Early Steps in Automated Behavior Mapping via Indoor Sensors
dc.contributor.author | Arsan, Taner | |
dc.contributor.author | Kepez, Orçun | |
dc.date.accessioned | 2019-06-27T08:01:14Z | |
dc.date.available | 2019-06-27T08:01:14Z | |
dc.date.issued | 2017 | |
dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
dc.department | Fakülteler, Sanat ve Tasarım Fakültesi, İç Mimarlık ve Çevre Tasarımı Bölümü | en_US |
dc.description.abstract | Behavior mapping (BM) is a spatial data collection technique in which the locational and behavioral information of a user is noted on a plan layout of the studied environment. Among many indoor positioning technologies we chose Wi-Fi BLE beacon and ultra-wide band (UWB) sensor technologies for their popularity and investigated their applicability in BM. We tested three technologies for error ranges and found an average error of 1.39 m for Wi-Fi in a 36 m(2) test area (6m x 6 m) 0.86 m for the BLE beacon in a 37.44 m(2) test area (9.6 m x 3.9 m) and 0.24 m for ultra-wide band sensors in a 36 m(2) test area (6 m x 6 m). We simulated the applicability of these error ranges for real-time locations by using a behavioral dataset collected from an active learning classroom. We used two UWB tags simultaneously by incorporating a custom-designed ceiling system in a new 39.76 m(2) test area (7.35 m x 5.41 m). We considered 26 observation points and collected data for 180 s for each point (total 4680) with an average error of 0.2072 m for 23 points inside the test area. Finally we demonstrated the use of ultra-wide band sensor technology for BM. | en_US] |
dc.identifier.citation | 9 | |
dc.identifier.doi | 10.3390/s17122925 | en_US |
dc.identifier.issn | 1424-8220 | en_US |
dc.identifier.issn | 1424-8220 | |
dc.identifier.issue | 12 | |
dc.identifier.pmid | 29258178 | en_US |
dc.identifier.scopus | 2-s2.0-85040359009 | en_US |
dc.identifier.scopusquality | Q1 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12469/312 | |
dc.identifier.uri | https://doi.org/10.3390/s17122925 | |
dc.identifier.volume | 17 | en_US |
dc.identifier.wos | WOS:000423285800224 | en_US |
dc.institutionauthor | Arsan, Taner | en_US |
dc.institutionauthor | Arsan, Taner | |
dc.institutionauthor | Kepez, Orçun | |
dc.language.iso | en | en_US |
dc.publisher | MDPI | en_US |
dc.relation.journal | Sensors | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Sensors and technologies for indoor localization systems | en_US |
dc.subject | Positioning strategies and algorithms | en_US |
dc.subject | Behavior mapping | en_US |
dc.subject | Activity monitoring | en_US |
dc.subject | Ultra-wide band sensors | en_US |
dc.title | Early Steps in Automated Behavior Mapping via Indoor Sensors | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 7959ea6c-1b30-4fa0-9c40-6311259c0914 | |
relation.isAuthorOfPublication | 0815099a-9281-471b-b5c2-832d10ad983d | |
relation.isAuthorOfPublication.latestForDiscovery | 7959ea6c-1b30-4fa0-9c40-6311259c0914 |
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