DC pole | Wartość | Język |
dc.contributor.author | Lewandowski, Marcin | - |
dc.contributor.author | Orczyk, Tomasz | - |
dc.contributor.author | Płaczek, Bartłomiej | - |
dc.date.accessioned | 2018-09-17T08:04:28Z | - |
dc.date.available | 2018-09-17T08:04:28Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Journal of Medical Informatics & Technologies, Vol. 25 (2016), s. 38-45 | pl_PL |
dc.identifier.issn | 1642-6037 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12128/6217 | - |
dc.description.abstract | Paper presents a new method of patient activity monitoring, by using modern ADL (Activities of
Daily Living) techniques. Proposed method utilizes energy efficient Bluetooth iBeacon BLE (Bluetooth
Low Energy) modules, developed by Apple. Main advantage of this technology is the ability to
detect neighboring devices, which belong to the same device family. Proposed method is based on
observing changes of received signal strength indicator (RSSI) in the time domain. The RSSI analysis
is performed in order to asses a human activity. Such observation may be particularly useful for
monitoring consciousness of elder people, where reaction time of emergency rescuers and appropriate
rescue operations may save the human lives. | pl_PL |
dc.language.iso | en | pl_PL |
dc.rights | Uznanie autorstwa-Użycie niekomercyjne-Bez utworów zależnych 3.0 Polska | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/pl/ | * |
dc.subject | język Fuzzy SQL | pl_PL |
dc.subject | iBeacon | pl_PL |
dc.title | Human Activity Detection Based on the iBeacon Technology | pl_PL |
dc.type | info:eu-repo/semantics/article | pl_PL |
Pojawia się w kolekcji: | Artykuły (WNŚiT)
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