外文文獻翻譯-基于熱釋電紅外傳感器的智能家居室內(nèi)感應(yīng)定位系統(tǒng)

APyroelectricInfraredSensor-basedIndoorLocation-AwareSystemfortheSmartHomeSukLee,Member,IEEE,KyoungNamHa,KyungChangLee,Member,IEEEAbstract—Smarthomeisexpectedtooffervariousintelligentservicesbyrecognizingresidentsalongwiththeirlifestyleandfeelings.Oneofthekeyissuesforrealizingthesmarthomeishowtodetectthelocationsofresidents.Currently,theresearcheffortisfocusedontwoapproaches:terminal-basedandnon-terminal-basedmethods.Theterminal-basedmethodemploysatypeofdevicethatshouldbecarriedbytheresidentwhilethenon-terminal-basedmethodrequiresnosuchdevice.Thispaperpresentsanovelnon-terminal-basedapproachusinganarrayofpyroelectricinfraredsensors(PIRsensors)thatcandetectresidents.Thefeasibilityofthesystemisevaluatedexperimentallyonatestbed.IndexTerms—smarthome,location-basedservice,pyroelectricinfraredsensor(PIRsensor),location-recognitionalgorithm1.INTRODUCTIONThereisagrowinginterestinsmarthomeasawaytoofferaconvenient,comfortable,andsaferesidentialenvironment.Ingeneral,thesmarthomeaimstoofferappropriateintelligentservicestoactivelyassistintheresident’slifesuchashousework,amusement,rest,andsleep.Hence,inordertoenhancetheresident’sconvenienceandsafety,devicessuchashomeappliances,multimediaappliances,andinternetappliancesshouldbeconnectedviaahomenetworksystem,asshowninFig.1,andtheyshouldbecontrolledormonitoredremotelyusingatelevision(TV)orpersonaldigitalassistant(PDA).Fig.1.ArchitectureofthehomenetworksystemforsmarthomeEspecially,attentionhasbeenfocusedonlocation-basedservicesasawaytoofferhigh-qualityintelligentservices,whileconsideringhumanfactorssuchaspatternofliving,health,andfeelingsofaresident.Thatis,ifthesmarthomecanrecognizetheresident’spatternoflivingorhealth,thenhomeappliancesshouldbeabletoanticipatetheresident’sneedsandofferappropriateintelligentservicemoreactively.Forexample,inapassiveserviceenvironment,theresidentcontrolstheoperationoftheHVAC(heating,ventilating,andairconditioning)system,whilethesmarthomewouldcontrolthetemperatureandhumidityofaroomaccordingtotheresident’scondition.Variousindoorlocation-awaresystemshavebeendevelopedtorecognizetheresident’slocationinthesmarthomeorsmartoffice.Ingeneral,indoorlocation-awaresystemshavebeenclassifiedintothreetypesaccordingtothemeasurementtechnology:triangulation,sceneanalysis,andproximitymethods.Thetriangulationmethodusesmultipledistancesfrommultipleknownpoints.ExamplesincludeActiveBadges,ActiveBats,andEasyLiving,whichuseinfraredsensors,ultrasonicsensors,andvisionsensors,respectively.Thesceneanalysismethodexaminesaviewfromaparticularvantagepoint.RepresentativeexamplesofthesceneanalysismethodareMotionStar,whichusesaDCmagnetictracker,andRADAR,whichusesIEEE802.11wirelesslocalareanetwork(LAN).Finally,theproximitymethodmeasuresnearnesstoaknownsetofpoints.AnexampleoftheproximitymethodisSmartFloor,whichusespressuresensors.Alternatively,indoorlocation-awaresystemscanbeclassifiedaccordingtotheneedforaterminalthatshouldbecarriedbytheresident.Terminal-basedmethods,suchasActiveBats,donotrecognizetheresident’slocationdirectly,butperceivethelocationofadevicecarriedbytheresident,suchasaninfraredtransceiverorradiofrequencyidentification(RFID)tag.Therefore,itisimpossibletorecognizetheresident’slocationifheorsheisnotcarryingthedevice.Incontrast,non-terminalmethodssuchasEasyLivingandSmartFloorcanfindtheresident’slocationwithoutsuchdevices.However,EasyLivingcanberegardedtoinvadetheresident’sprivacywhiletheSmartFloorhasdifficultywithextendibilityandmaintenance.Thispaperpresentsanon-terminalbasedlocation-awaresystemthatusesanarrayofpyroelectricinfrared(PIR)sensors.ThePIRsensorsontheceilingdetectthepresenceofaresidentandarelaidoutsothatdetectionareasofadjacentsensorsoverlap.BycombiningtheoutputsofmultiplePIRsensors,thesystemisabletolocatearesidentwithareasonabledegreeofaccuracy.Thissystemhasinherentadvantageofnon-terminalbasedmethodswhileavoidingprivacyandextendibility,maintenanceissues.Inordertodemonstrateitsefficacy,anexperimentaltestbedhasbeenconstructed,andtheproposedsystemhasbeenevaluatedexperimentallyundervariousexperimentalconditions.Thispaperisorganizedintofoursections,includingthisintroduction.SectionIIpresentsthearchitectureofthePIRsensor-basedindoorlocation-awaresystem(PILAS),andthelocation-recognitionalgorithm.SectionIIIdescribesaresident-detectionmethodusingPIRsensors,andevaluatestheperformanceofthesystemundervariousconditionsusinganexperimentaltestbed.Finally,asummaryandtheconclusionsarepresentedinSectionIV.2.ARCHITECTUREOFTHEPIRSENSOR-BASEDINDOORLOCATION-AWARESYSTEM2.1FrameworkofthesmarthomeGiventheindoorenvironmentofthesmarthome,anindoorlocation-awaresystemmustsatisfythefollowingrequirements.First,thelocation-awaresystemshouldbeimplementedatarelativelylowcostbecausemanysensorshavetobeinstalledinroomsofdifferentsizestodetecttheresidentinthesmarthome.Second,sensorinstallationmustbeflexiblebecausetheshapeofeachroomisdifferentandthereareobstaclessuchashomeappliancesandfurniture,whichpreventthenormaloperationofsensors.Thethirdrequirementisthatthesensorsforthelocation-awaresystemhavetoberobusttonoise,andshouldnotbeaffectedbytheirsurroundings.ThisisbecausethesmarthomecanmakeuseofvariouswirelesscommunicationmethodssuchaswirelessLANorradio-frequency(RF)systems,whichproduceelectromagneticnoise,ortheremaybesignificantchangesinlightortemperaturethatcanaffectsensorperformance.Finally,itisdesirablethatthesystem’saccuracyisadjustableaccordingtoroomtypes.Amongmanysystemsthatsatisfytherequirement,thePIRsensor-basedsystemhasnotattractedmuchattentioneventhoughthesystemhasseveraladvantages.ThePIRsensors,whichhavebeenusedtoturnonalightwhenitdetectshumanmovement,arelessexpensivethanmanyothersensors.Inaddition,becausePIRsensorsdetecttheinfraredwavelengthemittedfromhumansbetween9.4~10.4μm,theyarereasonablyrobusttotheirsurroundings,intermsoftemperature,humidity,andelectromagneticnoise.Moreover,itispossibletocontrolthelocationaccuracyofthesystembyadjustingthesensingradiusofaPIRsensor,andPIRsensorsareeasilyinstalledontheceiling,wheretheyarenotaffectedbythestructureofaroomoranyobstacles.Figure2showstheframeworkforthePILASinasmarthomethatofferslocation-basedintelligentservicestoaresident.Withinthisframework,variousdevicesareconnectedviaahomenetworksystem,includingPIRsensors,roomterminals,asmarthomeserver,andhomeappliances.Here,eachroomisregardedasacell,andtheappropriatenumberofPIRsensorsisinstalledontheceilingofeachcelltoprovidesufficientlocationaccuracyforthelocation-basedservices.EachPIRsensorattemptstodetecttheresidentataconstantperiod,andtransmitsitssensinginformationtoaroomterminalviathehomenetworksystem.Fig.2.FrameworkofsmarthomeforthePILAS.Consequently,theroomterminalrecognizestheresident’slocationbyintegratingthesensorinformationreceivedfromallofthesensorsbelongingtoonecell,andtransmitstheresident’slocationtothesmarthomeserverthatcontrolsthehomeappliancestoofferlocation-basedintelligentservicestotheresident.Withinthisframework,thesmarthomeserverhasthefollowingfunctions.1)Thevirtualmapgeneratormakesavirtualmapofthesmarthome(generatingavirtualmap),andwritesthelocationinformationoftheresident,whichisreceivedfromaroomterminal,onthevirtualmap(writingtheresident’slocation).Then,itmakesamovingtrajectoryoftheresidentbyconnectingthesuccessivelocationsoftheresident(trackingtheresident’smovement).2)Thehomeappliancecontrollertransmitscontrolcommandstohomeappliancesviathehomenetworksystemtoprovideintelligentservicestotheresident.3)Themovingpatternpredictorsavesthecurrentmovementtrajectoryoftheresident,thecurrentactionofhomeappliances,andparametersreflectingthecurrenthomeenvironmentsuchasthetime,temperature,humidity,andillumination.Afterstoringsufficientinformation,itmaybepossibletoofferhuman-orientedintelligentservicesinwhichthehomeappliancesspontaneouslyprovideservicestosatisfyhumanneeds.Forexample,ifthesmarthomeserver“knows〞thattheresidentnormallywakesupat7:00A.M.andtakesashower,itmaybepossibletoturnonthelampsandsomemusic.Inaddition,thetemperatureoftheshowerwatercanbesetautomaticallyfortheresident.2.2Location-recognitionalgorithmInordertodeterminethelocationofaresidentwithinaroom,anarrayofPIRsensorsareusedasshowninFig.3.Inthefigure,thesensingareaofeachPIRsensorisshownasacircle,andthesensingareasoftwoormoresensorsoverlap.Consequently,whenaresidententersoneofthesensingareas,thesystemdecideswhetherhe/shebelongstoanysensingareabyintegratingthesensinginformationcollectedfromallofthePIRsensorsintheroom.Forexample,whenaresidententersthesensingareaB,sensorsaandboutput‘ON’signals,whilesensorcoutputs‘OFF’signal.Aftercollectingoutputs,thealgorithmcaninferthattheresidentbelongstothesensingareaB.Accordingtothenumberofsensorsandthearrangementofthesensorssignaling‘ON’,theresident’slocationisdeter-minedinthefollowingmanner.First,ifonlyonesensoroutputs‘ON’signal,theresidentisregardedtobeatthecenterofthesensingareaofthecorrespondingsensor.Iftheoutputsoftwoadjacentsensorsare‘ON’,theresident’slocationisassumedtobeatthepointmidwaybetweenthetwosensors.Finally,ifthreeormoresensorssignal‘ON’,theresidentislocatedatthecentroidofthecentersofthecorrespondingsensors.Forexample,itisassumedthattheresidentislocatedatpoint1inthefigurewhenonlysensorasignals‘ON’,whiletheresidentislocatedatpoint2whensensorsaandbbothoutput‘ON’signals.Thelocationaccuracyofthissystemcanbedefinedthemaximumdistancebetweentheestimatedpointsandtheresident.Forexample,whenaresidententerssensingareaA,theresidentisassumedtobeatpoint1.OntheassumptionthataresidentcanberepresentedbyapointandtheradiusofthesensingareaofaPIRsensoris1m,weknowthatthelocationaccuracyis1mbecausethemaximumerroroccurswhentheresidentisontheboundaryofsensingareaA.Alternatively,whentheresidentisinsensingareaB,theresidentisassumedtobeatpoint2,andthemaximumlocationerroroccurswhentheresidentisactuallyatpoint3.Inthiscase,theerroris3/2mwhichisthedistancebetweenpoints2and3.Therefore,thelocationaccuracyofthetotalsystemshowninFig.3canberegardedas1m,whichisthemaximumvalueofthelocationaccuracyofeacharea.SincethenumberofsensorsandthesizeoftheirsensingareasdeterminethelocationaccuracyofthePILAS,itisnecessarytoarrangethePIRsensorsproperlytoguaranteethespecifiedsystemaccuracy.Fig.3.Thelocation-recognitionalgorithmforPIRsensors.Inordertodeterminetheresident’slocationpreciselyandincreasetheaccuracyofthesystem,itisdesirabletohavemoresensingareaswithgivennumberofsensorsandtohavesensingareasofsimilarsize.Fig.4showssomeexamplesofsensorarrangementsandsensingareas.Fig.4(a)and4(b)showthearrangementswithninesensorsthatproduce40and21sensingareas,respectively.ThearrangementinFig.4(a)isbetterthanFig.4(b)intermsifthenumberofsensingareas.However,thearrangementinFig.4(a)hassomeareaswherearesidentcannotbedetectedandlowerlocationaccuracythanthatinFig.4(b).Fig.4(c)showsanarrangementwithtwelvesensorsthatfive28sensingareaswithoutanyblindspots.Fig.4.LocationaccuracyaccordingtothesensorarrangementofPIRsensors.(a)40sensingareas.(b)21sensingareas.(c)28sensingareaswithtwelvesensors.WhenPIRsensorsareinstalledaroundtheedgeofaroom,asshowninFig.4(c),itsometimesmaygiveawkwardresults.OneexampleisshowninFig.5.Fig.5(a)showsthepathofaresident.Ifwemarktheestimatedpointsbyusingthesensorlocationorthemidpointofadjacentsensors,itwillbeazigzaggingpatternsasshowninFig.5(b).Inordertoalleviatethis,wemayregardthesensorsontheedgestobelocatedalittleinwards,whichgivetheresultshowninFig.5(c).Fig.5.Theeffectofcompensatingforthecenterpointoftheoutersensors.(a)Resident’smovement.(b)Beforecompensatingfortheoutersensors.(c)Aftercompensatingfortheoutersensors.3.PERFORMANCEEVALUATIONOFTHEPILAS3.1Resident-detectionmethodusingPIRsensorsSincethePILASrecognizestheresident’slocationbycombiningoutputsfromallthesensorsbelongingtoonecell,determiningwhetherasinglesensoris‘ON’or‘OFF’directlyinfluenceslocationaccuracy.Ingeneral,becausethe‘ON/OFF’valuescanbedeterminedbycomparingapredefinedthresholdandthedigitizedsensoroutputacquiredbysamplingtheanalogsignalfromaPIRsensor,itisnecessarytochooseanappropriatesignallevelforthethreshold.Forexample,SmartFloor,whichisanothernon-terminalmethod,canrecognizearesident’slocationexactlybycomparingtheappropriatethresholdandasensorvalue,becauseapressuresensoroutputsaconstantvoltagebasedontheresident’sweightwhenheremainsataspecificpoint.However,becauseaPIRsensormeasuresthevariationintheinfraredsignalproducedbyamovinghumanbody,itsoutputisinanalogform,asshowninFig.6.Thatis,asthevariationintheinfraredradiationfromaresidentincreaseswhenaresidententersasensingarea,thePIRsensoroutputsanincreasingvoltage.Conversely,thevoltagedecreasesastheresidentleavethesensingarea.Iftheresidentdoesnotmovewithinthesensingarea,thevariationintheinfraredradiationdoesnotexistandthePIRsensoroutputszerovoltage.Therefore,itisverydifficulttodeter-minewhenaresidentisstayingresidentwithinaspecificsensingareausingonlythevoltageorcurrentthresholdofaPIRsensor.Fig.6.SignaloutputofPIRsensor.Inordertoguaranteethelocationaccuracyofthesystem,theresident-detectionmethodmustmeetseveralrequirements.First,ifnoresidentispresentwithinasensingarea,thePIRsensorshouldnotoutput‘ON’signal.Thatis,thePIRsensormustnotmalfunctionbyotherdisturbancessuchasamovingpet,temperaturechangeandsunlight.Second,itshouldbepossibletopreciselydeterminethepointintimewhenaresidententersandleavesasensingarea.Thatis,inspiteofvariationsinsensorcharacteristics,resident’sspeedandheight,itshouldbepossibletodeterminethetimepointexactly.Finally,becausetheoutputvoltageofaPIRsensordoesnotexceedthethresholdvoltagewhentheresidentdoesnotmovewithinasensingarea,itisnecessarytoknowifaresidentstayswithinthesensingarea.Inordertosatisfytheserequirements,thispaperintroducesthefollowingimplementationmethodfortheresidentdetectionmethodforPIRsensors.First,inordertoeliminatePIRsensormalfunctioningduetopetsortemperaturechanges,aFresnellens,whichallowshumaninfraredwaveformstopassthroughitwhilerejectingotherwaveforms,isinstalledinfrontofthePIRsensors.Second,whentheoutputofaPIRsensorexceedsthepositivethresholdvoltage,andthisstateismaintainedforseveralpredefinedsamplingintervals,thattheresidenthasenteredasensingarea.Here,thethresholdmustbesufficientforthemethodtodistinguishvariationintheresident’sinfraredfromanenvironmentalinfraredsignalcausedbypetsortemperaturechange.Moreover,whenthesensor’soutputfallsbelowanegativethresholdvoltageandthisstatusismaintainedforseveralsamplingintervals,itisassumedthattheresidenthasleftthesensingarea.Finally,whentheoutputvoltageremainsbetweenthetwothresholdvoltages,forexamplewhentheresidentisnotmovinginsidethesensingarea,theoutputofthecorrespondingPIRsensorischangedfrom‘ON’to‘OFF’.Atthistime,ifothersensorsinstallednearthissensordonotoutput‘ON’signal,themethodregardstheresidentasremainingwithinthecorrespondingsensingarea.3.2PerformanceevaluationusinganexperimentaltestbedInordertoverifythefeasibilityofthePILAS,anexperimentaltestbedwasimplemented.Sincetheintelligentlocation-basedserviceinthesmarthomedoesnotrequireveryhighlocationaccuracy,wedesignedthesystemtohavealocationaccuracyof0.5m.Figure7showstheexperimentaltestbedinaroommeasuring4×4×2.5m(width×length×height).Intheexperiment,twelvePIRsensorswerefixedontheceiling,usingthearrangementshowninFig.4(c).AnAtmelAT89C51CC001microcontroller[17]wasusedforsignalprocessingandjudging‘ON/OFF’,andaNipponCeramicRE431BPIRsensor[18]andNL-11Fresnellenswereused.Especially,ahornwasinstalledoneachPIRsensortolimitthesensingareatothecirclewith2mdiameter.Fig.8showstheexperimentalresultswiththehorn.Inthefigure,theRE431Bsensoroutputsthesignalshownin(a)whenaresidentpassesthroughthesensingcircle,whileitoutputstheirregularsignalshownin(b)whentheresidentmoveswithinthecircle.Finally,nosignalisdetectedwhentheresidentmovesoutsidethecircle,asshownin(c).Fromtheseexperimentalresults,weverifiedthatthePIRsensordetectsresidentswithinthesensingareaonly.Inaddition,inordertojudgewhetherthesignalis‘ON’or‘OFF’,itisnecessarytochooseathresholdfortheRE431Bsensorthatconsidersexternalenvironmentaldisturbance.Initially,severalexperimentswereperformedtodeterminethethresholdwithrespecttotheinternaltemperaturechangecausedbyaairconditionerorheaterandotherdisturbances,suchaswindorsunshine.Basedontheseexperimentalresults,whenthethresholdoftheRE431Bsensorwas±0.4V,externalenvironmentaltemperaturechangedidnotaffectitsperformanceatdetectingtheresident.Inaddition,weverifiedthatpetsdidnotaffectthesensingperformancewiththesamethreshold.Fig.7.ExperimentaltestbedforthePILAS.Fig.8.Ensuringtheexactsensingrangewithahorn.Next,inordertodeterminetheresident’slocationusingtheinformationreceivedfromPIRsensors,aPC-basedlocationrecognitionalgorithmwasimplemented,asshowninFig.9.Here,aPCcollectsdatafromthePIRsensorsevery10msecusinganNI6025Edataacquisition(DAQ)board[19].Inthefigure,thelineintheleftwindowwasdrawnusingamousetoshowthepathoftheresidentgraphically,whilethatinthewindowontherightistheestimatedmovementtrajectoryoftheresidentdrawnbyconnectingtheresident’slocationsacquiredusingtheDAQboard.Finally,inordertoverifytheefficacyofthesystem,threeexperimentswereperformedwithresidentsbetween160and180cmtall,movingatspeedsbetween1.5and2.5km/h.Figure9showsthetrajectoryofaresidentmovingalongaTshapedpath.Thetrajectorymadebyconnectingtheresi-dent’slocationsrecognizedbythePILAS,shownontheright,wassimilartothetargetpathshownontheleft.Weknowthatthemaximumlocationerrorisabout30cmwithoutcompensatingfortheoutersensors.Fig.10showsthetrajectorywhentheresidentfollowsanH-shapedpath.Inthisexperiment,thelocationaccuracywassimilartothatinFig.9.Weverifiedthatthesystemcouldlocatearesidentwithaccuracyof0.5m,evenifthreeormoresensorswereactivated.Figure11showsthetrajectoryofaresidentmovingalongasquarepath.Inthiscase,thelocationerroristhelargest,andthetrajectoryisnotastraightline.WenotethatseriouslocationerrorsoccurredateachpointmarkedbyAduetotheinaccuratejudgmentoftheoutersensors.Nevertheless,thelocationerrorisstillsmallerthan0.5mwhenmovinginthesquarepath.Here,thecompensationmethodforoutersensors,whichwasexplainedinFig.5,reducesthelocationerrorateachpointA.Whentheresidentmovesinastraightline,asshowninFig.12(a),thelocationerrorisrelativelylargewithoutusingthecompensationmethod,asshowninFig.12(b).However,afterapplyingthecompensationmethod,weverifiedthatthedetectionresultsfortheareasinthesmallcirclesareenhancedbyroughlyabout30%.4.SUMMARYANDCONCLUSIONSThispaperpresentsaPIRsensor-basedindoorlocationawaresystemthatestimatestheresident’slocationforlocation-basedintelligentservicesinthesmarthome.Thispaperintroducestheframeworkofsmarthomeforthelocation-awaresystem,andalocation-recognitionalgorithmthatintegratestheinformationcollectedfromPIRsensors.Inaddition,thispaperpresentsaresident-detectionmethod.Finally,anexperimentisimplementedtoevaluatetheefficacyofthePILAS.Basedonseveralexperimentsconductedundervariousconditions,weverifiedthatthePILAScanestimatesresident’slocationsufficientlywell.Moreover,becausethelocationaccuracyofthesystemislessthan0.5mwithoutanyterminalforlocationrecognition,thesystemcanbeverypractical.Furthermore,itshouldbepossibletoenhancethelocationaccuracyofthesystembyincreasingthenumberofsensingareas,byequalizingthesensingareasbasedonthesensorarrangement,orbycompensatingforthecentersofoutersensors.Sincethelocationaccuracyofthissystemdiffersaccordingtothesensorarrangement,itisnecessarytodeterminetheoptimalsensorarrangementthatoffersthegreatestlocationaccuracy.Inordertoenhancethelocationaccuracy,itisalsonecessarytoenhancethemethodofprocessingthePIRsensorsusingmoreadvancedtechniquessuchasprobabilistictheoriesandsoftcomputing.Finally,theproposedPILAsystemshouldbeextendedtodealwitharoomoccupiedbymorethanoneresidents.基于熱釋電紅外傳感器的智能家居室內(nèi)感應(yīng)定位系統(tǒng)SukLee，電機及電子學(xué)工程師聯(lián)合會會員KyoungNamHa,KyungChangLee,電機及電子學(xué)工程師聯(lián)合會會員摘要:智能家居，是一種可以通過識別具有不同生活習(xí)慣和感覺的住戶來提供各種不同的智能效勞。而實現(xiàn)這樣的功能其中最關(guān)鍵的問題之一就是如何確定住戶的位置。目前，研究工作只要集中于兩種方法：終端方式和非終端方式。終端方式需要一種住戶隨身攜帶的設(shè)備，而非終端方式那么不需要這樣的設(shè)備。本文提出一種使用可以探測到住戶的熱釋電紅外傳感器〔紅外傳感器〕的新的非終端方式。該系統(tǒng)的可行性已經(jīng)通過了測試平臺的實驗性評估。索引詞:智能家居，定位效勞，熱釋電紅外傳感器〔紅外傳感器〕，定位識別算法1.簡介現(xiàn)在由于人人都想有一個方便，舒適，平安的居住環(huán)境，因此大家對于智能家居表現(xiàn)的越來越感興趣。一般來說，智能家居旨在提供適宜的智能效勞來積極促進住戶更好的生活，比方家務(wù)勞動，娛樂，休息和睡眠。因此，為了提高住戶的便捷和平安，像家用電器，多媒體設(shè)備和互聯(lián)網(wǎng)設(shè)備應(yīng)通過家庭網(wǎng)絡(luò)系統(tǒng)連接在一起，如圖1所示。并且它們應(yīng)通過電視或個人數(shù)字助理〔PDA〕來控制或遠程監(jiān)控。圖1智能家居的家庭網(wǎng)絡(luò)體系結(jié)構(gòu)尤其要注意的是，作為一種提供高質(zhì)量的智能效勞，目標應(yīng)集中于定位效勞，同時考慮人為因素，比方住戶的生活方式，健康狀況和居住感受。也就是說，如果智能家居能識別住戶的生活方式或健康狀況，那么家用電器應(yīng)該能預(yù)見住戶的需要，并能更主動的提供適合的智能效勞。例如，在一個被動的效勞環(huán)境下，需要住戶控制供熱通風(fēng)與空氣調(diào)節(jié)系統(tǒng)〔供暖，通風(fēng)和空調(diào)〕，而智能家居將根據(jù)住戶情況自動調(diào)節(jié)房間的溫濕度。智能家居或智能辦公室的各種室內(nèi)感應(yīng)定位系統(tǒng)的已經(jīng)研發(fā)到能夠識別住戶的位置。一般來說，室內(nèi)定位感應(yīng)系統(tǒng)根據(jù)測量技術(shù)分為三種類型：三角測量，場景分析和接近方法。三角測量法是通過多個點來計算位置距離。運用三角測量法的例子包括ActiveBadges，ActiveBats和EasyLiving，它們分別運用了紅外傳感器，超聲波傳感器和視覺傳感器來實現(xiàn)的。場景解析法是檢測一個場景內(nèi)的特定著眼點。場景解析法的典型例子是使用直流磁力跟蹤器的MotiveStar，和使用無線局域網(wǎng)絡(luò)[LAN]標準IEEE802,11的RADAR。接近法那么是以一組點中最接近的點近似作為定位點。接近法的例子有使用壓力傳感器的SmartFloor[。另外，室內(nèi)感應(yīng)定位系統(tǒng)可以根據(jù)是否需要住戶隨身攜帶一種設(shè)備來分類。終端方式，例如ActiveBats，不需要直接找到住戶位置，但是可以感應(yīng)到住戶隨身攜帶的設(shè)備位置，例如紅外收發(fā)器或者射頻識別技術(shù)〔RFID〕標簽。因此，如果住戶沒有隨聲攜帶終端設(shè)備，那就不可能找到他。相反的，非終端方式如EasyLiving和SmartFloor那么不需要這種設(shè)備就能找到住戶位置。然而，人們認為EasyLiving侵犯了住戶隱私，SmartFloor那么是擴展和維護都比擬困難。本文提出一種使用陣列熱釋電紅外〔PIR〕傳感器實現(xiàn)的基于非終端方式的室內(nèi)感應(yīng)定位系統(tǒng)。紅外傳感器固定在天花板上，并使相鄰的傳感器的感應(yīng)范圍有重疊。當它感應(yīng)到一名住戶時，通過多個紅外傳感器的綜合，能夠比擬準確確實定住戶的位置。該系統(tǒng)不僅具有非終端方式的特有優(yōu)點，還防止了侵犯隱私，擴展性不佳和維護困難的問題。為了證明其有效性，已經(jīng)在實驗平臺上通過了各種不同測試環(huán)境下的實驗性評估。包括此簡介，本文共分為四個局部，第二局部介紹基于紅外傳感器的室內(nèi)定位感應(yīng)系統(tǒng)架構(gòu)〔PILAS〕以及定位識別算法。第三局部介紹了基于紅外傳感器的住戶檢測法和在實驗測試平臺上的不同環(huán)境下評估系統(tǒng)的表現(xiàn)。最后一局部為總結(jié)和結(jié)論。2.基于熱釋電紅外傳感器的室內(nèi)感應(yīng)定位系統(tǒng)架構(gòu)2.1智能家居的結(jié)構(gòu)鑒于智能家居的室內(nèi)環(huán)境，室內(nèi)感應(yīng)定位系統(tǒng)必須滿足一下條件。第一，由于需要在各種大小不同的房間里安裝大量傳感器來感知智能家居中的住戶，因此定位感應(yīng)系統(tǒng)需保持較低的本錢。第二，傳感器的安裝必須是靈活可變的，因為各個房間的形狀結(jié)構(gòu)不同，并且還有各樣阻礙傳感器正常工作的家電和家具。第三，要求定位感應(yīng)系統(tǒng)使用的傳感器能夠抵御很強的噪聲，這是因為智能家居能利用各種無線傳輸技術(shù)，比方無線局域網(wǎng)，射頻系統(tǒng)，它們都會產(chǎn)生電磁噪聲，并且光或溫度的巨大變化也會影響傳感器的正常工作。最后該系統(tǒng)的精度可以，根據(jù)房間類型作出最適宜的調(diào)節(jié)。盡管基于熱釋電紅外傳感器的這個系統(tǒng)有諸多的優(yōu)點，但在眾多滿足要求的產(chǎn)品中并不能吸引人們更多的關(guān)注。它已應(yīng)用于感應(yīng)燈〔當它感應(yīng)到人體移動時使燈自動翻開〕，并且本錢低于許多其他種類的感應(yīng)器。另外，由于熱釋電紅外傳感器感應(yīng)的是人體發(fā)出的9.4～10.4微米波長的紅外線，從溫度、濕度和電磁噪聲來說，這種波長相對周圍環(huán)境較為明顯。而且，它可以通過調(diào)整感應(yīng)半徑來控制定位精度，并容易安裝在天花板上，這樣就不會受到房間結(jié)構(gòu)和障礙物的影響。圖2顯示的是為住戶提供基于位置的智能效勞的PILAS智能家居框架。在這個框架下，包括熱釋電紅外傳感器、房屋終端、智能家居效勞器和家用電器在內(nèi)的各種設(shè)備通過家庭網(wǎng)絡(luò)系統(tǒng)連接在一起。每個房間被視為一個單元，并在每個單元的天花板上安裝適當數(shù)量的傳感器，為定位效勞提供足夠的定位精度。每個紅外傳感器周期性的感應(yīng)住戶位置，然后將感應(yīng)信息通過家庭網(wǎng)絡(luò)系統(tǒng)傳輸?shù)椒课萁K端。因此，房屋終端通過集合來自同一個單元的傳感器信息來確定住戶的位置，再將住戶位置傳輸?shù)街悄芗揖有谄?，效勞器就會控制家用電器為住戶提供基于位置的定位效勞。圖2PILAS智能家居框架在這個框架內(nèi)，智能家居效勞器具有以下功能：〔1〕虛擬地圖發(fā)生器為智能家居提供虛擬地圖〔生成虛擬地圖〕，并在虛擬地圖中標出由房屋終端提供的住戶位置信息〔標注住戶位置〕。然后，它通過連接住戶的連續(xù)定位點來繪制住戶的運動軌跡〔追蹤住戶運動〕?！?〕家電控制器通過家庭網(wǎng)絡(luò)系統(tǒng)發(fā)送控制命令給家用電器為住戶提供智能效勞。〔3〕運動模式預(yù)測器保存當前的住戶運動軌跡、家電的動作和反映居家環(huán)境的參數(shù)，比方時間、溫度、濕度、光照度。儲存足夠的信息后，它可能會使家電主動提供滿足人們需要的人性化的智能效勞。例如，如果智能家居效勞器“知道〞住戶通常在早上7點醒來，之后要淋浴，它也許就會在那一時間翻開燈并播放音樂。另外，住戶的淋浴水溫也會被自動記錄。2.2定位識別算法為了確定住戶在房間里的位置，要使用一組熱釋電紅外傳感器，如圖3所示。在此圖中，每個傳感器的感應(yīng)面呈圓形并且相鄰的幾個傳感器有重疊的感應(yīng)范圍。因此，當住戶進入某一感應(yīng)區(qū)域后，系統(tǒng)根據(jù)從房間內(nèi)的所有傳感器收集到的感應(yīng)信息判斷他/她是否屬于這一感應(yīng)區(qū)。例如，當一位住戶進入B感應(yīng)區(qū)，a，b傳感器輸出“ON〞信號，而c傳感器輸出“OFF〞信號。收集輸出信號后，該算法可以推斷出住戶屬于B感應(yīng)區(qū)。根據(jù)傳感器的數(shù)量和傳感信號“ON〞的排列，住戶的位置通常有以下幾種情況。首先，如果只有一個傳感器輸出“ON〞信號，那么認為住戶處于該傳感器感應(yīng)區(qū)域的中心位置。其次，如果有兩個相鄰的傳感器輸出“ON〞信號，那么認為住戶位于兩傳感器的連線中心點處。最后，如果有