s Sensor k o o B Sensors and Actuators I P in Smart Cities D Edited by Mohammad Hammoudeh and Mounir Arioua Printed Edition of the Special Issue Published in JSAN M www.mdpi.com/journal/jsan s k Sensors and Actuators in Smart Cities o o B Special Issue Editors Mohammad Hammoudeh Mounir Arioua I P D MDPI•Basel•Beijing•Wuhan•Barcelona•Belgrade M s SpecialIssueEditors k MohammadHammoudeh ManchesterMetropolitanUniversity UK o MounirArioua AbdelmalekEssaadiUniversity Morocco o EditorialOffice MDPI B St.Alban-Anlage66 Basel,Switzerland ThiseditionisareprintoftheSpecialIssuepublishedonlineintheopenaccessjournalJournalofSensor andActuatorNetworks(ISSN2224-2708)from2013–2014(availableat:http://www.mdpi.com/journal/ jsan/specialissues/smartcities). Forcitationpurposes,citeeacharticleindependentlyasindicatedonthearticlepageonliIneandas indicatedbelow: P Lastname,F.M.;Lastname,F.M.Articletitle.JournalNameYear,Articlenumber,pagerange. FirstEditon2018 D ISBN978-3-03842-873-2(Pbk) ISBN978-3-03842-874-9(PDF) ArticlesinthisvolumeareOpenAccessanddistributedundertheCreativeCommonsAMttribution (CCBY)license, whichallowsuserstodownload, copyandbuilduponpublishedarticleseven forcommercialpurposes,aslongastheauthorandpublisherareproperlycredited,whichensures maximum dissemination and a wider impact of our publications. The book taken as a whole is (cid:2)c 2018MDPI,Basel,Switzerland,distributedunderthetermsandconditionsoftheCreativeCommons licenseCCBY-NC-ND(http://creativecommons.org/licenses/by-nc-nd/4.0/). s Table of Contents k AbouttheSpecialIssueEditors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v MohammadHammoudehandMounirArioua SensorsandActuatorsinSmartCities o doi:10.3390/jsan7010008 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 TianyuZhang,QianZhao,KilhoShinandYukikazuNakamoto Bayesian-Optimization-Based Peak Searching Algorithm for Clustering in Wireless SensorNetworks doi:10.3390/jsan7010002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .o. . . . . . 5 Abdelhamied A. Ateya, Ammar Muthanna, Irina Gudkova, Abdelrahman Abuarqoub, AnastasiaVybornovaandAndreyKoucheryavy DevelopmentofIntelligentCoreNetworkforTactileInternetandFutureSmartSystems doi:10.3390/jsan7010001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 B JieJiang,RiccardoPozza,Kristru´nGunnarsdo´ttir,NigelGilbertandKlausMoessner UsingSensorstoStudyHomeActivities† doi:10.3390/jsan6040032 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 DiegoCastro,WilliamCoral,CamiloRodriguez,JoseCabraandJulianColorado Wearable-BasedHumanActivityRecognitionUsinganIoTApproach doi:10.3390/jsan6040028 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 YounessRiouali,LailaBenhlimaandSlimaneBah ExtendedBatchesPetriNetsBasedSystemforRoadTrafficManagementinWSNs† doi:10.3390/jsan6040030 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 YorghosVoutos,PhivosMylonas,EvaggelosSpyrouandEleniCharou I ASocialEnvironmentalSensorNetworkIntegratedwithinaWebGISPlatform doi:10.3390/jsan6040027 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Vincenzo Catania, Giuseppe La Torre, Salvatore Monteleone, Daniela Panno Pand DavidePatti User-GeneratedServicesCompositioninSmartMulti-UserEnvironments doi:10.3390/jsan6030020 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 AlexAdimObinikpoandBurakKantarci BigSensedDataMeetsDeepLearningforSmarterHealthCareinSmartCities D doi:10.3390/jsan6040026 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Dhafer Ben Arbia, Muhammad Mahtab Alam, Abdullah KadrI, Elyes Ben Hamida and RabahAttia EnhancedIoT-BasedEnd-To-EndEmergencyandDisasterReliefSystem doi:10.3390/jsan6030019 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 M iii s k o o B I P D M s About the Special Issue Editors k MohammadHammoudeh, PhD,iscurrentlytheHeadoftheMMUIoTLaboratoryandaSenior Lecturer in computer networks and security with the School of Computing, Math and Digital Technology,ManchesterMetropolitanUniversity.Hehasbeenaresearcherandpublisherinthefield o ofbigsensorydataminingandvisualization.Dr.Hammoudehisahighlyproficient,experienced,and professionallycertifiedcybersecurityprofessional,specializinginthreatanalysis,andinformation andnetworksecuritymanagement.Hisresearchinterestsincludehighlydecentralizedalgorithms, communication,cross-layeredsolutionstotheInternetofThings,andwirelesssensornetworks. o MounirArioua,PhD,iscurrentlyanassociateprofessorattheNationalSchoolofAppliedSciences ofTetuan,UniversityofAbdelmalekEssaadi. HereceivedhisPhDdegreeinTelecommunications andComputerScienceandjoinedtheNationalSchoolofAppliedSciencesofMarrakechasaresearch assistant.Heisamemberofvariousinternationalscientificorganizationsandorganizingandscientific B committeesofmanyinternationalworkshopsandconferencesandarefereeofseveralinternational journals.Hehasauthoredorco-authoredmorethan50papersinrecognizedjournalsandinternational conferences.Hisresearchinterestsincludecommunicationreliability,datacompressioninwireless sensornetworksandembeddedsystem-basedwirelesscommunication,andtheInternetofThings. I P D M v s k o o B I P D M s Journal of Sensor and Actuator Networks k Editorial Sensors and Actuators in Smart Cities MohammadHammoudeh1,*,†andMounirArioua2,† o 1 SchoolofComputing,Mathematics&DigitalTechnology,ManchesterMetropolitanUniversity, ManchesterM156BH,UK 2 NationalSchoolofAppliedSciences,AbdelmalekEssaadiUniversity,Tétouan93000,Morocco; [email protected] * Correspondence:[email protected];Tel.:+44-(0)161-247-2845 † Theseauthorscontributedequallytothiswork. o Received:9February2018;Accepted:14February2018;Published:16February2018 1.ScopeandAim B Withthecity,fromitsearliestemergenceintheNearEastbetween4500and3100BCE,camea widerangeofnewdiscoveriesandinventions,fromsyntheticmaterialstowheeledvehicles.Through itsdensepopulation,irrigation,socialcontinuityandphysicalsecurity,emergedcivilengineering, monumentalconstruction,sculpture,mathematics,artsandlaw. Today,thereisanenormousset ofideasandnotionswithrespecttoourwaysofliving, e.g., therampandthelever, whichare stillfundamentaltocities’environmental,social,andeconomicstructures.Modern-daysmartcities competefortheintroductionofsmarttechnologiesandapplicationstoimprovekeyareasofurban communities,suchassystemautomation,sustainability,andqualityoflife. Technologyresearch expertspaintthrillingimagesoffuturisticcities. What’sglossedover,however,isthesensorand actuatortechnologiesthatenablethesesmartcities;inparticular,thereliable,heterogeneous,wireless networksspecificallydesignedtoprovisioncommunicationacrossacountlessnumberofsensors embeddedinalmosteverything. TheworldisonthevergeofanewepochofinnovationandchangewiththeemergenceoIfWireless SensorNetworks(WSN).Theconvergenceofsmaller,morepowerfulprocessors,smartmobiledevices, low-costsensing,bigdataanalytics,cloudhostingandnewlevelsofconnectivityallowedbythe InternetisfuellingthelatestwaveofMachine-to-Machine(M2M)technology. ThemerPitsofthis marriageofmachinesandthedigitalworldaremultipleandsignificant. Itholdsthepotentialto dramaticallyalterthewayinwhichmostglobalindustries,suchasbuildings,railtransportation, powergridsandhealthcareoperateondailybasis.WSNsexpandtoincludeourvehiclesandhomes,as wellasnewlydevelopedwearableandimplantedsensors,whichbringsfundamentaltransformations tomanyaspectsofdailylife. WSNinnovationspromiseto integrate andoptimisesmartbuildings, autonomousDvehicles, powergrids,etc.,toenableasuccessfultransitiontowardssmart,user-drivenanddemand-focused cityinfrastructuresandservices[1,2]. Thereisawiderangeofcurrentsmartcitiesapplications, whichmakeourliveseasierandmoreefficient,e.g.,asmartphoneapplicationthatletusersfindfree parkingspacesinthecentreoftown.However,citiesarenotoriouslyinefficient.Aspopulationsgrow, everythingfromgarbagecollectionandpublictransportbecomesmoreexpensiveandcomplex.Away fromincreasingspending,thereisalsoademandfromcitizensforsmarterservicesdrivenbysensor- M andactuator-basedinfrastructure. InthisSpecialIssue,weacceptedsubmissionsthatfocusonimplementingintelligentsensing infrastructuretosolvethesmartcitiesconundrum. ThisSpecialIssueattractedcontributionsfrom academic researchers in computer science, communication engineering and physics, as well as informationtechnologyindustryconsultantsandpractitioners,invariousaspectsofsensorsand J.Sens.ActuatorNetw. 2018,7,8 1 www.mdpi.com/journal/jsan s J.Sens.ActuatorNetw. 2018,7,8 actuatorsforsmartcities. Inthenextsection,wepresentabriefreviewofthepapekrspublished, highlightingtheirobjectivesandcontributions. 2.AReviewofContributionsinthisSpecialIssue Zhangetal. [3]addressthechallengeoflargescaledataanalyticsforsmartcities. Typically, o multi-modalsensordatacollectedfromcyberphysicalenvironments, suchassmartcities, must beprocessedbeforeitcanbecanbeusedbydatadiscovery, integrationandmash-upprotocols. Withheterogeneous,noisyandincompletedata,clusteringalgorithmsareusedtoorganisethedata inadatasetintoclusters. TheauthorsproposeanewpeaksearchingalgorithmthatusesBayesian optimisationtofindprobabilitypeaksinadatasettoincreasethespeedandaccuracyofdataclustering algorithms.Thisproposedclusteringalgorithmwasthoroughlyevaluatedinsimulationandresults o showthatitsignificantlydecreasestherequirednumberofclusteringiterations(by1.99to6.3times), andproduceclusteringwhich,forasyntheticdataset,is1.69to1.71timesmoreaccuratethanitisfor traditionalexpectation-maximization(EM).Moreover,thealgorithmcorrectlyidentifiedtheoutliersin arealdataset,decreasingiterationsbyapproximately1.88times,whilebeing1.29timesmoreaccurate thanEMatamaximum. Ateyaetal. [4]contributionaddressesthedevelopmentofintelligentcorenetwoBrkforTactile Internetandfuturesmartsystems.TactileInternetisanextremelylowlatencycommunicationnetwork withhighavailability,reliabilityandsecurity.TactileInternetispredictedtobringanewdimensionto human-to-humanandhuman-to-machineinteractioninamultitudeofdifferentsmartcityaspects suchtransport,powergrid,education,healthcareandculture.ThispaperpresentsaTactileInternet systemstructure,whichemployssoftwaredefinednetworkinginthecoreofthecellularnetworkand mobileedgecomputingatmulti-levels.Thecontributionfocusesonthestructureofthecorenetwork. Theproposedsystemissimulatedunderreliableenvironmentalconditionsandresultsshowsthatit achievedaroundtriplatencyofordersof1msbythereducingthenumberofintermediatenodesthat areinvolvedinthecommunicationprocess. Jiangetal.[5]addresstheproblemofestablishingagoodmeasureoftheagreementbetween the activities detected from sensor-generated data and those recorded in self-reported data. Thecontributionreportsonatrialconductedinthreesingle-occupancyhouseholdsfromwhiIchdatais collectedfromasetofsensorsandfromtimeusediariescompletedbytheoccupants. Theauthors demonstrate the applicationof Hidden Markov Modelswith featuresextracted from mean-shift clustering and change points analysis. Then, a correlation-based feature selection is aPpplied to reducethecomputationalcost.Finally,amethodbasedonLevenshteindistanceformeasuringthe agreementbetweenthesensor-detectedactivitiesandthatreportedbytheparticipantsisdemonstrated. Theauthorsconcludetheirpaperbyanexcitingdiscussiononlessonslearntonhowthefeatures derivedfromsensordatacanbeusedinactivityrecognitionandhowtheyrelatetoactivitiesrecorded intimeusediaries. Takingtheworkinthepreviouscontribution[5]onestepfurther,Castroetal. [6]presenta D systembasedontheInternetofThings(IoT)toHumanActivityRecognition(HAR)thatmonitors vitalbodysignsremotely.Theauthorsemploymachinelearningalgorithmstodetermineactivities thatoccurwithinfourpre-definedcategories(lie,sit,walkandjog). Evaluationusingadvanced real-worldhardwareplatformshowsthattheproposedsystemisabletogivefeedbackduringand aftertheactivityisperformed,usingaremotemonitoringcomponentwithremotevisualizationand programmablealarms.Thissystemwassuccessfullyimplementedwitha95.83%successratio. ThecontributionofRioualietal. [7]addressesanothervitalareaofsensingandactMuationin smartcities.Theauthorspresentaroadtrafficmanagementsystembasedonwirelesssensornetworks. Thispaperintroducesthefunctionalanddeploymentarchitectureofthissystemwithparticularfocus onthedataanalyticscomponent,whichusesanewextensionofbatchesPetrinetsformodellingroad trafficflow.Theevaluationoftheproposedsystemwasperformedusingarealworldimplementation ofvisualizationanddataanalysiscomponents. 2 s J.Sens.ActuatorNetw. 2018,7,8 Voutosetal. [8]presentasocialenvironmentalsensornetworkintegratedwithkinawebGIS platform.Controls,userinterfaceandextensionsoftheproposedsystemarepresented.Thekeynovel aspectofthiscontributionisthefactthatthegathereddatafromtheproposedsystemcarriesspatial information,whichisfundamentalforthesuccessfulcorrelationbetweenpollutantsandtheirplaceof origin.ThelatterisimplementedbyaninteractiveWebGISplatformoperatingoversightinsituand onatimelinebasis. o Cataniaetal.[9]contributeauser-generatedservicescompositioninsmartmulti-userenvironments. Inthiscontribution,thefocusisonsecurityissuesraisedbyservicesgeneratedbyusers,User-Generated Services(UGSs). UGSsarecharacterizedbyasetoffeaturesthatdistinguishthemfromconventional services.TocopewithUGSsecurityproblems,theauthorsintroducethreedifferentpolicymanagement models,analysingbenefitsanddrawbacksofeachapproach.Finally,acloud-basedsolutionthatenables o thecompositionofmultipleUGSsandpolicymodels,allowingusers’devicestosharefeaturesand servicesinIoTbasedscenariosisproposed. Obinikpoetal.’s[10]contributiondemonstrateshowbigsenseddatameetsdeeplearningfor smarterhealthcareinsmartcities. HealthcarelendsitselfasanaturalfitforIoTtechnologyand smartcityconcepts.Theauthorsadvocatethatintegratingsensorydata(hardsensing)withexternal datasources(soft sensing, e.g., crowd-sensing) couldrevealnew datapatternsandBinformation. Thisresearchaddressesthischallengethroughhiddenperceptionlayersintheconventionalartificial neuralnetworks,namelybydeeplearning.Thepaperstartsbyreviewingdeeplearningtechniques thatcanbeappliedtosenseddatatoimprovepredictionanddecisionmakinginsmarthealthservices. Then,acomparisonandtaxonomyofthesemethodologiesbasedontypesofsensorsandsenseddatais presented.Finally,athoroughdiscussionsontheopenissuesandresearchchallengesineachcategory isgiven. Arbiaetal.’s[11]contributiontargetssmartcitycriticalinfrastructure,particularly,anIoTenabled end-to-endemergencyanddisasterreliefsystem. Thispaperpresentsanewenhancementforan emergencyanddisasterreliefsystemcalledCriticalandRescueOperationsusingWearableWireless sensorsnetworks(CROW2). CROW2addressesthereliabilitychallengesinsettingupawireless autonomouscommunicationsystemtooffloaddatafromthedisasterarea(rescuers,trappedvictims, civilians,media,etc.)backtoacommandcentre.Theproposedsystemconnectsdeployedrescuers I toextendednetworksandtheInternet. Thesystemintegratesheterogeneouswirelessdevicesand differentcommunicatingtechnologiestoenableend-to-endnetworkconnectivity,whichismonitored byacloud-basedIoTplatform.TheoverallperformanceofCROW2isevaluatedusingend-to-end P linkqualityestimation,throughputandend-to-enddelay.Finally,thesystemarchitectureisvalidated throughdeploymentandmotiondetectionandlinksunavailabilitypreventionarehighlighted. 3.ConclusionsandRemarks Sensorsandactuatorsarethebuildingblocksfortheforthindustrialrevolution. Theyhave alreadytransformedthewayhumansperceivetheirenvironment. Sensor-enabledsmartcitiesare D pavingthewayforamoresustainablefuture,fromurbanplanningtosocialconscience.Thepapers publishedinthisspecialissueputhumansatthecentreofsmartcities. Fromtrafficmanagement toassistedliving,humancentreddesignofsmartcityservicesisadetrimentalfactortothesuccess ofsmartcities. Itisevidentthatwearestillatthestartofthesmartcitiesrevolutionandthefull economical,environmentalandsocialbenefitsareyettobeachieved. ConflictsofInterest:Theauthorsdeclarenoconflictofinterest. M References 1. Coates,A.;Hammoudeh,M.;Holmes,K.G.InternetofThingsforBuildingsMonitoring:Experiencesand Challenges. InProceedingsoftheInternationalConferenceonFutureNetworksandDistributedSystems, ICFNDS’17,Cambridge,UK,19–20July2017;ACM:NewYork,NY,USA,2017. 3