{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,24]],"date-time":"2025-08-24T01:52:26Z","timestamp":1756000346515,"version":"3.41.0"},"reference-count":36,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2018,9,18]],"date-time":"2018-09-18T00:00:00Z","timestamp":1537228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100002241","name":"Japan Science and Technology Agency","doi-asserted-by":"publisher","award":["CREST JP-MJCR15E2"],"award-info":[{"award-number":["CREST JP-MJCR15E2"]}],"id":[{"id":"10.13039\/501100002241","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP16H06539, JP17H04679"],"award-info":[{"award-number":["JP16H06539, JP17H04679"]}],"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":[[2018,9,18]]},"abstract":"<jats:p>This study presents a new method for estimating the physical distance between two locations using Wi-Fi signals from APs observed by Wi-Fi signal receivers such as smartphones. We assume that a Wi-Fi signal strength vector is observed at location A and another Wi-Fi signal strength vector is observed at location B. With these two Wi-Fi signal strength vectors, we attempt to estimate the physical distance between locations A and B. In this study, we estimate the physical distance based on supervised machine learning and do not use labeled training data collected in an environment of interest. Note that, because signal propagation is greatly affected by obstacles such as walls, precisely estimating the distance between locations A and B is difficult when there is a wall between locations A and B. Our method first estimates whether or not there is a wall between locations A and B focusing on differences in signal propagation properties between 2.4 GHz and 5 GHz signals, and then estimates the physical distance using a neural network depending on the presence of walls. Because our approach is based on Wi-Fi signal strengths and does not require a site survey in an environment of interest, we believe that various context-aware applications can be easily implemented based on the distance estimation technique such as low-cost indoor navigation, the analysis and discovery of communities and groups, and Wi-Fi geo-fencing. Our experiment revealed that the proposed method achieved an MAE of about 3-4 meters and the performance is almost identical to an environment-dependent method, which is trained on labeled data collected in the same environment.<\/jats:p>","DOI":"10.1145\/3264940","type":"journal-article","created":{"date-parts":[[2018,9,19]],"date-time":"2018-09-19T11:58:41Z","timestamp":1537358321000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Estimating the Physical Distance between Two Locations with Wi-Fi Received Signal Strength Information Using Obstacle-aware Approach"],"prefix":"10.1145","volume":"2","author":[{"given":"Tomoya","family":"Nakatani","sequence":"first","affiliation":[{"name":"Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan"}]},{"given":"Takuya","family":"Maekawa","sequence":"additional","affiliation":[{"name":"Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan"}]},{"given":"Masumi","family":"Shirakawa","sequence":"additional","affiliation":[{"name":"Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan"}]},{"given":"Takahiro","family":"Hara","sequence":"additional","affiliation":[{"name":"Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan"}]}],"member":"320","published-online":{"date-parts":[[2018,9,18]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2486001.2486039"},{"key":"e_1_2_1_2_1","first-page":"203","article-title":"Support vector regression","volume":"11","author":"Basak Debasish","year":"2007","unstructured":"Debasish Basak , Srimanta Pal , and Dipak Chandra Patranabis . 2007 . Support vector regression . Neural Information Processing-Letters andReviews 11 , 10 (2007), 203 -- 224 . Debasish Basak, Srimanta Pal, and Dipak Chandra Patranabis. 2007. Support vector regression. Neural Information Processing-Letters andReviews 11, 10 (2007), 203--224.","journal-title":"Neural Information Processing-Letters andReviews"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1410012.1410023"},{"key":"e_1_2_1_4_1","volume-title":"CSCW 2002 Workshop: Ad hoc Communications and Collaboration in Ubiquitous Computing Environments.","author":"Choudhury Tanzeem","year":"2002","unstructured":"Tanzeem Choudhury and Alex Pentland . 2002 . The sociometer: A wearable device for understanding human networks . In CSCW 2002 Workshop: Ad hoc Communications and Collaboration in Ubiquitous Computing Environments. Tanzeem Choudhury and Alex Pentland. 2002. The sociometer: A wearable device for understanding human networks. In CSCW 2002 Workshop: Ad hoc Communications and Collaboration in Ubiquitous Computing Environments."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2971648.2971699"},{"key":"e_1_2_1_6_1","volume-title":"MobiQuitous","author":"Gordon Dawud","year":"2012","unstructured":"Dawud Gordon , Jan-Hendrik Hanne , Martin Berchtold , Takashi Miyaki , and Michael Beigl . 2012. Recognizing group activities using wearable sensors . In MobiQuitous 2012 . 350--361. Dawud Gordon, Jan-Hendrik Hanne, Martin Berchtold, Takashi Miyaki, and Michael Beigl. 2012. Recognizing group activities using wearable sensors. In MobiQuitous 2012. 350--361."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2009.090103"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pmcj.2016.12.001"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2493988.2494348"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2011.243"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2370216.2370282"},{"key":"e_1_2_1_12_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik","year":"2014","unstructured":"Diederik Kingma and Jimmy Ba . 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014). Diederik Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.5555\/1361492.1361494"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2607023.2610281"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2971648.2971651"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/MPRV.2006.60"},{"key":"e_1_2_1_17_1","volume-title":"UbiComp","author":"Krumm John","year":"2004","unstructured":"John Krumm and Ken Hinckley . 2004. The NearMe wireless proximity server . In UbiComp 2004 . 283--300. John Krumm and Ken Hinckley. 2004. The NearMe wireless proximity server. In UbiComp 2004. 283--300."},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/11428572_8"},{"key":"e_1_2_1_19_1","volume-title":"2013 International Conference on Indoor Positioning and Indoor Navigation (IPIN). 1--7.","author":"Zeinalipour-Yazti Demetrios","year":"2013","unstructured":"ChristosLaoudias, Demetrios Zeinalipour-Yazti , and Christos G Panayiotou . 2013 . Crowdsourced indoor localization for diverse devices through radiomap fusion . In 2013 International Conference on Indoor Positioning and Indoor Navigation (IPIN). 1--7. ChristosLaoudias, Demetrios Zeinalipour-Yazti, and Christos GPanayiotou. 2013. Crowdsourced indoor localization for diverse devices through radiomap fusion. In 2013 International Conference on Indoor Positioning and Indoor Navigation (IPIN). 1--7."},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2014.2335537"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/1571941.1571949"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2078316.2078320"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2750858.2806061"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3131898"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3090089"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2370216.2370440"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.5555\/2627435.2670313"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2370216.2370266"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/2971648.2971684"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2014.2382478"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/2667226"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/PLANS.2006.1650667"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-79576-6_9"},{"key":"e_1_2_1_34_1","volume-title":"13th USENIX Symposium on Networked Systems Design and Implementation (NSDI","author":"Vasisht Deepak","year":"2016","unstructured":"Deepak Vasisht , Swarun Kumar , and Dina Katabi . 2016 . Decimeter-level localization with a single Wi-Fi access point . In 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 2016). 165--178. Deepak Vasisht, Swarun Kumar, and Dina Katabi. 2016. Decimeter-level localization with a single Wi-Fi access point. In 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 2016). 165--178."},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2012.214"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/AINA.2005.286"}],"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\/3264940","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3264940","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3264940","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:08:00Z","timestamp":1750212480000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3264940"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,18]]},"references-count":36,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,9,18]]}},"alternative-id":["10.1145\/3264940"],"URL":"https:\/\/doi.org\/10.1145\/3264940","relation":{},"ISSN":["2474-9567"],"issn-type":[{"type":"electronic","value":"2474-9567"}],"subject":[],"published":{"date-parts":[[2018,9,18]]},"assertion":[{"value":"2018-02-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-09-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-09-18","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}