SVM-Based Traffic Data Classification for Secured IoT-Based Road Signaling System

Thetrafficcontrollingsystemsatpresentaremicrocontroller-based,whichissemi-automaticinnature wheretimeistheonlyparameterthatisconsidered.WiththeintroductionofIoTintrafficsignaling systems,researchisbeingdoneconsideringdensityasaparameterforautomatingthetrafficsignaling systemandregulatetrafficdynamically.Securityisaconcernwhensensitivedataofgreatvolume isbeingtransmittedwirelessly.SecurityprotocolsthathavebeenimplementedforIoTnetworkscan protectthesystemagainstattacksandarepurelybasedonstandardcryptosystem.Theycannothandle heterogeneousdatatype.Topreventtheissuesonsecurityprotocols,theauthorshaveimplemented SVMmachinelearningalgorithmforanalyzingthetrafficdatapatternanddetectanomalies.The SVMimplementationhasbeendonefortheUKtrafficdatasetbetween2011-2016forthreecities. TheimplementationbeencarriedoutinRaspberryPi3processorfunctioningasanedgerouterand SVMmachinelearningalgorithmusingPythonScikitLibraries. KeywoRDS IoT, Pi3, SciKit, SVM

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