signal degraded areas","volume":"59","author":"Mezentsev Oleg","year":"2005","unstructured":"Oleg Mezentsev, Gerard Lachapelle, and Jussi Collin. 2005. Pedstrian Dead Reckoning---A solution to navigation in GPS signal degraded areas? GEOMATICA 59 (2005), 175--182.","journal-title":"GEOMATICA"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351257"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPIN.2014.7275552"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2750858.2806061"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/PERCOM.2017.7917860"},{"key":"e_1_2_1_35_1","volume-title":"Analog Devices","author":"Scarlett Jim","year":"2007","unstructured":"Jim Scarlett. 2007. Enhancing the performance of pedometers using a single accelerometer. Application Note, Analog Devices (2007)."},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/2971648.2971684"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/2667226"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3328918"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/2307636.2307655"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341162.3343765"},{"key":"e_1_2_1_41_1","doi-asserted-by":"crossref","unstructured":"Shun Yoshimi Kohei Kanagu Masahiro Mochizuki Kazuya Murao and Nobuhiko Nishio. 2015. PDR trajectory estimation using pedestrian-space constraints: real world evaluations. In Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers (UbiComp\/ISWC'15 Adjunct). Association for Computing Machinery New York NY USA 1499--1508.","DOI":"10.1145\/2800835.2807949"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2017.2784386"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2015.2423326"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.3390\/s16050596"}],"container-title":["Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3569467","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3569467","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T20:52:34Z","timestamp":1752612754000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3569467"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,21]]},"references-count":44,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,12,21]]}},"alternative-id":["10.1145\/3569467"],"URL":"https:\/\/doi.org\/10.1145\/3569467","relation":{},"ISSN":["2474-9567"],"issn-type":[{"value":"2474-9567","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,21]]},"assertion":[{"value":"2023-01-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}