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1、The28thInternationalConferenceonDistributedComputingSystemsDataEstimationinSensorNetworksUsingPhysicalandStatisticalMethodologiesYingshuLiChunyuAiWiwekP.DeshmukhYiweiWuDepartmentofComputerScienceGeorgiaStateUniversity,Atlanta,GA30303{yli,chunyuai,wdeshmukh,wy

2、w}@cs.gsu.eduAbstractinthevisibleandNIRrangeinsidegreenhouses.Thelightintensitycanbemeasuredbythesesensors,anddataestima-WirelessSensorNetworks(WSNs)areemployedinmanytiontechniquesemployedinsuchenvironmentswouldhelpapplicationsinordertocollectdata.Onekeychall

3、engeisconserveenergyandprolongnetworklifetime.Commercialtominimizeenergyconsumptiontoprolongnetworklife-lightsensorswhichusephotodiodesthatproduceavoltagetime.Aschemeofmakingsomenodesasleepandesti-proportionaltothelightintensityarenowavailable.Sim-matingtheir

4、valuesaccordingtotheotheractivenodesilarly,lightintensitysensorsarerequiredtomonitormain-readingshasbeenprovedenergy-ef?cient.Forthepur-tenanceofoptimumlightinginanimalhusbandryrelatedposeofimprovingtheprecisionofestimation,wepro-business[1],andalsoincell-cul

5、tureexperiments[10]underposetwopowerfulestimationmodels,DataEstimationus-arti?ciallight,wherealsodataestimationtechniqueswouldingPhysicalModel(DEPM)andDataEstimationusinghelpenhancethelongevityofWSNs.StatisticalModel(DESM).DEPMestimatesthevaluesofsleepingnode

6、sbythephysicalcharacteristicsofsensedat-Usually,userscanacceptapproximatedata.Asaresult,tributes,whileDESMestimatesthevaluesthroughthespa-amethodofdataestimationisaperfectoptionforconserv-tialandtemporalcorrelationsofthenodes.Experimentalingenergy.Infact,thek

7、eychallengeishowtoprovideesti-resultsonrealsensornetworksshowthattheproposedtech-mateddatawithhighprecisionwhileconsumingaslittleen-niquesprovideaccurateestimationsandconserveenergyergyaspossible.Toaddressthisproblem,twonoveldataes-ef?ciently.timationmethodsa

8、reproposedinthispaper.Inourscheme,aminimalnumberofnodesaresettobeactiveandtheothernodesaresettosleep.Allnodesserveasactivework-ingnodesbyturns.Thebasestationestimatesvaluesof1Introduction