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The Global Market forIntelligent Video Analytics2018 to 2023
Published: Q3 2018
GlobalMarketforIntellVideoAnalytics2018to2023
Synopsis
Thisreportaimstoassistallstakeholdersandinvestorsinthevideosurveillanceindustryinunderstandingthepotentialimpactofartificialintelligenceonthemarket.
©MeemooriResearchAB
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Introduction
ThisReportisOur1stDetailedAssessmentofthePotentialImpactArtificialIntelligencewillhaveonVideoSurveillance&Analytics.
Videoanalyticshaseatenafewfreelunchesoverthelast15years.Whilstithascertainlyaddedsomevaluetovideoinstallations,therehasbeenmuchdebateaboutexactly‘howintelligent’thetechnologyreallyisandwhetheritprovidessatisfactoryROI.Butin2018,thereisnowagrowingbeliefthatvideoanalyticscouldfinallymovebeyondwhathasbeenachievedthroughconventionalrulebasedsystems.
Thisisdueinlargeparttomajoradvancesinsemiconductorarchitecture,whichisenablingmuchfasterprocessing;Empoweringdeeplearningandmachinelearningalgorithmstoanalyzedatamanytimesfasterthanwaspreviouslypossible.VenturecapitalistsarenowpouringbillionsofdollarsintofinancingArtificialIntelligence(AI)chipandanalyticsoftwarecompanies.Indeedwhileresearchingthisreport,weidentified128companiesacrosstheworldthatarenowinsomewayhelping(hardware&software)todeliverAIvideoanalyticsolutions.
Thereisstillmuchtobedoneinperfectingthetechnologyandgettingittomarket,butthese‘newtools’haveopeneduptheopportunitytobringAIproductstothevideoanalyticsmarketpotentiallyrevolutionizingitsperformanceandcapability.Andifitcandeliver,itwillfurtherdrivedemandforintelligentvideosurveillance,notjustfornewprojectsbutopenupavastlatentpotentialforretrofittingmillionsofexistingcamerainstallations.
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Why Do You Need This Report?
Whatisthemarketworthnow?WehavedefinedAIVideoAnalyticsasasolutionthatisrunningdeeplearningalgorithmsonaplatformthatismostlikelytobebuiltonaGPUchiparchitecture.ThesesolutionsareverymuchintheirembryonicstageandourbestestimateisthatglobalsalesofAIVideoAnalyticsolutionsin2017wasonlyaround$115million,muchofthisbeinginstalledinChinaonSafeCityprojects.
VideoSurveillancesystemsgeneratevastamountsofdatathatissadlynotbeingutilizedproperly.Thereishugepotentialtomaximizethevalueofthisdatabyconvertingitfrom“dumbtoactionable”.Thematerialisalreadyouttherejustwaitingtobemined.NewchiparchitecturescombinedwithAIvideoanalyticssoftwarewhenputtoworkonthesegargantuanvolumesofdatashouldimprovethesecurity,safetyandperformanceofpeople,buildingsandthebusinessenterpriseandatthesametimeprovideamajorboosttotheVideoSurveillanceEcosystem.
Currentlawenforcementsystemsareincreasinglyunabletocopewiththesheervolumeofsurveillancematerialcapturedandstoredeveryday.Thisisonlysettorise,withthepopulationofvideocamerasincreasingbyatleast12%peryear.Thesevideostreamswillonlyeverbeusefulifprocessesto
searchandanalyzethemountainofdatakeeppace.Asitstandstodayvitalinformationismissedbecausethevastmajorityofvideoissimplynever
viewed.
Inordertobothsizethepotentialmarketandfutureforintelligentvideoanalyticssoftware,inthisreportwealsoestablishthesizeoftheVideoSurveillanceequipmentbusiness,howitisorganizedandthenfocusdeeperintotheVideoManagementSolutions(VMS)businessasthisiswherecurrentanalyticsoftwareforthevideosurveillancebusinessismostoftenapplied.Todaymostofthesoftwareusedfallsoutsideourdefinitionofbeing“AIVideoAnalytics”butinthefutureitwillbeaninextricablepartofit.WethereforereviewthevideosurveillanceandtheVMSbusinessinordertomakeaseriousattempttoforecastthedemandfortheAIVideoAnalyticsmarket.
Wehaveidentifiedsome128companiesthatarecurrentlyactiveinsupplychainforAIVideoAnalytics.Newcompaniesarebeingaddedtothislistalmostdailyandwecannotclaimthatourlistisfullycomprehensive.NvidiahasemergedastheearlyleaderinAIchipsandisparticularlystronginvideoanalytics.Nvidia’sedgeisthatitsPCgamingprocessors(GPUs)canbescaleduptohandleAIsoftware,thankstotheir“parallelprocessing”circuitrywhichcanhandlecomplexmultipletasks.
ChinahaspublicallyannounceditsgovernmentstrategytodominateAItechnology.ItsInternetgiantslikeBaidu,AlibabaGroupHoldingsandTencentHoldingsarepouringmoney
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intoAIresearch.Chinaproducesaround40%oftheworld’svideocamerasandconsequentlywillgeneratemassiveamountsofrawdatatotrainAIsystemsinhowtomakepredictions.ThereisgoodreasontothinkChinawillmakebreakthroughsindevelopingcomputeralgorithmsforvideoapplications.
Withinits144Pagesand8ChartsandTables,Thereportpresentsallthekeyfactsanddrawsconclusions,soyoucanunderstandtheimpactthatartificialintelligenceishavingonvideosurveillanceandanalytics;
Thereare2elementstotheimplementationofvideoanalytics.Thefirstisthetaskofaddingtheanalyticsenginestothevariousvideostreamsandenablingthem.Thisisrelativelysimpletoachieve.Thesecondpartoftheimplementation,andthepartoftheprocessthatcanbefarmoretime-consuming,isconfiguringthemforaccurateperformance.Everysiteisbespoke,andevenverysimilarsitesusingthesameanalyticrulesmayneedtodeliververydifferentresults,baseduponthespecificoperationalrequirements.Evenwithaself-learningsystem,theremaybeaneedtoadjustdetectionzonesandmasks,cameraangles,perspectivesettings
Webelievethereare2mainfactorsthatwilldeterminethefuturerolethatthesuppliersofthevideosurveillancemarketwillplay.ThefirstisthebroadsplitbetweentheEnterprisemarketandtheSMBmarketandthe2methodsofapplyingAIthrougheithertheedgeorthecloud.
Inthisreport,wehavedetailedsome6methodsofapplyingAIanddeeplearning.Theyallhavebenefitsinparticularapplicationsbutalltoofteninthepasttherehasbeenafailuretotakeintoaccounttheneedtosimplifytheinstallationandconfigurationandmoreimportantlysatisfythebuyerthatthesystemisreliableandrobust.
StartingatonlyUSD$1,750foraSingleUserLicense,thisreportprovidesvaluableinformationintohowVideoSurveillanceandITcompaniesaredevelopingtheirbusinessesthroughInvestment,M&AandStrategicAlliance.
Table of Contents Preface
ExecutiveSummary
1.Introduction
2.AITechnologyanditsimpactonIntelligentVideoAnalyticsSolutions
2.1ThePanoramaofAI–IoT,BigData&Blockchain
2.2AIChipTechnologiesDiversify&OpenupNewApplications
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2.3TheDevelopmentofAIChipTechnology–MachineLearning&DeepLearning
2.3.1TheDevelopmentofAIChipTechnology
2.3.2MachineLearning&DeepLearning
2.4TheAdvantagesofDeepLearninganditsAlgorithms
2.4.1DeepLearning
2.4.2Start“Shallow”go“Deep”
2.4.3“ArtificialAspects”to“AspectLearning”
2.4.4KeyFactorsofDeepLearning
2.4.5ApplicationofDeepLearningProducts
2.4.6TheCostofDeepLearning
2.4.7SpikingNeuralNetworks
2.5ThereisaGrowingNecessityforAIVideoAnalytics
3.MarketSizeofVideoSurveillanceSystems&VMSSoftware
3.1MarketSizeofVideoSurveillanceEquipment2017&Forecastto2022
3.1.1ImplicationsofUsing2DCamerasforAIAnalytics
3.1.2ImplicationsofUsing3DCameras
3.1.3ImplicationsofUsingThermalCameras
3.2MarketSizeofVideoManagementSoftwareSystems2017&Forecast2022
4.MarketSizeofVideoAnalyticSoftware&TransitiontoAIVideoAnalyticsSoftware
4.1MarketSizeofVideoAnalyticSoftware2017
4.1.1VideoAnalyticSoftwareabouttoreachtheInflectionPoint
4.1.2WhyVideoAnalyticSoftwarehasanimmenseGrowthPotential
4.1.3TraditionalVideoAnalyticAlgorithmsLackSophistication
4.2HowWillAIVideoAnalyticsbeApplied
4.2.1AddonCameraAnalytics
4.2.2AnalyticsAppliance/Encoder
4.2.3CloudAnalytics
4.2.4EmbeddedCameraAnalytics
4.2.5EmbeddedDVR/VMSAnalytics
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4.2.6ServerBasedAnalytics
4.3TheWorldMarketforAIVideoAnalytics
5.AssessingtheSupplySide&CompetitiveLandscape
5.1TheWorlds’LeadingCameraSuppliers
5.2TheWorlds’LeadingVMSSuppliers
5.3TheWorlds’LeadingVideoAnalyticSuppliers
5.4TheWorlds’LeadingAIChipManufacturers
5.4.1AISemiconductorChips
5.4.2WhereareweatTodayinApplyingAITechnology
5.4.3ChallengesinApplyingAITechnology
5.4.4ChallengesRunningAIatthe‘Edge’ofNetworks
6.EvaluatingtheDemand&SupplySideChallenges
6.1DemandforVideoAnalytics
6.2OvercomingtheSupplySideChallengers
6.3LeadingVerticalsforAIVideoAnalytics
6.3.1HowIntelligentVideoCanMakeSmartCitiesSee
6.3.2TransportgoesforAIVideoAnalyticSolutions
6.3.3RetailBuildingsgoforAIVideoAnalyticSolutions
6.3.4FacialRecognitionAnalyticsMovestotheEdge
6.4ConnectingAI–IoT–BlockChain
6.5CanAIVideoAnalyticsSoftwareDeliver?
7.ChannelsofDistributionforAIVideoAnalyticSolutions
7.1ThroughtheVideoSurveillanceNetwork
7.2IntheCloud
8.Funding–Investment&IntellectualPropertyintheRaceforAITechnology
8.1Funding&InvestmentinAIChips&Software
8.2AIPatents3rdFastestGrowingCategory2013to2017
9.VentureCapitalisInvestingEnormousFundsinAI
9.1InvestmentinAI&MachineLearningCompanies
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9.2ChineseInvestorsPourBillionsintoAISolutions
10.Mergers&Acquisitions–StrategicAlliances
10.1StrategicAlliances
10.1.1IBM–CenterforOpenSourceDataandAITechnologiesinSanFrancisco
10.1.2NvidiaandARMPartnerforChipmakerstoEmbedDeepLearning
10.1.3AmazonDeepLearningPartnershipWithAgentVi
10.1.4Google&BaiduSpearheadMLPerf
10.2Mergers&Acquisitions
10.2.1GoogleandApple’sGlobalAcquisitions
10.2.2Facebook’sComputerVisionCollection
10.2.3Qualcomm
10.2.4Intel
10.2.5CanonAcquiresBriefcam
10.2.6MotorolaAcquiresAvigilon
10.2.7NortekSecurity&ControlAcquiresIntelliVisionTechnologiesCorp
List of Figures
Fig2.1MachineLearning&DeepLearningCapability
Fig3.1WorldSalesofVideoSurveillanceProducts2017–2022($b)
Fig3.2WorldVMSMarketforVideoSurveillance2013–2022($m)
Fig4.1TheWorldMarketforAIVideoAnalyticsMarket2017–2022($m)
Fig5.1PerformanceofEstablishedPlayers/NewVentures/Challengers/LeadersintheVideoSurveillanceCameraMarket2017
Fig5.2PerformanceofEstablishedPlayers/NewVentures/Challengers/LeadersintheVMSMarket2017
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List of Tables
Table5.1DirectoryofAISemiconductorSpecialist&VideoAnalyticSuppliers2018
Table8.1USMachineLearningPatentApplicationsin2017byCompany
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