ICT Applications for Smart Cities

212 Pages·2022·7.06 MB·English

by  Angel D. Sappa

Intelligent Systems Reference Library 224
Angel D. Sappa   Editor
ICT Applications
for Smart Cities
Intelligent Systems Reference Library
Volume 224
SeriesEditors
JanuszKacprzyk,PolishAcademyofSciences,Warsaw,Poland
LakhmiC.Jain,KESInternational,Shoreham-by-Sea,UK
The aim of this series is to publish a Reference Library, including novel advances
and developments in all aspects of Intelligent Systems in an easily accessible and
wellstructuredform.Theseriesincludesreferenceworks,handbooks,compendia,
textbooks,well-structuredmonographs,dictionaries,andencyclopedias.Itcontains
wellintegratedknowledgeandcurrentinformationinthefieldofIntelligentSystems.
Theseriescoversthetheory,applications,anddesignmethodsofIntelligentSystems.
Virtuallyalldisciplinessuchasengineering,computerscience,avionics,business,
e-commerce,environment,healthcare,physicsandlifescienceareincluded.Thelist
oftopicsspansalltheareasofmodernintelligentsystemssuchas:Ambientintelli-
gence,Computationalintelligence,Socialintelligence,Computationalneuroscience,
Artificiallife,Virtualsociety,Cognitivesystems,DNAandimmunity-basedsystems,
e-Learningandteaching,Human-centredcomputingandMachineethics,Intelligent
control,Intelligentdataanalysis,Knowledge-basedparadigms,Knowledgemanage-
ment, Intelligent agents, Intelligent decision making, Intelligent network security,
Interactive entertainment, Learning paradigms, Recommender systems, Robotics
and Mechatronics including human-machine teaming, Self-organizing and adap-
tive systems, Soft computing including Neural systems, Fuzzy systems, Evolu-
tionarycomputingandtheFusionoftheseparadigms,PerceptionandVision,Web
intelligenceandMultimedia.
IndexedbySCOPUS,DBLP,zbMATH,SCImago.
AllbookspublishedintheseriesaresubmittedforconsiderationinWebofScience.
Angel D. Sappa
Editor
ICT Applications for Smart
Cities
Editor
AngelD.Sappa
EscuelaSuperiorPolitécnicadelLitoral
Guayaquil,Ecuador
ComputerVisionCenter
Barcelona,Spain
ISSN 1868-4394 ISSN 1868-4408 (electronic)
IntelligentSystemsReferenceLibrary
ISBN 978-3-031-06306-0 ISBN 978-3-031-06307-7 (eBook)
https://doi.org/10.1007/978-3-031-06307-7
©TheEditor(s)(ifapplicable)andTheAuthor(s),underexclusivelicensetoSpringerNature
SwitzerlandAG2022
Thisworkissubjecttocopyright.AllrightsaresolelyandexclusivelylicensedbythePublisher,whether
thewholeorpartofthematerialisconcerned,specificallytherightsoftranslation,reprinting,reuse
ofillustrations,recitation,broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,and
transmissionorinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilar
ordissimilarmethodologynowknownorhereafterdeveloped.
Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication
doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant
protectivelawsandregulationsandthereforefreeforgeneraluse.
Thepublisher,theauthors,andtheeditorsaresafetoassumethattheadviceandinformationinthisbook
arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor
theeditorsgiveawarranty,expressedorimplied,withrespecttothematerialcontainedhereinorforany
errorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregardtojurisdictional
claimsinpublishedmapsandinstitutionalaffiliations.
ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG
Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland
Preface
By2050,itispredictedthat85%oftheworld’spopulationwouldmaketheirhomesin
cities.Inthecomingdecades,urbancentersarelikelytofaceanincreasingnumberof
problems,someofwhicharelinkedtoissuessuchas(a)monitoringandmaintenance
of urban heritage, (b) traffic planning in urban environments, (c) efficient use of
energyandtheuseofrenewableresources,(d)earlywarningsystems,and(e)optimal
managementofresourcesinemergencysituations,amongothers.
In recent years, different solutions to these problems have been suggested and
raised under the umbrella of what has been called “Smart Cities”. A Smart City
can be described as a citythat applies Information and Communication Technolo-
gies(ICTs)toprovideitwithaninfrastructurethatguaranteesthefollowingamong
others:(i)sustainabledevelopment,(ii)anincreaseinthequalityoflifeofcitizens,
(iii) greater efficiency of available resources, and (iv) active citizen participation.
Therefore,aSmartCityisasocially,economically,andenvironmentallysustainable
city,maintainingabalancebetweentheseaspectsandalwayshavingtheindividual
(thecitizen)asthemainbeneficiary.
ThisbookpresentsdifferentsuccessfulcasestudiesofICTsintheapplicationof
SmartCities.Theseprototypesweredevelopedandevaluatedintheframeworkofthe
Ibero-AmericanResearchNetworkTICs4CIfundedbytheCYTEDprogram.This
networkstartedin2018andlastfor5yearsinvolvingmorethan50researchersfrom
eightresearchinstitutionshailingfromsevenIbero-Americancountries.Morespecif-
ically,thebookdescribesunderlyingtechnologiesandpracticalimplementationsof
severalapplicationsdevelopedinthefollowingareas:
(cid:129)
Urbanenvironmentmonitoring.
(cid:129)
Intelligentmobility.
(cid:129)
Wasterecyclingprocesses.
(cid:129)
Computer-aideddiagnosisinhealthcaresystems.
(cid:129)
Computervision-basedapproachesforefficiencyinproductionprocesses.
Guayaquil,Ecuador AngelD.Sappa
March2022
v
Acknowledgements
This book would not have been possible without the collaboration and support of
severalpeople.Firstandforemost,IwouldliketothankallmembersoftheTICs4CI
Ibero-AmericanNetworkandtheirinstitutions,whodevelopedthedifferentcontribu-
tionsandprototypesundertheumbrellaofSmartCityapplications.Researchonthese
topicshelpedtofindfruitfulcollaborationsamongthepartnersofthenetworkandto
contributetothestateoftheart.SpecialthankstoProf.ÁngelSanchez,fromUniver-
sidadReyJuanCarlos(Madrid,Spain),whomotivatedthesetupofthisnetworka
coupleofyearsbeforethecollaborationamongourpartnersstarted;afterallthese
years,differentapplications, research collaborations, and mobility actions become
arealityallowingthevalidationofmodelsandprototypesrelevantforSmartCities.
Specialthanksaswelltoalltheresearchersandengineersfromthedifferentinstitu-
tionswhocontributedwiththeirworkduringalltheseyears.Finally,Iwishtothank
theCYTEDprogramforthefinancialsupportthroughthe“Ibero-AmericanThematic
NetworkonICTApplicationsforSmartCities”(REF-518RT0559).Withoutadoubt,
thisprojectisjustthebridgebuilttodrivefurtherandstrongercollaborationsamong
thedifferentpartnersoftheTICs4CInetwork.
vii
viii Acknowledgements
Contents
1 ArtGraffitiDetectioninUrbanImagesUsingDeepLearning ..... 1
TacioSouzaBomfim, ÉldmandeOliveiraNunes,
andÁngelSánchez
1.1 Introduction ............................................. 1
1.2 DetectionofArtGraffiti ................................... 3
1.3 ObjectDetectionDeepArchitectures ........................ 4
1.3.1 YOLOModels ................................... 4
1.3.2 YOLOv4 ........................................ 5
1.3.3 YOLOv5 ........................................ 5
1.3.4 YOLOv4-tiny .................................... 6
1.4 Dataset ................................................. 7
1.5 Experiments ............................................. 9
1.5.1 EvaluationMetricsandComputingResources ........ 9
1.5.2 Experiments ..................................... 10
1.6 Conclusion .............................................. 18
References .................................................... 19
2 DeepNeuralNetworksforPassengers’DensityEstimation
and Face Mask Detection for COVID-19 in Public
TransportationServices ........................................ 21
RogelioHasimoto-Beltran, OdinF.Eufracio-Vazquez,
andBereniceCalderon-Damian
2.1 Introduction ............................................. 22
2.2 ProposedArchitecture .................................... 25
2.3 DeepLearningforObjectDetection ......................... 27
2.4 ExperimentsandResults .................................. 30
2.5 ConclusionsandFutureWork .............................. 33
References .................................................... 34
ix
x Contents
3 EpistemicUncertaintyQuantificationinHumanTrajectory
Prediction .................................................... 37
MarioCanche,RanganathKrishnan,andJean-BernardHayet
3.1 Introduction ............................................. 37
3.2 RelatedWorkandProblemStatement ....................... 38
3.3 QuantificationofAleatoricandEpistemicUncertainties ........ 40
3.3.1 BayesianDeepLearning ........................... 40
3.3.2 UncertaintyEstimationThroughBayesianDeep
Learning ........................................ 41
3.4 EvaluatingandCalibratingUncertainties .................... 42
3.4.1 CalibrationofUncertaintiesin1DRegression ......... 43
3.4.2 HighestDensityRegions ........................... 44
3.4.3 HDR-BasedCalibration ........................... 45
3.5 Experiments ............................................. 47
3.5.1 TrajectoryPredictionBaseModelandBayesian
Variants ......................................... 47
3.5.2 ImplementationDetails ............................ 49
3.5.3 EvaluationoftheUncertaintiesQuality .............. 50
3.5.4 EvaluationoftheRe-calibrationProcess ............. 51
3.6 Conclusions ............................................. 54
References .................................................... 54
4 AutomaticDetectionofKnivesinComplexScenes ................ 57
MairaMoran,AuraConci,andÁngelSánchez
4.1 Introduction ............................................. 58
4.2 RelatedWork ............................................ 59
4.3 YOLOv4ArchitectureforDetectionofKnives ............... 60
4.3.1 DetectionofKnives ............................... 60
4.3.2 YOLOv4 ........................................ 61
4.4 Datasets ................................................ 63
4.4.1 DaSCIDataset ................................... 63
4.4.2 MSCOCODataset ................................ 65
4.4.3 KnifeClassificationDatasets ....................... 66
4.5 Pre-processingsonDataset ................................ 67
4.5.1 DatasetPreparation ............................... 67
4.5.2 DatasetVariabilities ............................... 68
4.5.3 TransferLearning ................................. 69
4.6 ExperimentalResults ..................................... 70
4.6.1 DescriptionofPerformanceMetrics ................. 70
4.6.2 ExperimentalResults .............................. 71
4.6.3 GeneralResults ................................... 72
4.6.4 ResultsConsideringVariabilitiesinImages ........... 73
4.7 Conclusion .............................................. 75
References .................................................... 76