Publication
Intelligent beacon location and fingerprinting
| dc.contributor.author | Martins, Pedro | |
| dc.contributor.author | Abbasi, Maryam | |
| dc.contributor.author | Sa, Filipe | |
| dc.contributor.author | Celiclio, Jose | |
| dc.contributor.author | Morgado, Francisco | |
| dc.contributor.author | Caldeira, Filipe | |
| dc.date.accessioned | 2019-05-29T15:01:26Z | |
| dc.date.available | 2019-05-29T15:01:26Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | The complex way radio waves propagate indoors, leads to the derivation of location using fingerprinting techniques. In this cases, location is computed relying on WiFi signals strength mapping. Recent Bluetooth Low Energy (BLE) provides new opportunities to explore positioning. Indoor location identification plays a fundamental role as a business and personal level. At a business level, indoor location pinpointing where GPS signal is nonexistent is used to advise users and send push notifications (e.g., stores publicity, guide persons with special needs, or even for emergency evacuation). In this work is studied how BLE beacons radio signals can be used for indoor location scenarios, as well as their precision. The proposed study is performed inside the campus of Viseu Polytechnic Institute, using hundreds of students, each with his smart-phone, as proof of concept. Experimental results show that BLE allows having less than 1.5 meters error approximately 90% of the times. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Pedro Martins, Maryam Abbasi, Filipe Sa, Jose Celiclio, Francisco Morgado, Filipe Caldeira, Intelligent beacon location and fingerprinting, Procedia Computer Science, Volume 151, 2019, Pages 9-16, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2019.04.005. | pt_PT |
| dc.identifier.doi | 10.1016/j.procs.2019.04.005 | pt_PT |
| dc.identifier.issn | 1877-0509 | |
| dc.identifier.uri | http://hdl.handle.net/10400.19/5519 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Springer | pt_PT |
| dc.relation | BlueEyes | pt_PT |
| dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S1877050919304661 | pt_PT |
| dc.subject | Beacons | pt_PT |
| dc.subject | Wireless | pt_PT |
| dc.subject | GPS | pt_PT |
| dc.subject | Indoor location | pt_PT |
| dc.subject | Crowd learning | pt_PT |
| dc.subject | Bluetooth | pt_PT |
| dc.subject | BLE | pt_PT |
| dc.subject | WiFi | pt_PT |
| dc.subject | Fingerprinting | pt_PT |
| dc.title | Intelligent beacon location and fingerprinting | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Leuven - Belgium | pt_PT |
| oaire.citation.endPage | 16 | pt_PT |
| oaire.citation.startPage | 9 | pt_PT |
| oaire.citation.title | The 10th International Conference on Ambient Systems, Networks and Technologies (ANT 2019) | pt_PT |
| oaire.citation.volume | 151 | pt_PT |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |