ASU Internet of Things Primer - cynthiaselin.com€¦ · 5.1 Embracing the Internet of Everything...

Internet of Things Primer CNS-ASU Report #R16-0001

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THEINTERNETOFTHINGS:APRIMER

LaurenWithycombeKeeler,VisitingAssistantProfessor,SchoolfortheFutureofInnovationinSociety//CenterfortheStudyoftheFuture,ArizonaStateUniveristyAykutDengi,ResearchAssociateProfessor,SchoolofComputing,Informatics,andDecisionSystemsEngineering,ArizonaStateUniversity August 2016 CNS-ASUanditsresearch,educationandoutreachactivitiesaresupportedbytheNationalScienceFoundationundercooperativeagreement#0937591.Anyopinions,findingsandconclusionsarethoseoftheauthorsanddonotnecessarilyreflecttheviewsoftheNationalScienceFoundation

CNS-ASU Report # R16-0001 CNS-ASU Report

SENSORS & HUMANS IN NETWORKING

ENVIRONMENTS [SHINE]



Preface ThisPrimercontainsacuratedselectionofrecentarticles,industryreportsandothermaterialsthathelptoclarifythemeaningandimportofthe“InternetofThings”.Whilethefieldisrapidlyevolvingandasyetunsettled,wehavegatheredworkstocaptureasnapshotofthecontemporarystateofthefield.ThiscollectionwasrapidlyproducedasameanstoorientparticipantsintheCenterforNanotechnologyinSociety(CNS-ASU)SensorsandHumansinNetworkingEnvironments(SHINE)workshopheldAugust15-16,2016inTempe,Arizona.TheCenterforNanotechnologyinSocietyatArizonaStateUniversity(CNS-ASU)hasforthelastdecadeengagedwithscientists,engineers,humanists,artists,politicalfiguresandthepublictoconsiderthepoliticalandethicaldimensionsofinnovationandsocio-technicalchange.CNS-ASUhasbeenworkingwithaspectrumofscienceandengineeringpartnersthroughscenarioworkshopsthatconsiderhowtechnologiescurrentlyunderdevelopmentmightevolvetoimpactandbeshapedbysocietyinunexpectedways.The“InternetofThings”ischangingrapidlyandpromisestobringbigsocietalimpacts.AdvancesinembeddingdiverseformsofautonomousICTinbodies,buildings,machinesandnaturehaveledtoanevolutionincomputingthatisrapidlyredefiningtheinterplaybetweenoureducational,productivity,energy,medical,transportationandcommunicationinfrastructuresandsystemsacrosstimeandspace.Therearenotableconcernsovertheprivacyandownershipofbiomedicalandfinancialdata.Butequallyintriguingaredeeperquestions,enthusiasmsanddisquietaboutwhatitmeanstonotonlysurveybodies,butalsotoinhabitcitiesandnaturalenvironmentsthatareconstantlyandinvisiblymediatedbyemerginginformation&communicationstechnologies(ICT).Howwillourcultural,environmentalandsocialsensibilitiesandpoliticalstructuresshapeandadapttotheseseeminglyradicalchanges?Whatnewresponsibilitiesandrisksareimpliedfordifferentplayersacrossthevaluechain/ecosystem?Howcanthinkinginadvanceaboutnewdesignsandnoveldevelopmentsimprovethelikelihoodofpreferredsocietaloutcomes?SHINE(SensorsandHumansInNetworkingEnvironments)originatedasadialoguebetweendifferentgroupsatArizonaStateUniversitywhosharethesequestionsandareinterestedinfurtheringresearchanddiscoursearoundthefutureof“internetofthings”.Ratherthanbeginningwiththeanticipatedtechnologicaladvancementofsensorsanddatacollection,SHINEtakesahuman-centeredlenstoconsiderthesocial,ethical,culturalandlegaldimensionsoftheproliferationofso-called“smart”objectsordevicesthathavethecapacitytosenseandmonitorindividualsandenvironmentsaswellasprovidefeedback,recommendationsordecisionsbasedoninformationgatheredoranalyticsperformedthroughavarietyofinteractionsandimmersions.Therefore,weseektobringtogetherengineers,technologists,artists,humanists,socialscientistsandlegalscholarsaswellaspartnersfromindustrytoconsiderapan-ASUefforttoinvestigateSHINEwithaneyetowardsadvancingscholarshipandresponsibleinventionandinnovationaroundthefutureof“internetofthings”topromotehumanwellbeing.



1. Overview1.1TheInternetofThings:AnOverview.UnderstandingtheIssuesandChallengesofaMoreConnectedWorld1.2SemantictechnologiesfortheIoT–anInter-IoTperspective1.3TheInternetofThings:TheNextGrowthEnginefortheSemiconductorIndustry

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2. IoTandtheUnderlyingTechnology2.1WhattheInternetofThings(IoT)NeedstoBecomeaReality2.2TheInternetofThings:TheNextGrowthEnginefortheSemiconductorIndustry

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3. IoTinHealthcare3.1HowCantheInternetofThingsHelptoOvercomeCurrentHealthcareChallenges3.2RegulatingHealthcareRobots:MaximizingOpportunitieswhileMinimizingRisks3.3IoTAnalyticsforSmartHealthandCare3.4How5GTechnologyEnablestheHealthInternetofThings3.5IndustrialInternetInsightsReport

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4. LawandIoT4.1CareandFeedingofPrivacyPoliciesandKeepingtheBigDataMonsteratBay:LegalConcernsinHealthcareintheAgeoftheInternetofThings4.2ALitigator'sGuidetotheInternetofThings

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5. TelecommunicationsforIoT5.1EmbracingtheInternetofEverythingtoCaptureyourShareof$14.4Trillion5.2UnderstandingtheInternetofThings(IoT)5.3OnNetworkingofInternetofThings:ExplorationsandChallenges

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6. IndustrialIoT6.1InternetofThingsforIndustrialAutomation–ChallengesandTechnicalSolutions6.2Industry4.0:TheFutureofProductivityandGrowthinManufacturingIndustries6.3ForgingLinksintoLoops:TheInternetofThings’PotentialtoRecastSupplyChainManagement6.4PrecisionAgricultureTechnologyforCropFarming

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7. CyberSecurity7.1MobileCybersecurityintheInternetofThings:EmpoweringM2MCommunication7.2SecurityintheInternetofThings:AReview

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8. SmartCity8.1TowardsaSmartCityBasedonCloudofThings,aSurveyontheSmartCityVisionandParadigms8.2BuildingSmartCities8.3TheSpectrumofControl:ASocialTheoryoftheSmartCity

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9. AutomatedTransportation9.1AutomatedVehicleResearch9.2PreparingaNationforAutonomousVehicles:Opportunities,BarriersandPolicyRecommendations

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10. BigDataAnalyticsandIoT 3811. IoTStandards

11.1AworldwithmoreIoTbodiesthanstandards

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1. Overview1.1 The Internet of Things: An Overview. Understanding the Issues and Challenges of a MoreConnectedWorldKarenRose,ScottEldridge,LymanChapin(October2015),TheInternetSocietyThedefinitionofIoTRoseetal.usetheworkingdefinition:“theextensionofnetworkconnectivityandcomputingcapabilitytoobjects,devices,sensors,anditemsnotordinarilyconsideredtobecomputers.”(p.17)Alternativenetworkarchitectures

• Device-to-Device: Two or more devices thatdirectly connect and communicate with oneanother(p.18)

• Device-to-Cloud: “IoT device connects directlyto an Internet cloud service like an applicationservice provider to exchange data and controlmessagetraffic.”(p.19)

• Device-to-Gateway: “Application softwareoperatingona local gatewaydeviceacts as anintermediarybetweenthedeviceandthecloudserviceandprovidessecurityorotherfunctionse.g.dataorprotocoltranslation.”(p.20)

• Back-End Data-Sharing: “A communication architecture that enables users to export cloudservice in combination with data and other sources. This supports users desire for grantingaccesstouploadedsensordatatothirdparties.”(p.21)

SomechallengesaheadThereport identifiesanumberofchallengeareasof IoT.These includekeyquestionsthatneedtobeanswered by publics, industry, and governments. Some key questions related to privacy issues arehighlightedbelow:IoTPrivacyQuestions(p.42–43)FairnessinDataCollectionandUse

• Howdoweresolvethemarketplacerelationshipbetweendatasourcesanddatacollectors?• Howmight distinct interests be expressed in away that leads to fair and consistent rules for

bothsourcesandcollectorsconcerningaccess,control,transparency,andprotection?Transparency,Expression,andEnforcementofPrivacyPreferences

• How can privacy policies and practices be made readily available and understandable in thecontextofIoT?

• Whatarealternativestothe“noticeandconsent”model?• What is an effective model for expressing, applying, and enforcing individual privacy

preferences?Wide-rangingPrivacyExpectations

• Privacynormsandexpectationsarecloselyrelatedtothesocialandculturalcontextoftheuser.• Whatwillthatmeanforthedevelopmentofabroadlyapplicableprivacyprotectionmodel?• How can IoT devices and systems be adapted to recognize and honor the range of privacy

expectationsoftheusersanddifferentlaws?



PrivacybyDesign• HowcanweencourageIoTdevicemanufacturersto integrateprivacybydesignprinciples into

theircorevalues?• Howdowe foster the inclusionofconsumerprivacyconsiderations ineveryphaseofproduct

developmentandoperation?Identification

• How shouldweprotect data collectedby IoT that appearsnot tobepersonal at thepoint ofcollection or has been “de-identified” butmay at some point in the future become personaldata?

1.2SemantictechnologiesfortheIoT–anInter-IoTperspectiveMariaGanzha,MarcinPaprzycki,WieslawPawlowski,PawelSzmeja,KatarzynaWasielewska(2016),IEEEFirstInternationalConferenceonInternet-of-ThingsDesignandImplementationInthisarticle,GanzhaandcolleaguespositthatthedefinitionalcomplexityofIoTandapparentconflictsin definition are essential. “Dealing with volume of data produced by the things, their varyingcapabilities, and an exploding number of services, which they offer (or require, to be “useful”), areamongthebiggestconceptualandtechnologicalchallengesofourtime.Butit’snotonlythescaleandthe heterogeneity, which have to be considered. A dynamic and often unknown topology of thenetwork, high possibility of conflicts between things, unknown availability of data-points, as well asvarioussecurityissuesarejustafewexamplesofotherproblemstobetackled.”IoTdeviceswillhavetobe homogeneous and will have to allow discovery of their capabilities – requiring an inchoatedefinitionalstateattheoutset.Theypresent internetontologiesasameanstoachievingdevice inter-operability andhomogeneity through application in “semantic annotation,managing access, resourcediscoveryandknowledgeextraction.”(p.271)InternetOntologiesfromGanzhaetal.(2016,p.271–272)InternetOntologies

Description

CSIRO SensorOntology

Genericontology fordescribing function, physical andmeasurement aspectsofsensors–classesincludesensors,features,operations,results,processes,inputsandoutputs,accuracy,resolution,abstract&physicalproperties,metadatalinks

SWAMOOntology

Collaborative,distributedsetofintelligentagentsforsupervisingandconductingautonomous mission operations – enables automated decision making andresponsetosensorwebenvironment

MMI DeviceOntology

Ontology ofmarine devices that integrateswithmodels of sensor descriptions(component,systemprocess,platform,device,sensorandsampler)

SEEK ExtensibleObservationOntology

Suite of ontologies formodeling and representing scientific observations – canexpress a range of measurement types, includes mechanism for specifyingmeasurementcontext,canspecifytypeofentitybeingmeasured.



1.3TheInternetofThings:MappingtheValueBeyondtheHypeMcKinseyGlobalInstitute(June,2015),WhitepaperTheeconomicimpactofIoTisdiscussedintheMcKinseyreport,whichalsocontainsquantitativeassessmentsofpotentialinseveralkeyareas.DifferentusemodelswiththeIoT(p.3,19):



PotentialValueintheInternetofThings(p.9):



2. IoTandtheUnderlyingTechnology2.1WhattheInternetofThings(IoT)NeedstoBecomeaRealityFreescale/ARM(May2014),WhitePaperThiswhitepaperbyFreescale/ARMpresentsIoTfromthevantagepointofthesemiconductorindustry,whose technology will be at the heart of all IoT. They provide an overview of the technologicalcapabilitiesnecessarytomakevisionsofIoTbecomereality.TechnicalRequirementsforIoTinclude(p.7):

1) Sensinganddatacollectioncapability(sensingnodes)2) Layersoflocalembeddedprocessingcapability(localembeddedprocessingnodes)3) Wiredand/orwirelesscommunicationcapability(connectivitynodes)4) Softwaretoautomatetasksandenablenewclassesofservices5) Remotenetwork/cloud-basedprocessingcapability(remoteembeddedprocessingnodes)6) Fullsecurityacrossthesignalpath

The white paper takes these requirements and converts them to products that will be necessary toestablishIoT(p.12):

2.2TheInternetofThings:TheNextGrowthEnginefortheSemiconductorIndustryRamenChitkara,WernerBallhaus,OlafAcker,Dr.BinSong,AnandSundaramandMariaPopova,(May2015)PricewaterhouseCoopers



IoTwillhaveatremendousfinancialimpactonthesemiconductorindustry.

Chitkaraandcolleaguesforecasttheanticipatedfinancial impactof IoTonthesemiconductor industry(p.22):

“PwC’sforecastfortheglobalsemiconductormarketsuggeststhatbetween2014and2019billingswillincreasebyUS$96billion,representingacompoundannualgrowthrate(CAGR)of5.2%.Dataprocessingwill be the largest single segment with a total of US$162 billion in 2019, followed by thecommunications segmentwith a total of US$127 billion in 2019. The strongest growthwill be in thesmaller segments: industrial (forecasted CAGR of 9.7%) and automotive (forecasted CAGR of 8.2%).”(p.32)RIOTOS:TowardsanOSfromtheInternetofThingsEmmanuel Baccelli, Oliver Hamm, Mesut Günes, Matthias Wählisch, and Thomas Schmidt (2013)INFOCOMDemo/Postersession.IoTdeviceshavetheiruniqueanddiversesetofsoftwarerequirements.BaccellietalintroduceRIOTOS,anopen-sourceOSdesignedfor low-power, low-resourceIoTdevices, incompetitionwiththeexistingplayers such as mBed from ARM,Windows 10 fromMicrosoft, Brillo from Google, etc. In the bookInternetofThingsbasedonSmartObjects,authorsdiscusstheuseofsmartobjectsandmiddlewareto



dealwith theheterogeneityanddecentralizednatureof IoT.Becauseof theexpectation for IoTtobesomewhatautonomous,machinelearningandartificial intelligencehavebeenconsideredpartsof IoT,betheyimplementedattheleafnodesorinthecloud,asdetailedinHoldowskyetal’sprimeronIoT.HoldowskyJ,MonikaM,RaynorME,CotteleerM(2015)InsidetheInternetofThings,DeloitteUniversityPress(p.3)



3. IoTinHealthcare3.1HowCantheInternetofThingsHelptoOvercomeCurrentHealthcareChallenges?Jerome Couturier, Davide Sola, Giovanni Scarso Borioli, Cristina Raiciu (2012), Digiworld EconomicJournal(87)3,p.67-82.“Healthcare systems are facing several challenges starting from an ageing population to a growingdemand formore advanced and better healthcare outcomes. This leads to an increase of healthcarecosts as well as a need for change in healthcare systems in terms of better and more efficientoutcomes.”CouturierandcolleaguespositthatIoTcouldhelpsolvetheseissuesandothersbyenablingmoresystematicmanagementofthehealthcaresystemand“behavioralchangesbystakeholdersinthesystem.” To test this hypothesis they analyzed 71 “innovative health solutions…developed for 10therapeuticareas.”(p.67)FourcasesdemonstratinghowIoTcanaddresshealthcaresystemchallenges:Challenge Description IoTSolutionCardiacArrhythmia(p.71–72)

Deviations of the heart fromthe norm - whichmay lead totoo fast, too slow or irregularheartbeats

(1) Mobile Cardiac Outpatient Telemetry (MCOT) –monitorspatients24/7via small sensor that transmitsactivitytocompany’smonitorycenterandtophysician(2) Sensor attached to patient’s chest that detects,transmits, and records physiological information viawireless connection to central server – reviewed bycardiologisttech

Heartfailure(p.73)

Condition in which the heartcan no longer pump enoughbloodtotherestofthebody

Fluidstatusmonitoringdevice–whenapatientcrossesthefluidthreshold,dietandmedicationareadjustedtoget him/her back on track. Device helps patientscomplywithtreatmentroutine.

Diabetes(p.74–76)

Chronic disease that affectshow the body metabolizesglucose resulting in prolongedhighbloodglucoselevels

Monitoring device that uses blood pressure andglucosemonitor togiveaccurate test results tobettermanage glucose levels. Monitor communicates viaBluetooth to a smart screen (PC or cellular)transmittingdatatoserverwhereitisstored,reviewedandinterpretedbythepatient’sdoctor.

Obesity(p.76–77)

Excessivebodyfatrelativetoaperson’s height and gender. ABMIof30orgreater.

Wireless-enabled wearable fitness tracker with 3Dmotion sensor to accurately track calories, steps,distance,and sleepquality.Automaticallyuploaded tointernet,analyzedbypatientordoctor.



ImpactoftheIoTsolutionsandtheirfulfillmentofthepropositions(p.78):

3.2RegulatingHealthcareRobots:MaximizingOpportunitieswhileMinimizingRisksSimshawetal.(2016)“Robots inhealthcarewill be anevolution in the comingdecades, and there arebasic questions thatneed to be addressed in this nearer future in order to ensure that robots are able to maintainsustainable innovation with the confidence of providers, patients, consumers, and investors. Onlythrough such responsible design, deployment, and use will robots' potential be maximized inhealthcare.”There is amovement inhealthcare toward theuseof robotswith far greaterautonomy.“Suchautonomy includes the supervisorycontrolparadigm, inwhichcertain functionsareautomatedwith a human supervising the system, all the way to fully autonomous robots. Similarly, health careenvironments that are reliant on or dominated by all-purpose "healthcare companions" and robotic"doctors,"utilizingartificialintelligence,willraisefascinatingquestions.”Drivingforcesbehindautomationandroboticsinhealthcare

• Withagingpopulationsworldwidetherewillbeincreaseddemandforhealthcarewhichcanbemet,inpart,throughefficiencyandautomation.

• Risinghealthcarecostscanbeaddressed,inpart,throughthecosteffectiveuseofrobots(e.g.conductingpatientintake)andtheextensionofroboticservicestohomehealthcare(e.g.takingvitals,administeringmedication,providingcomfort).

• Personalizedhealthcaremayincreasethedemandforrobotsastheirservicescanbetailoredtospecificpatientsneeds.

Typesofhealthcarerobots

• Surgicalrobots(whichatpresentaredirectlycontrolledbydoctors)



• “Routine-task” robots (“bring meals andmedications to patients, transfer lab specimens andcarrylinens)

• Personal care robots (beginning as assistants to doctors butwill increasingly perform care onpatientsinmedicalfacilitiesandhomes)

Keylegalandregulatoryissues

• Differenttypesofrobots,performingdifferenttasks,arecurrentlyregulateddifferentlybytheFDA(e.g.asmedicaldevicesormobileapps);nnocomprehensiveregulatoryframeworkexistsfromconnectedandautomatedhealthcarerobots;

• Patientsecurityandprivacyinthedesignanddeploymentofrobotsinhealthcaresettings;• As healthcare robots become more autonomous and connected to other devices they may,

eventually,makemedicaldecisionswithhumanoversight;• The collection, processing, storing and use of patient data by robots and the sharing of data

betweenrobotsandotherdevices.3.3IoTAnalyticsforSmartHealthandCareProf.Dr.Ch.Thuemmler,PresentationtoIoTWeek(2015)Inhis presentation, Thuemmler challenges the vision that the current stakeholderswill be capableofchangingtheirperspectivesbutstillholdsanoptimisticviewofIoTapplicationinthehealthcaresector.Hedoesthisbyofferingaseriesof“myth-busters”thatarticulatethediscrepancybetweenthepromisesofIoTofferedbyEuropeangovernmentsandtheactualexperienceofhealthcareandindustriescreatingIoTtechnologies.

Despite thesechallengeshe foresees that individualswillbetterown theirwellbeing-relateddataandparticipateintheirowncare.Healsolistsregulatorychallengesthatneedtobeovercome,suchasdatagovernance.3.4How5GTechnologyEnablestheHealthInternetofThingsDarrellM.West(July,2016)CenterforTechnologyInnovationatBrookings,WhitepaperWestemphasizestheroleoffuture5GtelecommunicationtechnologiesinenablingIoTinhealthcare.



Keyareasofadvancement:Imaging(p.6)

• Imagesandinformationsharingacrossgeographicareas• Patientsinruralareasgainaccesstodoctorselsewhere• Doctorsgainaccesstoexpertiseinotherlocales• Could address disparity in access to healthcare based on geographical distribution of services

andservicequalityDiagnostics(p.7-9)

• Newapplicationsexpandtheuseofmonitoringwithwearableandingestiblemedicalequipment• Monitoring can replace self-reporting for chronic diseases like Parkinson’s or for monitoring

foodintakeandexercise.• Medicalhealthanddiagnosisthroughvideoforthoseinremotelocationsorthosewithlimited

mobility.• Patientbiomonitoring:e.g.remotemonitoringofvulnerablepatients’vitals• Precisionmedicineenabledbyintegrationofpatientdatastoredoncloud

Dataanalyticsandtreatment(p.9-10)

• Mininghealthdata• CollaborativeCancerCloudTM–integratepatientsinformationfromavarietyoforganizations• Wearabledevisesthatsendoutalertsorremindpatientstotakemedication• Remotesurgery

3.5IndustrialInternetInsightsReportGE-Accenture(2015)The GE Accenture report presents surveys in the healthcare industry revealing some of the barriersaheadintheuseofIoT,especiallyorganizationalchallengesincompanies.“Among the healthcare organizations we surveyed as part of our Industrial Internet research, anoverwhelmingmajorityacknowledgedthecriticalroleofanalyticsindrivingimprovedclinical,financialandoperationaloutcomes.Theseorganizations feel thatanalyticswillhave thepower todramaticallyimprove patient outcomes…However, challenges around system barriers between departments,budgetary constraints and organizational obstacles are impeding implementation of their analyticsinitiatives.”(p.16)“Healthcareorganizations…haveagreaterfocusonhowanalyticscandriverbetterpatientcareratherthan as a means to achieve competitive advantage.” (p. 19) “Healthcare organizations clearlyunderstandthepotentialofanalyticstodrivebetterpatientoutcomesandoperationalefficiencies.”(p.20)



Topanalyticscapabilitiestargetedfordevelopmentbyhealthcareproviders(p.20):



4. LawandIoT4.1CareandFeedingofPrivacyPoliciesandKeepingtheBigDataMonsteratBay:LegalConcernsinHealthcareintheAgeoftheInternetofThingsChristinaScelsi(2014-2015),NovaLawReview(39),p.391-435.“While the use of big data that is generated by the IoT has great potential to produce boundlesstechnologicaladvances,italsopresentssomeveryrealandseriouslegalconcernsforconsumers,aswellas a number of regulated industries… A prime example of the myriad of data privacy issues thatconsumersandbusinesses face[…]canbefound inanexaminationof the issuescurrent facedbythehealthcareindustryintheageofIoT.Whilewearablefitnesstrackers, likeFuelBandandFitBitdevices,seem like innocuous gadgets urging users tomovemore and get in shape, the long term impact ofhavingdata aboutone’s habits andhealth collected areunknown.Howwould thedatabe viewed intheeyesofaperson’sphysician,orinsurancecompanyforthatmatter?Whendeviceismorenecessaryfor life– likeapacemakercapableof remotemonitoringvia the Internet– the implicationsofadatabreach or potential attack by hackers become evenmore dire.When it comes to healthcare relatedapplications, the Food and Drug Administration (FDA) is considering different tiers of regulation toensurethattheseappsareprovidingsafeandaccurateinformationtoconsumers.”(p.394)CrimeConcerns“Data has [always] been a double sided coin with both good and bad aspects; and in today’senvironment of three-dimensional printing and other high techweapons,where the positive aspectshave great potential, the negative present consequences will call for regulatory solutions in comingyears.”ShefollowswithanexampleoftheMumbaiterroristattack.“Whatmarkedashiftfromprevioussuch attackswas that,while these terrorists attachedwith the expectedweapons of hand grenades,explosivesandmachineguns,theyalsocamearmedwithmobilephones,nightvisiongoggles,accesstosatelliteimagery,andmostimportantly,accesstoanoperationscenterinPakistan.”WithaccesstotheinternetterroristsinMumbaimonitoredreal-timemediacoverageoftheirattackandchangedstrategy–includingmurderingahostage-basedonthisinformation.(p.399)IoT,HealthandtheLaw

• IntheUSthereare60,000peoplewithpacemakersthatconnecttotheInternet.“Inthehandsofacriminaltheabilitytoshockapatientremotelycouldbeameansofcommittingmurder.”(p.401)

• Fitbit and FuelBanddatahavealreadybeenadmittedas evidence in apersonal injury case inCalgary in 2014 – the concern is that coupledwith data available through socialmedia thesedevicescouldbecome“blackboxes”forhumans.(p.401)

• FDA has new regulations that “at a minimum, medical devices should require secureauthentication foraccess,useencryptedcommunication,andmakesure thatsecuritypatchesarealwaysadded.”(p.402)

Scelsi runs through an interesting hypothetical of hacking an insulin pump (p. 403). The detailsinterestinglyhighlightthecomplexityandextentofthreatstoindividualprivacyandsafety.DataDiscriminationOneofthebiggestconcernsassociatedwithIoTinhealthcareisdiscriminationbasedonthedatathatiscollected.Will this information be used to determinewhether or not someone is in compliancewith



theirhealthpolicyanddenycoverage in thecaseofnon-complianceor in themakingofemploymentdecisions?(p.405)SecurityandPrivacyRecommendationsThereportstatesthat“giventheveryrealriskofdatabreaches,regulatoryagencies–aswellasfederalandstatelegislatures–arekeepinganeyeonthesituationandarerecommendingsecurityguidelinesfortheIoTasitrelatestohealthcare.”(p.406-408)PolicyprinciplesproposedbyIntelintheirreporttotheSenateSpecialCommitteeonAging(p.408):

1. Standardization: To require data standards for connectivity as well as for interoperabilitybetween smart devices. “IoT in healthcare has the potential to aggregate data from patientrecords,wearablesensors, labs,diet, theenvironment,andsocialnetworking inrealtime,butonlyifthedatacanbeanalyzed.Thistakesstandardizedformats.”

2. Regulate Smartly: Avoid de-innovation in developing security standards and the need forcollaborationbetweenCongress,regulators,andindustrytodevelopregulatoryframeworks.

3. Rethinking Reimbursement: The adoptions of virtual care for patients by phsyicians andhealthcare systems has been delayed by a failure to reimburse providers when the providevirtualcarethatissuperior(toinpersoncare)forpatients.

4. Link Patient Collected Data with Patient Records: 78% of physicians and 66% of hospitalsadoptedelectronicmedicalrecordsaftertheHITECHActbutdatafromsensorsarenotincluded.

5. ExtendingPrivacyandSecurityStandards:StandardsshouldberequiredforIoTapplicationsanddevices that are part of the IoT – a “universally accepted health IT security standard or[principles]thatcanbeenforceable”andcriteriafororganizationstobedeemedHIPAASecurityRuleCompliant.”

RelevantLawsandRegulationsApplicabletoIoTFederal Privacy Act of 1974: “governs the collection, maintenance, use, and dissemination ofinformationaboutindividualsthatisstoredintherecordssystemsoffederalagencies.”Thisincludesthenodisclosurewithoutconsentrule-“noagencyshalldiscloseanyrecordwhichiscontainedinasystemofrecordsbyanymeansofcommunicationtoanyperson,ortoanotheragency,exceptpursuanttoawrittenrequestby,orwith thepriorwrittenconsentof, the individual towhomtherecordpertains.”(p.409-410)Children’s Online Privacy Protection Act (COPPA): Protects the personally identifiable information ofchildren under the age of thirteen and sets out regulations that commercial website operatorsmustabideby if thewebsite iscollectingsuch information. [SHINECuratornote:COPPArecentlycame intoplayinanIoTlawsuitrelatedtoMattel’sHelloBarbiewhichrecordsthe(presumablyunderage)owner’svoiceandtransmitstheinformationtoMattel’sserverwhereacustomizedresponseiscraftedandthenspokentoyourchildthroughthedoll.](p.410-413)California Online Privacy Protection Act (CalOPPA): Requires all online services or websites to“conspicuously post privacy policies to informusers about (a) the categories of personally identifyinginformation being collected; and (b) with which third parties the information will be shared.”Amendments require “retailwebsiteoperators includeadeletebuttonon such sites andapplicationsthatwouldallowminorswhoareregisteredusersonthesitetohavetheabilitytodeletetheircontentthathasbeenpostedonthesite,ortheabilitytorequestthatitbedeleted.”(p.413-414)



HealthInformationPrivacyAct:Protectsindividuallyidentifiablehealthinformationbutappliesonlytocertainentitiesinclude:healthplans,healthcareclearinghousesandhealthcareproviderwhotransmitsanyhealthinformationinelectronicform.ThelattercategoryislikelytobechangedinresponsetoIoTdevices.(p.421)Health Information Technology (HITECH) Act: “Provided monetary incentives to hospitals andhealthcare providers to convert to electronic medical records systems” but also “made significantchanges toboth the enforcement and sanctions as they relate to thehealthcareprivacy and securityrequirementsenactedaspartofHIPAA.”This includestheextensionofprivacyobligationstobusinessassociatesandentitiesnotcoveredbyHIPAA(e.g.Lawyers,ITpersonnel,...).(p.422)AffordableCareAct: Amongmanyother things, establishedHealthcare.gov as theonline location fortheHealth InsuranceMarketplace.Thearticledetailssomeof theprivacy issuesthathavearisenwiththemarketplace.(p.423-425)GeneticInformationNondiscriminationActof2008:Geneticinformationispersonalhealthinformationprotected under HIPAA and cannot be used by health insurance companies for underwriting or byemployersfordiscriminationbasedontheinformation.(p.425)4.2ALitigator'sGuidetotheInternetofThingsAntigonePeyton(2016),RichmondJournalofLawandTechnology(22)3,p.1-21.Peytonpresentsadifferentlegalperspective:IoTasatoolforalitigator,alsohighlightingthepotentialfutureroleofIoTdevelopersinlegalcases.“Fromalitigator’sperspective,therearebenefitsandrisksassociated with IoT evidence. These connected objects, combined with big data analytics, canmakecasessimultaneouslyclearerandmorecomplicated.TheIoTmovementalsochallengeslitigatorstorolluptheirsleevesandthinkcreativelyabouthowtheseconnectedobjectscantellastory.”(p.2)ThearticlecontinueswithexamplesofIoTcasesincluding:

• Mattel’sHelloBarbie:Connecteddollthatrecordsyourchildthroughanembeddedmicrophoneand uses a wi-fi connection to send the conversation to Mattel’s partner company ToyTalk,whichrecordsandstoresallconversationsandsendsbackapre-programedresponse.(p.6-7)

• DetectiveMode:Spyware installedonrentalorrent-to-own laptopsthatturnsonthebuilt-in-cameraifcustomersfailtomakepaymentsontime.Italsogathers“dataaboutwhoeverisusingthe computer, and transmits it to the software manufacturer every two minutes, who thensendsthedatatotherent-to-ownstore.”(p.7-8)

Wearabledevicesandthelaw

• “Apersonalinjurylawyermightbeinterestedinthedatacollectedfromtheirclient’swearablefitnessdevice.Forinstance,thedataobtainedfromaFitbitdevicehasbeenusedaevidenceofan individual’s diminished physical activity resulting from awork-related injury in a Canadianpersonalinjurycase.”Inacaseofallegedrape,“theFitbitdatacontradictedthestatementsoftheallegedvictimbyshowingthatatthetimeofthecrime,shewasawakeandwalkingaround,eventhoughsheclaimedshewasattackedwhileasleep.”(p.9)

• Thereisalegalprecedentfortheuseofdatagatheredfromwearablesincourt:“CourtsalreadyusedatafromGPSservicesandbikingappsincasesinvolvingbikeaccidents.Policeroutinelyusesurveillance technology like Automatic License Plate Readers mounted on police cars, or



[elsewhere]…Privatecompaniesalsocollectlicenseplatephotosandgeo-taggedimagesandsellthatdatatolawenforcement, insurers,andfinancial institutions.Theyconsiderthisanalogoustotakingphotographsofpublicanddisseminatingtheinformation,anactivityprotectedbythefirstamendment.”(p.11)

• Reliabilityofthedatagatheredandtheanalysisremainsanissue.(p.12)ConnectedCarsandtheLaw“IoT implicates a wide variety of technologies involvedwith running andmonitoring connected cars,including connected control systems, Event Data Recorders, and other vehicle telematics. Vehiclecontrol software may use proximity sensors to identify collision risks and automatically engage thebrake,surveyblindspotsandreportobjects,andparkavehiclewithoutdriverassistance…These [andautonomous cars]will be connected to the internet andwill transmit all kindsofdata relating to thevehicle and its passengers’ activities.” “At least one rental car agency is already putting cameras innavigationaldevicesinstalledinitsfleetofcars,andtheusercannotdisablethecamera.”(p.14-15)Thearticlecontainsfurtherinformationon:

• DiscoveryofIoTinformation(p.15)• IoTObjectasWitness(p.17)• LitigatinginanIoTWorld(p.20)



5. TelecommunicationsforIoT5.1EmbracingtheInternetofEverythingtoCaptureyourShareof$14.4TrillionJosephBradley,JoelBarbier,DougHandler(2013),CiscoBradley et al present Cisco’s point of view: Cisco as amajor networking player stands to gain in theexplosion that IoT represents in data traffic and attempts to quantify the economic implications fordifferent industries. TheauthorsquantifytheValueatStakewithIoT(this includesincreasedrevenueanddecreasedcost)at$14.4Trillion.(p.1)Thisisbrokendowninto5drivers:

Theyalsobreakdownthevalueof IoTby industryandindicatethecurrentstateof industriesandthepotentialofferedbyIoTin2022:SmartFactories$1.95trillionintotalValueatStake(p.7)

ConnectedMarketingandAdvertising$1.95trillionoftotalValueatStake(p.8)



SmartGrid$757billionoftotalValueatStake(p.9)

Connectedgamingandentertainment$635billionoftotalValueatStake(p.10)

SmartBuildings$349billionoftotalValueatStake(p.11)

Connectedcommercialgroundvehicles$347billionoftotalValueatStake(p.12)

ConnectedHealthcare andPatientMonitoring$106billionoftotalValueatStake(p.13)

Connectedprivatecollegeeducation$78billionoftotalValueatStake(p.14)



5.2UnderstandingtheInternetofThings(IoT)GSMA,WhitepaperThispaperemphasizes thecritical rolewireless technologieswillplay in the IoTandtherequirementsand challenges, in particular the distinction between the current human-centric protocols and therequired machine-to-machine (M2M) ones. “M2M solutions – a subset of the Internet of Things –alreadyusewirelessnetworks toconnectdevices toeachotherand the Internet,withminimaldirecthuman intervention, to deliver services that meet the needs of a wide range of industries. The IoTrepresentsanevolutionofM2Mthroughthecoordinationofmultiplevendors’machines,devicesandappliancesconnectedtotheinternetthroughmultiplenetworks.”(p.1)Consumerimpactoftheconnectedlife(p.3):

Socio-EconomicImpactoftheConnectedLifein2017(p.4):



Understanding the Internet of Things: GMSA offers 5 features of IoT of critical import fortelecommunications(p.9-11):

1. The internet of things can enable the next wave of life-enhancing services across severalfundamentalsectorsoftheeconomy(Healthcare,SmartCities)

2. Meeting theneedsof customersmay requireglobaldistributionmodelsandconsistentglobalservices

3. IoTpresentsanopportunityfornewcommercialmodelstosupportmassglobaldeployments

4. Themajorityofrevenueisderivedfromtheprovisionofvalueaddedservicesandoperatorsare

buildingnewcapabilitiestoaddressthesenewserviceareas5. Deviceandapplicationbehaviorwillplacenewandvaryingdemandsonmobilenetworks.



5.3OnNetworkingofInternetofThings:ExplorationsandChallengesHuadongMa,LiangLiu,AnfuZhou,DongZhao(2016),IEEEInternetofThingsJournal(3)4,p441-452.Ma et al is a survey of the challenges in telecommunications in making IoT possible, in particularheterogeneityofthedevices,themodalityoftheconnection(i.e.,IPvs.non-IP).ComparisonbetweenheterogeneousnetworkelementsinIoT(p.442):



6. IndustrialIoTAlthoughthepublic ismostacutelyawareofthepartof IoTthatwillhavedirectcontactwiththem,alargepartofIoTwillbehiddenfromview,yetnolessinfluentialontheimpactonoursociety:industrialIoT(IIoT).6.1InternetofThingsforIndustrialAutomation–ChallengesandTechnicalSolutionsHongyu Pei Breivold and Kristian Sandström, (2015) IEEE International Conference on Data IntensiveSystemsBreivold and Sandströmprovide an overview of the goals of IIoT, relevantmetrics such as reliability,functional safety, scalability, etc., as well as the challenges such as heterogeneity, compatibility,longevity,etc.IoTChallengesinIndustrialAutomation(p.533-534)

• Dataandservicesecurity• Trust,dataintegrityandinformationprivacy• Scalability• Interoperability

AutomationDomain-SpecificConstraints(p.534-535)

• Timinganddeterminism• Reliabilityandavailability• Safetyandcriticality• Interoperability

IndustrialIoTChallenges(p.535-537)Mixedcriticality • Virtualization

• Partitionmodelw/mechanismthatdecideseachpartition’speriodandexecutiontimeautomatically

Latency • “fogcomputing”or“edgecomputing”• Computeroffloading• SmartGateway+SmartNetwork

Scalability w/ respect to data updatecyclesFaulttolerance • Redundancy: duplicating servers, controllers, I/O and

networks• Designlocalfallbacksolutions• FaultpredictionusingIoT

Scalablecollaborationinrealtime • Zeroconfigurationnetworking• AMQP,MQTTorDDSforconnectingheterogeneousdevices• Serviceorchestrationandchoreography

Functionalsafety • SeparatesafetysystemsfromIoTsystems• Partial integrationwhere information from safety systemsare isolated and don’t depend on IoT systems but stillprovideinformation

Industry-specificsecuritychallenges Legacylong-livedindustrialsystems



6.2Industry4.0:TheFutureofProductivityandGrowthinManufacturingIndustriesTheBostonConsultingGroup(April2015).TheBCG reportsdiscuss theeconomicaspectsof IIoTas an integralpartof “Industry4.0”alongwithothertransformationaltechnologiessuchasassistivemanufacturing,simulationandaugmentedreality,includinghowitwillaffecttheworkforceandhowitwillhelptransformmanygoodsintodigitalservices.“Industry4.0willtransformthedesign,manufacture,operation,andserviceofproductsandproductionsystems. Connectivity and interaction among parts, machines, and humans will make productionsystemsasmuchas30percentfasterand25percentmoreefficientandelevatemasscustomizationtonew levels.” “Manufacturing will be transformed from single automated cells to fully integratedautomatedfacilitiesthatcommunicatewithoneanotherandboostflexibility,speed,productivity,andquality. In Germany’s advanced manufacturing landscape, for example, Industry 4.0 can driveproductivitygainsof5to8percenttotalmanufacturingcostsovertenyears,totaling90billionto150billionEuros.”“TheimpactofIndustry4.0willbesignificant.OurresearchshowsthatinGermanyaloneitwillcontributeand1percentperyeartoGDPovertenyears,createasmanyas390,000jobsand250billionEurotomanufacturinginvestment(or1to1.5percentofmanufacturers’revenues).AlthoughthefullshifttowardIndustry4.0mighttake20yearstoreachfruition,inthenext5to10yearskeyadvanceswillbeestablishedandwinnersandloserswillemerge.”(p.2)



NinePillarsofTechnologicalAdvancementThesearetheadvancesthatBCGseesasformingthebasisofIndustry4.0,itincludes(p.4):TechnologicalAdvancement Example1. BigDataandAnalytics Semiconductor manufacturer Infineon Technologies had decreased

product failuresbycorrelatingsingle-chipdatacaptured inthetestingphaseattheendoftheproductionprocesswithprocessdatacollectedinthewaferstatusphaseearlierintheprocess.

2. AutonomousRobots Kuka, a European manufacturer of robotic equipment, offersautonomous robots that interact with each other. These robots areinterconnected so that they work together and automatically adjusttheiractionstofitthenextunfinishedproductinline.

3. Simulation Siemens and a German machine-tool vendor developed a virtualmachinethatcansimulatethemachiningofpartsusingdatafromthephysicalmachine.This lowersthesetuptimefortheactualmachiningprocessby80%.

4. Horizontal and VerticalSystemIntegration

Dassault Systèmes and BoostAeroSpace launched a collaborationplatform for the European aerospace and defense industry. Theplatform, AirDesign, serves as a common workspace for design andmanufacturingcollaboration.

5. The Industrial InternetofThings

Bosch Rexroth, a drive-and-control-system vendor, outfitted aproduction facility for valves with a semi-automated, decentralizedproduction process. Products are identified by radio frequencyidentification codes, and workstations “know” which manufacturingstepsmustbeperformed for eachproduct and canadapt toperformthespecificoperation.

6. Cybersecurity Industry 4.0 will need to protect critical industrial systems andmanufacturing lines from cybersecurity threats. Secure reliablecommunications and sophisticated identity and access managementmachinesandusersareessential.

7. TheCloud Machine data and functionality will increasingly be deployed to thecloud,enablingmoredata-drivenservicesforproductionsystems.Evensystemsthatmonitorandcontrolprocessesmaybecomecloudbased.

8. AdditiveManufacturing Aerospacecompaniesusethistoapplynewdesignsthatreduceaircraftweight,loweringtheirexpensesforrawmaterialsliketitanium

9. AugmentedReality Workersmayreceiverepairinstructionsonhowtoreplaceaparticularpart as they are looking at the actual system needing repair. Virtualtrainingmayalsoriseinprominence.

6.3ForgingLinksintoLoops:TheInternetofThings’PotentialtoRecastSupplyChainManagementJoeMariani,EvanQuasney,andMichaelE.Raynor,(2015),DeloitteReview(17),p118-129.Mariani et al present the potential of IoT to redefine supply chain management by providing anunprecedented levelof timely feedbackanddetaileddata.Theyarticulate thispotential in termsofavalue loop that “consists of stages, each enabled by specific technologies. An act is monitored by asensor that creates information; that information passes through a network so that it can becommunicated;andstandards–betheytechnical,legal,regulatory,orsocial–allowthatinformationbe



aggregatedacrosstimeandspace.Anenterpriseusesaugmentedintelligence,oranalyticalsupport,toanalyze the information, and the loop is completed via augmented behavior technologies that eitherenable automated autonomous action or shape human decisions in a manner leading to improvedaction.InformationValueLoop(p.120)

ThreewaysinwhichtheIoTtransformsthesupplychain(p.122)



NewpathstosupplychainmanagementthroughIoT:Efficiency:The IoT’sability tomakevisiblepreviouslyunseen informationaboutasupplychainallowsforgreaterefficiencythanprocesscontrolsalone.IoTsolutionswiththisgoalaretypicallyfound“withinthewalls,”makingaparticularplantorfacilityrunmoreefficiently.(p.122)Differentiation:Byexpandingwithin-the-walls IoTapplications to include suppliersanddistributors inan end-to-end supply chain, companies can transformpush-drivenorder systems to pull-drivenones.Theseapplicationscanhavethesameefficiencygainsaswithin-the-wallsapplications,buttheycanalsoimprovecustomerexperienceprovidingforgreaterdifferentiation.(p.123-124)Innovation:PervasiveIoTapplicationsthatintegratecustomersandtheend-to-endsupplychainintoasingle product ecosystem open the possibility of new, innovative business models. Among the mostinterestingofthesenewbusinessmodelsarethosethattransformthesupplychainfromacostburdentoonethatcangeneraterevenueitself.(p.125)6.4PrecisionAgricultureTechnologyforCropFarmingQinZhang(Ed),CRCPress,2016The collection edited by Zhang called “Precision AgricultureTechnologyforCropFarming”givesadetailedanalysisofhowIoTis already changing agriculture and how it can improve waterefficiencyamongothermetrics.AnE-versionof thebookcanbemadeavailableuponrequest.



7. Cybersecurity7.1MobileCybersecurityintheInternetofThings:EmpoweringM2MCommunicationCTIA(2014)EssentialtothesuccessofIoTisthedifficultgoalofsecurity.TheCTIAreportisaqualitativeoverviewofthe challenges in securing IoT wireless communications against a growing and diversifying group ofthreatswhilemeetingstringentpowerandresourcerequirements.ExamplesofM2Mconnectionsandcorrespondingprotectivecountermeasures(p.14):



7.2SecurityintheInternetofThings:AReviewHuiSou,JiafuWan,CaifengZou,JianqiLiu,(2012)InternationalConferenceonComputerScienceandElectronicsEngineeringSouetalreviewexistingsecurityarchitectures,theirapplicationtotheIoTandtheirlimitations.(p.648)

SecurityRequirements(p.649)



8. SmartCity8.1TowardsaSmartCityBasedonCloudofThings,aSurveyontheSmartCityVisionandParadigmsRiccardo Petrolo, Valeria Loscri and Nathalie Mitton (2015), Transactions on EmergingTelecommunicationsTechnologiesDOI:10.1002/ettPetroloetalpresentanoverviewofhowIoTcanbenefitcityresidents.Theyemphasizethatinsteadofbeingonehomogeneoustightlyconnectednet,smartcityIoTwillbealooselyboundfederation,makingtheinterfacesamongthosecriticalforsuccess.“Althoughthereisnotaformalanduniversallyaccepteddefinitionofa‘SmartCity’yet,…,authorstrytodelineatetheconcept,definingasmartcityasacitythatfunctionsinasustainableandintelligentway,byintegratingallitsinfrastructureandservicesintoacohesivewholeandbyusingintelligentdevicesformonitoringandcontrol, toensuresustainabilityandefficiency.”This includesan IoTstructuredividedintofivelayers:(p.5)

• DeviceLayer:“dealswiththeidentificationandcollectionofobjectsspecificinformationbythesensordevice;”

• NetworkLayer:“usedtosenddatacollectedbythedevicelayertotheinformationprocessingsystem;”

• Middleware Layer: “performs information processing and ubiquitous computation and takesautomaticdecisionbasedontheresults;”

• Application Layer: “provides globalmanagement of the application based on the informationprocessedthroughMiddleware:

• BusinessLayer:“responsibleforthemanagementofoverallIoTsystem.”ThisideaoftheconglomerationofmanyIoTsisexaminedindetailinthebookCollaborativeInternetofThings.Thisbookcanbemadeavailableuponrequest.



8.2BuildingSmartCitiesCarolL.Stimmel,CRCPress,2015

StimmelinherbookBuildingSmartCitiesemphasizestheroleofdesignthinkinginwiselydeployingIoTtechnologytoreachsociety’sgoals.HerbookcoversmanyaspectsofIoTfromtheperspectiveoftheirimpact of society including energy, water, city revitalization, transportation, democracy etc. Sheunderlinesthevulnerabilitiesthatconnectedcitieswillhavebut inachaptercalled“HackingtheCity”also underlines that the same hacker spirit can be used as a positive disruptive force in thetransformation of our society. Jeremy Rifkin in his book The Zero Marginal Cost Society discusses asimilarvisionwheretheIoTwillbeinstrumentalincombattingeconomicinequality.8.3TheSpectrumofControl:ASocialTheoryoftheSmartCityJathanSadowskiandFrankPasquale (2015),UniversityofMarlyandFrancisKingCareySchoolof Law,LegalStudiesResearchPaper(20)7.SadowskiandPasqualeofferacriticalperspectiveonsmartcities thatcastsa shadowover theentireIoT.While smart cities and IoT are normally referenced in terms of new or improved technologies -applications,devices,andconnections-thisarticledepictstheminthemucholdertermsofpowerandcontrol. Take, for instance, their commentary on the way industry frames privacy and surveillance:“Their[so-calledtechnocrats]normativetoolsofevaluation,focusingonconsumerandcitizen“consent”tosurveillance,aremanipulatableenoughtoembraceeventhemostdisturbingtechnologiesofcontrol– such as drone-driven crowd control directed at protesters, or automobile loan technology thatdisables cars mere minutes after a payment is late – as expressions of democratic will and marketrationality.”(p.2)Theyofferatheoreticalresponse“thatlaysoutthecharacteristicsandconsequencesof a dominant socio-political logic that courses throughout and ties together many of the variouspracticesandideologiesrelatedto‘smartcities.’”(p.2)Threetypesofsmartcities:



• Existing (retrofitted and renovated) smart cities: “the smart city is assembled piecemeal,integrated awkwardly into existing configurations of urban governance and the builtenvironment”(cf.…)andtheresultof“increasinglyentrepreneurialformofurbangovernancethatseekstomakethecityintoacenterof…competitiveeconomicgrowth.”(p.3)

• Smart shocked cities: “a city undergoes a quick, large-scale integration of ‘smart’ ideals,technologies,andpolicies.”“PerhapsthebestexampleistheIntelligentOperationsCenterbuiltinin2010byIBMforthecityofRiodeJaneiro…WiththisNasa-esquecontrolroom,thecityofRio is turned into a system for optimization and securitization…thus amplifying the alreadyexistingpracticesofmilitaristicurbancontrol.”(p.3)

• Idealisticmodelsofthesmartcity:“builtfromscratchprojectsthatarebeingconstructedwherenothing exist before.” “This type also reveals striking historical similarities that exist betweenthe smart city ideology and the ideology of twentieth century high modernist architecture”ExamplesincludeSongdo,SouthKoreaandMasdarCity,UAE.(p.3)

Theauthorsgoontopresenttwocasestudiesexemplifyingaspectrumofcontrol,drawing“connectionsbetweentechnologiesthatwerebeforethoughtofasdiscreteandindependent.”(p.9)Theyarguethat“any significant technology of the smart city becomes a tool to be repurposed for later, often-unforeseeablegoals.”(p.9)Withthisperspective inmindtheygoontoproposetheprincipleof“TheRighttotheCity.”(p.10)“ThisrightoriginatedfromHenriLefebvreasameansforpeopletotakebacktheurbansocialspacebychallengingtheabusesofcapitalthroughare-imaginationofthedutiesandprerogativesofcitizenship(Purcell,2002).”(p.14)



9.TransportationandIoT9.1AutomatedVehicleResearchUSDepartmentofTransportation,IntelligentTransportationSystemsJointProgramOffice,availableat:http://www.its.dot.gov/automated_vehicle/avr_plan.htm“TheUSDOT reportpresents thegovernment’sperspective inhow IoT (connected transportation)willtransformtheU.S.Itiscirca2014andinIoTtime-scalethatiseternity,thereforeitdoesnotforeseetherapid realization of some of the technologies such as assisted driving. Yet it still manages to give abalancedviewoftheimplicationsforthesociety.”Vision“TheUSDOTautomationprogramwillpositionindustryandpublicagenciesforthewide-scaledeploymentofpartiallyautomatedvehiclesystemsthatimprovesafetyandmobilityandreduceenvironmentalimpactsbytheendofthedecade.”Role:TheUSDOT’sroleinvehicleautomationisto:

• “Facilitatedevelopmentanddeploymentofautomatedtransportationsystemsthatenhancesafety,mobility,andsustainability

• Identifybenefitopportunitiesinautomatedvehicletechnology• Investinresearchareasthatfurtherindustryinvestmentsandsupportrealizationofbenefit

opportunities• EstablishFederalMotorVehicleSafetyStandardsandinfrastructureguidance.”

ProgramGoals:ThegoalsoftheDepartment’sautomationprogramareto:

• “Developestimatesofthepotentialbenefitsand[risks]ofautomatedvehicles• Evaluateandpromoteenablingtechnologies• Developprototypeapplications• Identifyneededstandardsandappropriatemethodsfordevelopment• Identifytechnical,policy,institutional,andregulatorybarrierstodeploymentandpossible

solutions• Generatedesignguidelinesforautomatedvehicles• Collaboratewithabroadrangeofpublicandprivatestakeholders.”

ProgramOrganization“Three capability-based tracks form the program core, with cross-cutting activities such as policyresearchandinternationalresearchexchange.Thetracksfocusonvariouslevelsofautomation.”



HumanFactorsEvaluationofLevel2andLevel3AutomatedDrivingConcepts“There are critical research questions regarding driver transitions between automated and manualdriving modes, such as how drivers perform over time when using these systems. This initial policystudy, fundedby theNationalHighwayTrafficSafetyAdministrationandthe ITS JointProgramOffice,addresseshumanfactorsresearchquestionsfocusedondriverstransitioningintoandoutofautomateddriving states enabled by Level 2 and Level 3 automated driving concepts. The results supportdevelopment of initial human factors driver-vehicle interface principles. Project partners include theVirginia Tech Transportation Institute, Battelle, Bishop Consulting, General Motors, Google, and theSouthwestResearchInstitute.”Additionalcurrentresearchincludes:

• “IntroductionofCooperativeVehicle-HighwaySystemstoImproveSpeedHarmonization• SimulationforResearchonAutomatedLongitudinalVehicleControl• HighPerformanceVehicleStreamsSimulation• PartialAutomationforTruckPlatooning:PortAuthorityTrans-HudsonCorporation/Caltrans• PartialAutomationforTruckPlatooning:AuburnUniversity• SaxtonTransportationOperationsLaboratoryTask3:ProcureandInstrumentResearchVehicles• DevelopmentofaPlatformTechnologyforAutomatedVehicleResearch• VehicleAutomationProgramManagementandPlanning• HumanFactorsEvaluationofLevel2andLevel3AutomatedDrivingConcepts• CooperativeAdaptiveCruiseControl–InvestigationofKeyHumanFactorsIssues• Development of Functional Descriptions and Test Methods for Emerging Automated Vehicle

Applications• TransportationSystemBenefitStudyofHighlyAutomatedVehicles• LaneChanging/MergeFoundationalResearch”

ThePotentialofAutomation“Automated vehicles have the potential to bring about transformative safety, mobility, energy, andenvironmental benefits to our nation’s surface transportation system. These benefits could includecrash avoidance, reducedenergy consumption and vehicle emissions, reduced travel times, improvedtraveltimereliabilityandmulti-modalconnectivity,andimprovedtransportationsystemefficiencyandaccessibility, particularly for persons with disabilities and the growing aging population. The pace ofresearch, development, and commercialization of automation technologies has increased rapidly in



recentyears.Whiletechnologiesavailabletodayrequireahumandrivertomonitortheroadwayandbepreparedtotakecontrol,researchintothedevelopmentoffullyself-drivingvehiclesisunderway.”9.2PreparingaNationforAutonomousVehicles:Opportunities,BarriersandPolicyRecommendationsDanielFagnant,KaraKockelman(2013),EnoCenterforTransportation,Report“In2004,DARPA’sGrandChallengewaslaunchedwiththegoalofdemonstratingAVtechnicalfeasibilitybynavigatinga150-mileroute.Whilethebestteamcompletedjustoversevenmiles,oneyearlaterfivediverless cars successfully navigated the route. In 2007, six teams finished the newUrbanChallenge,with AVs required to obey traffic rules, deal with blocked routes, and maneuver around fixed andmovingobstacles,..”“AsofApril2013,Google’sself-drivingcarshavedrivenover435,000miles…”(p.2)PotentialBenefits:

• Safety: AVs have the potential tosignificantly reduce crashes caused byhumanandenvironmentalfactors(p.3)

• CongestionandTrafficOperations:AVscansenseandanticipateleadvehicles’brakingandaccelerationdecisions…expectedtouseexistinglanesandintersectionsmoreefficientlythroughshorterheadways,coordinatedplatoonsandmoreefficientroutechoices.(p.4)

• Travel-Behavior Impacts: AVs mayprovidemobilityforthosetooyoungtodrive, the elderly and disabled,generating new roadway capacitydemands. Parking patterns couldchange, ride-sharing programs couldexpand. More vehicle miles travelled.(p.6)

• Freight Transportation: Truckingindustryapplications–reducedneedfor truckdrivers (negative impacton jobs in thissector),increasedfueleconomy.(p.7)

PolicyRecommendations(p.15):

1. Expandfederalfundingforautonomousvehicleresearch2. Developfederalguidelinesforautonomousvehiclelicensing3. Determineappropriatestandardsforliability,securityanddataprivacy



AnticipatingEconomicBenefits(p.8):



10.BigDataAnalyticsandIoTBigDataAnalyticsisalreadyabusinesssuccess.Theanalysisofdatafromcurrentsourcesofinformationhasgeneratedvaluableinsights,productsandservices.Theinternetofthingsisinlargepartmotivatedby the hunger for more big data. There are a few candidate architectures with differentimplementationsoftheinterfacesamongtheIoTwherethedataisgenerated,theCloudwherethedatais stored and Analytics (probably also in the Cloud) where the data is processed. There are severalrequirements for data analytics to realize the full potential of the data from IoT including real timeanalyticsandextremescalability(e.g.,asdiscussedinGooglePlatformdocumentation).

Infact,acloseanalysisoftherequirementsrevealsthatafeasiblesolutionmustinvolvethecoordinateddesignofallpartsofthesystem.Becauseoflimitationsondatabandwidth,someofthedataprocessingwill have to be at the IoT edge nodes,which is now called processing in the fog (as opposed to thecloud).Similarly,dataanalyticsinthecloudmayhelptheseleafnodesconfigureorplacethemselvesforoptimaloperation.



11.IoTStandards11.1AworldwithmoreIoTbodiesthanstandardsTerryHughes,PublishedMarch18,2016,availableat:http://internetofthingsagenda.techtarget.com/blog/IoT-Agenda/A-world-with-more-IoT-standards-bodies-than-IoT-standardsGiven the very large and fragmented use scenarios of IoT and its large potential footprints on thesociety,businessandtechnology,itisnotsurprisingthatstandardsarekeytosuccessandproliferation.Theyalsoformabattleground.TerryHughesofAppCarouselpublishedasnapshotoftheIoTstandardsbodies,whicharemorenumerousthanthestandards:

Internet Standards Bodies (Ted Hughes, IoT Agenda, March 2016) IPSOAlliance “Definingidentityandprivacyforthenextgenerationofsmartobjects.”IPSOis

anopen, informalandthought-leadingassociationof like-mindedorganizationsthat promote the value of using the Internet Protocol for the networking ofsmartobjects.

AllSeenAlliance “A cross-industry consortium dedicated toenabling the interoperability ofbillions of devices, services and apps that comprise the Internet of Things.”Qualcomm kicked this off as AllJoyn and then handed the source code to theLinuxFoundation,fromwheretheAllSeenAlliancewasborn.

The IndustrialInternetConsortium

“The openmembership, international not-for-profit consortium that is settingthe architectural framework and direction for the Industrial Internet.” It wasfounded by AT&T, Cisco, GE, IBM and Intel in March 2014, with amission tocoordinate vast ecosystem initiatives to connect and integrate objects withpeople, processes and data using common architectures, interoperability andopenstandards

oneM2M “TheglobalstandardsinitiativeforMachinetoMachineCommunicationsandtheInternet of Things.” Itspurpose and goal is to develop technical specificationswhich address the need for a commonM2MService Layer that can be readilyembeddedwithin various hardware and software, and relied upon to connectthemyriadofdevicesinthefieldwithM2Mapplicationserversworldwide.

FiWare “An independent open community whose members are committed tobuildingan open sustainable ecosystem around public, royalty-free andimplementation-driven software platform standards that will ease thedevelopmentofnewsmartapplicationsinmultiplesectors.”

OpenDaylightIoDM OpenDaylight (ODL) is a modular opensoftware defined networking(SDN)platform for networks large and small, and ODL has an initiative calledIoTDM (where DM stands for data management) which aims to deliver opensourceIoTmiddlewaresolutionsbasedononeM2MoverODL.

OpenFog “Apublic-privateecosystemformedtoacceleratetheadoptionoffogcomputingin order to solve the bandwidth, latency and communications challengesassociated with IoT.”Itswork is centered around creating a framework forefficient and reliable networks combinedwith identifiable, secure and privacy-friendly information flows between clouds, endpoints and services based onopenstandardtechnologies.

Open ConnectivityFoundation

“The Open Connectivity Foundation (OCF) is creating a specification andsponsoringanopensourceprojecttounlockthemassiveopportunityintheIoTmarket, accelerate industry innovation, and help developers and companies



create solutions thatmap to a singleopen specification.”OCFwill help ensuresecureinteroperabilityforconsumers,businessesandindustries.

ThreadGroup “It’s hard to get devices to talk to one another. And once they do, theconnection is often spotty and power hungry. Thread changes all that. It’s ameshnetworkdesigned to securely and reliably connect hundredsof productsaroundthehome—withoutblowingthroughbatterylife.”Threadhasacoupleofhundredmembersintheconnectedhomespace.

Hypercat “Aconsortium and standard to drivesecure and interoperable IoT for industryand cities.”The Hypercat specification allows Internet of Things clients todiscoverinformationaboutIoTassetsovertheWeb.WithHypercat,developerscan write applications that will work across many servers, breaking down thewallsbetweenverticalsilos.

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