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3. Algorithmsusedfor indoor location
Different techniques have been used based onWi-Fi signals for indoor location [5,6]:
a) Wi-Fi signal propagation model use sampled intensity of the WAPs around and a
signal path-loss models to estimate the distance of the user to different WAPs; once
these distances are estimated, trilateration is used to provide an estimated location of
the user; b) TimeofArrival (ToA) is based on the time used by theWi-Fi signalwhen
traveling between the emitter and the receiver to estimate the distance between them,
then trilateration isused toprovideanestimated locationof theuser; c)AngleofArrival
(AoA)usethetimeatwhichWi-Fisignalarrives toasetofantennasseparatedbyaknow
distance to estimate the angle of arrival, and then triangulation can be used to estimate
user’s location; d)Wi-fi fingerprinting is based onmeasuring theWi-Fi intensity of a
signalatdifferentpoints,creatingasocalledradiomap; thenthe informationin theradio
map isused toestimateuser’s locationbasedon theWi-Fi samplesprovidedby theuser.
4. Examplesandcase studies
Inparticular, remotehealthcareandolderadultswellbeingrealmshavepaid lotofatten-
tion to indoor locationmethodsasenabling technologies [7,8].
5. Future linesofresearchfor indoor location
The use of newWi-Fi standards, data fusion using data coming from various sensors
(Wi-Fi,magnetic, inertial),ubiquitouslocationindoorsandoutdoorsaresomeofthemos
promisingand interesting linesof future researchwithin the IndoorLocation realm.
References
[1] Li,RuijiaoandLu,BowenandMcDonald-Maier,KlausD.Cognitiveassisted livingambient system:a
survey.DigitalCommunicationsandNetworks.1 (2015), 229–252.
[2] Queiro´s,AlexandraandSilva,AnabelaandAlvarelha˜o, JoaquimandRocha,NelsonPachecoandTeix-
eira, Anto´nio. Usability, accessibility and ambient-assisted living: a systematic literature review.Uni-
versalAccess in the InformationSociety1, 14 (2015), 57–66.
[3] VanHaute, TomandDePoorter, Eli andCrombez, Pieter andLemic, Filip andHandziski,Vlado and
Wirstro¨m,Niklas andWolisz,AdamandVoigt,ThiemoandMoerman, Ingrid.Performanceanalysis of
multiple IndoorPositioningSystems inahealthcareenvironment Int JHealthGeogr15 (2016).
[4] Hussien, HabibMohammed and Shiferaw, YalemzewedNegash and Teshale, Negassa Basha. Survey
on indoor positioning techniques and systems. Lecture Notes of the Institute for Computer Sciences,
Social-InformaticsandTelecommunicationsEngineering,LNICST 2446 (2018), 46–55.
[5] GkhanKul andTansel zyer andBlentTavli. IEEE802.11WLANbasedRealTime IndoorPositioning:
LiteratureSurveyandExperimental Investigations.ProcediaComputerScience34 (2014), 157–64.
[6] AhmedMakkiandAbubakrSiddigandMohamedSaadandChrisBleakley.SurveyofWiFipositioning
using time-based techniques.ComputerNetworks88 (2015), 218–233.
[7] Santoso, Fendy andRedmond, Stephen J. Indoor location-awaremedical systems for smart homecare
and telehealthmonitoring:State-of-the-art.PhysiologicalMeasurement3610 (2015), 53–87.
[8] Blackman, Stephanie andMatlo,Claudine andBobrovitskiy,Charisse andWaldoch,Ashley andFang,
MeiLanand Jackson,Piper andMihailidis,AlexandNyga˚rd,Louise andAstell,ArleneandSixsmith,
Andrew.AmbientAssistedLivingTechnologies forAgingWell:AScopingReview. Journal of Intelli-
gentSystems251 (2016), 55–69.
Ó.Belmonte-Fernández /Fundamentalsof IndoorLocation
forSmartEnvironmentsApplications4
Intelligent Environments 2019
Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Titel
- Intelligent Environments 2019
- Untertitel
- Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Autoren
- Andrés Muñoz
- Sofia Ouhbi
- Wolfgang Minker
- Loubna Echabbi
- Miguel Navarro-Cía
- Verlag
- IOS Press BV
- Datum
- 2019
- Sprache
- deutsch
- Lizenz
- CC BY-NC 4.0
- ISBN
- 978-1-61499-983-6
- Abmessungen
- 16.0 x 24.0 cm
- Seiten
- 416
- Kategorie
- Tagungsbände