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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