Handbook of Ambient Intelligence and Smart Environments

1292 Pages·2010·57.57 MB·English

by  Juan Carlos Augusto

Handbook of Ambient Intelligence and Smart
Environments
· ·
Hideyuki Nakashima Hamid Aghajan
Juan Carlos Augusto
Editors
Handbook of Ambient
Intelligence and Smart
Environments
123
Editors
HideyukiNakashima HamidAghajan
FutureUniversityHakodate DepartmentofElectricalEngineering
Kameda-Nakano116-2 StanfordUniversity
Hakodate,Hokkaido 350SerraMall
041-8655Japan Stanford,CA94305-9515
[email protected] USA
[email protected]
JuanCarlosAugusto
SchoolofComputing&Mathematics
UniversityofUlsteratJordanstown
ShoreRoad,Newtownabbey,Co.Antrim
UKBT370QB
[email protected]
ISBN978-0-387-93807-3 e-ISBN978-0-387-93808-0
DOI10.1007/978-0-387-93808-0
SpringerNewYorkDordrechtHeidelbergLondon
LibraryofCongressControlNumber:2009935679
(cid:2)c SpringerScience+BusinessMedia,LLC2010
Chapter11(cid:2)c2009FrankStajano.Usedwithpermission
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SpringerispartofSpringerScience+BusinessMedia(www.springer.com)
Contents
PartI Introduction
AmbientIntelligenceandSmartEnvironments:AStateoftheArt ..... 3
JuanCarlosAugusto,HideyukiNakashima,HamidAghajan
1 Introduction............................................. 3
2 Sensors,Vision,andNetworks ............................. 7
3 MobileandPervasiveComputing........................... 10
4 Human-centeredInterfaces ................................ 14
5 ArtificialIntelligenceandRobotics ......................... 17
6 Multi-Agents............................................ 20
7 Applications ............................................ 22
8 SocietalImplicationsandImpact ........................... 24
9 SelectedResearchProjects ................................ 26
10 PerspectivesoftheArea................................... 29
11 Conclusions............................................. 30
References.................................................... 31
PartII Sensor,VisionandNetworks
ASurveyofDistributedComputerVisionAlgorithms................ 35
RichardJ.Radke
1 Introduction............................................. 35
2 DistributedAlgorithms.................................... 37
3 TopologyEstimation ..................................... 38
3.1 Non-overlappingTopologyEstimation............... 40
3.2 OverlappingTopologyEstimation................... 41
4 CameraNetworkCalibration............................... 42
4.1 Non-overlappingCameraCalibration................ 43
v
vi Contents
4.2 OverlappingCameraCalibration.................... 44
4.3 ImprovingCalibrationConsistency.................. 45
5 TrackingandClassification ................................ 47
6 Conclusions............................................. 49
References.................................................... 50
Video-BasedPeopleTracking .................................... 57
MarcusA.Brubaker,LeonidSigalandDavidJ.Fleet
1 Introduction............................................. 57
1.1 TrackingasInference ............................. 58
2 GenerativeModelforHumanPose.......................... 60
2.1 KinematicParameterization........................ 60
2.2 BodyGeometry.................................. 61
2.3 ImageFormation................................. 62
3 ImageMeasurements ..................................... 62
3.1 2DPoints ....................................... 63
3.2 BackgroundSubtraction........................... 64
3.3 AppearanceModels............................... 65
3.4 EdgesandGradientBasedFeatures ................. 66
3.5 Discussion ...................................... 68
4 MotionModels .......................................... 68
4.1 JointLimits ..................................... 69
4.2 SmoothnessandLinearDynamicalModels........... 69
4.3 ActivitySpecificModels .......................... 70
4.4 Physics-basedMotionModels...................... 72
5 Inference ............................................... 73
5.1 ParticleFilter .................................... 74
5.2 AnnealedParticleFilter ........................... 75
5.3 MarkovChainMonteCarloFiltering ................ 78
6 InitializationandFailureRecovery.......................... 79
6.1 Introductionto DiscriminativeMethodsfor Pose
Estimation ...................................... 80
6.2 DiscriminativeMethodsasProposalsforInference .... 82
7 Conclusions............................................. 82
References.................................................... 83
LocomotionActivitiesinSmartEnvironments ...................... 89
BjörnGottfried
1 Introduction............................................. 89
1.1 WhyLocomotionMatters.......................... 89
1.2 Overview ....................................... 90
2 RelatedWorkonMotionAnalysisandSmartEnvironments..... 90
2.1 MotionParameters ............................... 91
2.2 Precision........................................ 91
2.3 Viewpoint....................................... 92
2.4 Wayfinding...................................... 92
Contents vii
2.5 Modelling....................................... 93
2.6 Summary ....................................... 94
3 LocomotionActivitiesinSmartEnvironments ................ 94
3.1 SmartHospitals.................................. 94
3.2 ScenariosinaSmartHospital ...................... 96
3.3 CharacterisingLocomotionActivities................ 98
4 TheRepresentationofLocomotionActivities................. 101
4.1 SpatiotemporalInformation........................ 101
4.2 FunctionalSpecification........................... 102
4.3 AllocentricView ................................. 104
5 LocomotionBasedAlgorithms ............................. 104
5.1 PlanningScenario ................................ 105
5.2 WayfindingScenario.............................. 106
5.3 SearchingScenario ............................... 106
5.4 MonitoringScenario.............................. 108
6 Discussion .............................................. 109
7 Outlook ................................................ 110
8 Summary ............................................... 111
References.................................................... 112
TrackinginUrbanEnvironmentsUsing SensorNetworksBasedon
Audio-VideoFusion ............................................ 117
ManishKushwaha,SonghwaiOh,IsaacAmundson,XenofonKoutsoukos,
AkosLedeczi
1 Introduction............................................. 117
2 ChallengesandRelatedWork .............................. 119
3 Architecture............................................. 121
4 AudioBeamforming...................................... 123
5 VideoTracking .......................................... 125
6 TimeSynchronization .................................... 128
6.1 SynchronizationMethodology...................... 128
6.2 EvaluationofHSNTimeSynchronization ............ 129
6.3 SynchronizationService........................... 130
7 MultimodalTargetTracking ............................... 131
7.1 SequentialBayesianEstimation..................... 132
7.2 SensorModels................................... 134
7.3 Multiple-TargetTracking .......................... 136
8 Evaluation .............................................. 137
8.1 SequentialBayesianEstimation..................... 137
8.2 MCMCDA ...................................... 141
9 Conclusions............................................. 144
References.................................................... 145
viii Contents
Multi-CameraVisionforSurveillance ............................. 149
NorikoTakemuraandHiroshiIshiguro
1 Introduction............................................. 149
2 CameraSystems ......................................... 150
2.1 FixedCamera.................................... 150
2.2 ActiveCamera................................... 152
2.3 MixedSystem ................................... 152
2.4 Multi-modalSystem .............................. 154
2.5 SurveillanceIssues ............................... 154
2.6 LocationandSubjects............................. 156
2.7 Occlusion....................................... 156
3 CaseStudies ............................................ 157
3.1 Real-timecooperativemulti-targettrackingbydense
communicationamongActiveVisionAgents ......... 157
3.2 TrackingMultipleOccludingPeoplebyLocalizingon
MultipleScenePlanes............................. 158
3.3 ApplyingaFormofMemory-basedAttentionControl
toActivityRecognitionataSubwayStation .......... 160
3.4 DMCtrac:DistributedMultiCameraTracking........ 161
3.5 Abnormal behavior-detection using sequential
syntacticalclassification in a networkofclustered
cameras......................................... 163
4 IndustrySystems......................................... 163
5 Conclusion.............................................. 164
6 FurtherReading ......................................... 165
References.................................................... 165
PartIII MobileandPervasiveComputing
CollaborationSupportforMobileUsersinUbiquitousEnvironments... 173
BabakA.FarshchianandMonicaDivitini
1 Introduction............................................. 173
2 CharacteristicsofCollaboration ............................ 174
2.1 CollaborationandSharedContext................... 174
2.2 EmbodiedInteractionsandArtifactsasResources ..... 177
2.3 MobilityofPeopleandResources................... 178
2.4 PhysicalDistributionofPeople ..................... 178
2.5 FlexibilityandtheNeedforTailoring................ 179
3 ExistingTechnologyinSupportofUbiquitousCollaboration.... 180
4 HumanGridasaUnifyingConceptforAmIandCSCW........ 181
4.1 TheExampleofUbiBuddy......................... 183
4.2 SharedContextinHumanGrid ..................... 186
4.3 EmbodimentinHumanGrid ....................... 186
4.4 MobilityinHumanGrid........................... 187
4.5 SupportforPhysicalDistributioninHumanGrid ...... 187
Contents ix
4.6 FlexibilityandTailoringinaHumanGrid ............ 187
5 ImplementationofHumanGrid:TheUbiCollabPlatform....... 188
5.1 UbiNodeOverallArchitecture...................... 189
5.2 CollaborationInstanceManager .................... 190
5.3 SessionManager ................................. 192
5.4 CollaborationSpaceManager ...................... 192
5.5 ServiceDomainManager.......................... 193
5.6 ResourceDiscoveryManager ...................... 193
5.7 IdentityManager................................. 194
6 Conclusions............................................. 195
7 Acknowledgements ...................................... 196
References.................................................... 196
PervasiveComputingMiddleware ................................ 201
GregorSchiele,MarcusHandteandChristianBecker
1 Introduction............................................. 201
2 DesignConsiderations .................................... 202
2.1 OrganizationalModel............................. 202
2.2 ProvidedLevelofAbstraction...................... 204
2.3 SupportedTasks ................................. 205
3 SpontaneousInteraction................................... 206
3.1 UbiquitousCommunicationandInteraction........... 207
3.2 IntegrationofHeterogeneousDevices ............... 210
3.3 DynamicMediation............................... 211
4 ContextManagement..................................... 214
4.1 AcquisitionandFusion............................ 216
4.2 ModelingandDistribution ......................... 217
4.3 ProvisioningandAccess........................... 218
5 ApplicationAdaptation ................................... 218
5.1 Inter-ApplicationAdaptation....................... 219
5.2 Intra-ApplicationAdaptation....................... 222
6 Conclusion.............................................. 224
References.................................................... 225
CaseStudy ofMiddleware InfrastructureforAmbient Intelligence
Environments ................................................. 229
TatsuoNakajima
1 Introduction............................................. 229
2 HighLevelAbstraction ................................... 232
3 CaseStudies ............................................ 233
3.1 MiddlewareInfrastructureforDistributedAudioand
VideoAppliances ................................ 233
3.2 MiddlewareInfrastructuretoHideComplexDetailsin
UnderlyingInfrastructures......................... 237
3.3 MiddlewareInfrastructuretoSupportSpontaneous
SmartObjectIntegration .......................... 241
x Contents
3.4 MiddlewareInfrastructureforContextAnalysis ....... 245
4 MiddlewareDesignIssuesforAmbientIntelligence ........... 249
4.1 HighLevelAbstractionandMiddlewareDesign....... 249
4.2 Interfacev.s.Protocol............................. 249
4.3 NonFunctionalProperties ......................... 250
4.4 Portability....................................... 251
4.5 HumanFactors................................... 251
5 FutureDirections ........................................ 253
References.................................................... 253
CollaborativeContextRecognitionforMobileDevices ............... 257
PerttiHuuskonen,JaniMäntyjärviandVilleKönönen
1 Introduction............................................. 257
1.1 Humans:Context-awareAnimals ................... 258
2 ContextFromCollaboration ............................... 259
3 MobileContextAwareness ................................ 260
3.1 ContextSources.................................. 260
3.2 ApplicationAreas ................................ 262
3.3 ContextRecognition.............................. 263
3.4 DistributedContextAwareness ..................... 264
4 MakingRationalDecisions ................................ 264
4.1 DistributedDecisionMaking....................... 265
4.2 Voting Protocolsas Distributed Decision Making
Strategies ....................................... 265
4.3 VotingasCCRMethod............................ 266
5 CaseStudy:PhysicalActivityRecognition ................... 270
5.1 DataSetandTestSettings ......................... 270
5.2 EmpiricalResults ................................ 272
6 ContextRecognitionPlatform.............................. 273
7 TheWayForward........................................ 274
7.1 EnergySavings .................................. 274
7.2 Risks........................................... 275
7.3 Knowledge-basedCCR?........................... 276
References.................................................... 277
SecurityIssuesinUbiquitousComputing .......................... 281
FrankStajano
1 FundamentalConcepts.................................... 281
1.1 Ubiquitous(Pervasive,Sentient,Ambient...)Computing 282
1.2 Security ........................................ 284
1.3 SecurityIssuesinUbiquitousComputing............. 286
2 ApplicationScenariosandTechnicalSecurityContributions .... 287
2.1 WearableComputing ............................. 288
2.2 LocationPrivacy ................................. 289
2.3 RFID........................................... 292
2.4 AuthenticationandDevicePairing .................. 298