{"id":748,"date":"2020-09-13T05:30:43","date_gmt":"2020-09-13T14:30:43","guid":{"rendered":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/?p=748"},"modified":"2020-09-30T20:48:10","modified_gmt":"2020-10-01T05:48:10","slug":"%e5%8a%a9%e6%95%99%e3%81%ae%e8%a5%bf%e5%b1%b1%e3%81%8chasca2020%ef%bc%88acm-ubicomp2020-%e4%bd%b5%e8%a8%ad%e3%83%af%e3%83%bc%e3%82%af%e3%82%b7%e3%83%a7%e3%83%83%e3%83%97%ef%bc%89%e3%81%ab%e3%81%a6","status":"publish","type":"post","link":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/en\/2020\/09\/13\/%e5%8a%a9%e6%95%99%e3%81%ae%e8%a5%bf%e5%b1%b1%e3%81%8chasca2020%ef%bc%88acm-ubicomp2020-%e4%bd%b5%e8%a8%ad%e3%83%af%e3%83%bc%e3%82%af%e3%82%b7%e3%83%a7%e3%83%83%e3%83%97%ef%bc%89%e3%81%ab%e3%81%a6\/","title":{"rendered":"\u52a9\u6559\u306e\u897f\u5c71\u304cHASCA2020\uff08ACM UbiComp2020 \u4f75\u8a2d\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\uff09\u306b\u3066\u7814\u7a76\u767a\u8868\u300cUsing IOS for Inconspicuous Data Collection: A Real-World Assessment\u300d\u3092\u884c\u3044\u307e\u3057\u305f\uff01"},"content":{"rendered":"\n<p>\u52a9\u6559\u306e\u897f\u5c71\u304c\u3001<a href=\"https:\/\/ubicomp.org\/ubicomp2020\/\" target=\"_blank\" rel=\"noreferrer noopener\">ACM UbiComp2020<\/a>\u306e\u4f75\u8a2d\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7<a href=\"http:\/\/wellcomp.org\/2020\">HASCA2020<\/a>\u306b\u3066\u7814\u7a76\u767a\u8868\u3092\u884c\u307e\u3057\u305f\u3002<\/p>\n\n\n\n<p><\/p>\n\n\n<div class=\"tp_single_publication\"><span class=\"tp_single_author\">Yuuki Nishiyama, Denzil Ferreira, Wataru Sasaki, Tadashi Okoshi, Jin Nakazawa, Anind K Dey, Kaoru Sezaki: <\/span> <span class=\"tp_single_title\">Using IOS for Inconspicuous Data Collection: A Real-World Assessment<\/span>. <span class=\"tp_single_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers, <\/span><span class=\"tp_pub_additional_pages\">pp. 261\u2013266, <\/span><span class=\"tp_pub_additional_publisher\">Association for Computing Machinery, <\/span><span class=\"tp_pub_additional_address\">Virtual Event, Mexico, <\/span><span class=\"tp_pub_additional_year\">2020<\/span>, <span class=\"tp_pub_additional_isbn\">ISBN: 9781450380768<\/span>.<\/span><\/div>\n\n\n\n<p><\/p>\n\n\n<h2 class=\"tp_abstract\">Abstract<\/h2><p class=\"tp_abstract\">Mobile Crowd Sensing (MCS) is a method for collecting multiple sensor data from distributed mobile devices for understanding social and behavioral phenomena. The method requires collecting the sensor data 24\/7, ideally inconspicuously to minimize bias. Although several MCS tools for collecting the sensor data from an off-the-shelf smartphone are proposed and evaluated under controlled conditions as a benchmark, the performance in a practical sensing study condition is scarce, especially on iOS. In this paper, we assess the data collection quality of AWARE iOS, installed on off-the-shelf iOS smartphones with 9 participants for a week. Our analysis shows that more than 97% of sensor data, provided by hardware sensors (i.e., accelerometer, location, and pedometer sensor), is successfully collected in real-world conditions, unless a user explicitly quits our data collection application.<\/p>\n\n\n\n<!--more-->\n\n\n<h2 class=\"tp_links\">Links<\/h2><p class=\"tp_abstract\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/doi.org\/10.1145\/3410530.3414369\" title=\"https:\/\/doi.org\/10.1145\/3410530.3414369\" target=\"_blank\">https:\/\/doi.org\/10.1145\/3410530.3414369<\/a><\/li><li><i class=\"fab fa-github\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/github.com\/tetujin\/AWAREFramework-iOS\" title=\"https:\/\/github.com\/tetujin\/AWAREFramework-iOS\" target=\"_blank\">https:\/\/github.com\/tetujin\/AWAREFramework-iOS<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1145\/3410530.3414369\" title=\"Follow DOI:10.1145\/3410530.3414369\" target=\"_blank\">doi:10.1145\/3410530.3414369<\/a><\/li><\/ul><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u52a9\u6559\u306e\u897f\u5c71\u304c\u3001ACM UbiComp2020\u306e\u4f75\u8a2d\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7HASCA2020\u306b\u3066\u7814\u7a76\u767a\u8868\u3092\u884c\u307e\u3057\u305f\u3002<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_locale":"en_US","_original_post":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/?p=744"},"categories":[12,4],"tags":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/wp-json\/wp\/v2\/posts\/748"}],"collection":[{"href":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/wp-json\/wp\/v2\/comments?post=748"}],"version-history":[{"count":4,"href":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/wp-json\/wp\/v2\/posts\/748\/revisions"}],"predecessor-version":[{"id":765,"href":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/wp-json\/wp\/v2\/posts\/748\/revisions\/765"}],"wp:attachment":[{"href":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/wp-json\/wp\/v2\/media?parent=748"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/wp-json\/wp\/v2\/categories?post=748"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.mcl.iis.u-tokyo.ac.jp\/wp-json\/wp\/v2\/tags?post=748"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}