Internet of Things: Cases and Studies: 305 (International Series in Operations Research & Management Science, 305) PDF
Preview Internet of Things: Cases and Studies: 305 (International Series in Operations Research & Management Science, 305)
International Series in Operations Research & Management Science Fausto Pedro García Márquez Benjamin Lev Editors Internet of Things Cases and Studies International Series in Operations Research & Management Science Volume 305 SeriesEditor CamilleC.Price DepartmentofComputerScience,StephenF.AustinStateUniversity, Nacogdoches,TX,USA AssociateEditor JoeZhu FoisieBusinessSchool,WorcesterPolytechnicInstitute,Worcester,MA,USA FoundingEditor FrederickS.Hillier StanfordUniversity,Stanford,CA,USA Moreinformationaboutthisseriesathttp://www.springer.com/series/6161 Fausto Pedro García Márquez (cid:129) Benjamin Lev Editors Internet of Things Cases and Studies Editors FaustoPedroGarcíaMárquez BenjaminLev IngeniumResearchGroup,ETSI LeBowCollegeofBusiness IndustrialesdeCiudadReal DrexelUniversity,DecisionSciencesand UniversityofCastilla-LaMancha MIS CiudadReal,Spain Philadelphia,PA,USA ISSN0884-8289 ISSN2214-7934 (electronic) InternationalSeriesinOperationsResearch&ManagementScience ISBN978-3-030-70477-3 ISBN978-3-030-70478-0 (eBook) https://doi.org/10.1007/978-3-030-70478-0 ©SpringerNatureSwitzerlandAG2021 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped. 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ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Preface Internet of Things (IoT) is a relatively new discipline, an emerging research field whichutilizestoolsandtechniquestakenfromoperationsresearchandmanagement science(OR/MS).IoTisanetworkofdevicesconnectedandcapableoftransferring information over the network. Devices on the network can include machine, equipment, human, animal, parking lot, or anything. It can transfer text, signals, media, and software. This book introduces the topic and its origin. It starts with basicconceptsandpresentcases,applications,theory,andpotentialbenefitsasseen fromOR/MSpointofview,forexample,advancedanalyticsandmachinelearning. Examples are from smart industry, city, transportation, home, and smart devices. The future applications, trends, and potential benefits of this new discipline are discussed.ThebookprovidesaninterfaceamongOR/MS,engineering/technology, organization and administration, and IoT. It is yet to be seen how OR/MS will influencethedevelopment,direction,andshapeofIoT.ThefutureofIoTisbright and strong. It will stay with us for decades, will be part of our daily life, will be almosteverywhere,andwillbeextremelyuseful. CiudadReal,Spain FaustoPedroGarcíaMárquez Philadelphia,PA,USA BenjaminLev v Introduction Internet of Things (IoT) is a relatively new discipline, an emerging research field thatrequirestheuseandapplicationofmanagementscience.Thisbookintroduces thetopicanditsorigin.Itstartswithbasicconceptsandoverviewandthenpresents cases,applications,theories,andpotentials.Thechaptersinthisbookcoverawide array of topics as space permits. Examples are smart industry, city, transportation, home,andsmartdevices.Italsodiscussesfutureapplications,trends,andpotential ofthisnewdiscipline. IoT is a network of devices connected and capable of transferring information over the network. The network can be a group of machines, equipment, human, animal,parking lot,andsoon.Itcould transfertext,signals,media, and software. To build and manage IoT, new disciplines in management science have emerged such as advanced analytics and machine learning. Specifically, this book provides an interface between the main disciplines of engineering/technology and the organizational,administrative,andplanningcapabilitiesofmanagingIoT. This book provides relevant theoretical frameworks and the latest empirical research findings in IoT. It has been written for professionals to show their understanding of the strategic role of IoT at various levels of the information and knowledge organization, that is, IoT at the global economy level, at networks and organizations,atteamsandworkgroupsofinformationsystems,and,finally,atthe levelofindividualsasplayersinthenetworkedenvironments. This book is intended for professionals in the field of engineering, information science,mathematics,economists,andresearcherswhowishtodevelopnewskills in IoT, or who employ the IoT discipline as part of their work. The authors who contributedtothisbookdescribetheiroriginalworkintheareaorprovidematerial forcasesandstudiessuccessfullyapplyingtheIoTdisciplineinreal-lifecasesand theoreticalapproaches. Blockchain is a new technology resulting from a continuous research on consensus mechanisms to ensure the integrity of a distributed shared replica. It represents a data structure built on a hash function and distributed among the various participants according to previously agreed consensus rules. Chapter 1 aims to carry out a comprehensive survey of the consensus mechanism that forms vii viii Introduction the heart of blockchain technology and its suitability for the IoT. It begins by explaining blockchain technology from a historical and technical point of view before approaching the different philosophical approaches within the consensus mechanism,theirdisadvantage,andtheirsuitabilityfortheIoTsector. IoT implementation depends, to a large extent, on human and technological resourcesavailabilityandculturalaspectsandprioritiesoforganizations.According to their state, the different factors can be enablers or inhibitors of IoT imple- mentation. Since IoT implementation is a case of digitalization, main elements of digitalization and most typical enablers and inhibitors are presented in Chap. 2. Based on scientific and professional literature, the specific enablers and inhibitors ofIoTarepresented.Theyinvolvetechnologicalenablers(abilitytoprovidepower to the devices, connectivity, communication capability between elements, and data handling capacity), strategic enablers (IoT adoption as a strategic element, formulation of a global architecture of IoT), organizational enablers (digital talent and skills and digital culture), organizational barriers (need for standardization, securityrisks,privacyrestrictions,cost,andregulatoryissues),andculturalbarriers (perceptionofcomplexityandlackoftrust) The use of the IoT in the healthcare sector has shown to be a promising solution to reduce the workload of doctors and provide better service to patients. However,shareddatamaybesubjecttotheftormisuseduetothesecurityissueson various devices. Moreover, transparency among stakeholders, confidentiality, and micropayments need to be addressed. The objective of Chap. 3 is to use federated learning over blockchain data generated from IoT devices with the usage of zero- knowledgeprooforconfidentialtransactions.Theproposedarchitectureensuresthe user a level of privacy set by them while making sure of sharing relevant insights withtheconcernedparties. IoT has been undergoing a rapid development and has obtained increasing visibility. Many scientific research achievements have been published. Chapter 4 aims to provide a bibliometric review for highly cited papers in the field of IoT usingtheEssentialScienceIndicators,awidelyuseddatabasetoevaluatescientific outputs. Through the retrieval process, 388 papers were identified as highly cited papers. Based on these 388 papers, it analyzes their characteristics from four perspectives: annual and discipline distributions; productive players in terms of journals, countries, institutes, and authors; top-15 most-cited papers; and author keyword analysis. Interesting results are given after the analyses. Through author keyword analysis, the chapter also provides research trends of the IoT for future study. Inmacroeconomics,“information”isacopiableproductwithnoadditionalcost. DespiteservicesonIoTconsidertheinformation,theirscalabilitiesaresmallerthan other information products. Chapter 5 models IoT services as a composition of information, devices, and electricity, and points out that the existence of devices andelectricitypreventsreducingmarginalcostsoftheservices.Itismentionedthat the informatization of the computer industry in the past was the replacement of accounting subjects. The chapter describes that design to scale IoT services is to developincentiveslettingothersshoulderthecostsofdevicesandelectricity Introduction ix In Chap. 6, COVID-19 data are analyzed using the biclustering approach to gain insights such as which group of countries have similar epidemic trajectory patterns over the subset of COVID-19 pandemic outburst days (called bicluster). Countries within these groups (biclusters) are all in the same phase but with a slightlydifferenttrajectory.AnapproachbasedontheGreedyTwo-WayK-Means biclustering algorithm is proposed to analyze COVID-19 epidemiological data, which identifies subgroups of countries that show a similar epidemic trajectory patternsoveraspecificperiod.Itisthefirsttimethatthebiclusteringapproachhas beenappliedtoanalyzeCOVID-19data.Infact,theseCOVID-19epidemiological dataarenotarealcountbecausenotalldatacanbetrackedproperly,andthereare otherpracticaldifficultiesincollectingthedata.Evenindevelopedcountries,ithas hugepracticalproblems.Therefore,iftheIoT-basedCOVID-19monitoringsystem can be used todetect the originof theCOVID-19outbreak, then therealsituation can be identified in each country. Results confirm that the proposed approach can alertandhelpthegovernmentauthoritiesandhealthcareprofessionalstoknowwhat toanticipateandwhichmeasurestoimplementtodeceleratethespreadofCOVID- 19. Chapter 7 aims to review IoT applications in the healthcare domain that are representative and active in practice and research. The chapter introduces the existing IoT products in the healthcare market; reviews the studies on developing, using, and improving IoT healthcare applications; and presents and discusses the recent trend and focus of IoT healthcare applications. First, the chapter describes a general picture of IoT healthcare applications. Then, the chapter studies IoT healthcareapplicationsinfourscenarios:(1)acutediseasecare–threeapplications areintroducedtoshowhowIoTbenefitsacutecare:vitalsignmonitoring,acutecare telemedicine,andIoT-baseddetectionandcontrolofinfectiousdiseases;(2)chronic disease care – the chapter focuses on remote health monitoring used for patients with chronic diseases, especially patients with Alzheimer’s disease, diabetes, and heart failure; (3) self-health management – the chapter pays attention to the most common representative device for self-health management, smartwatches, and analyzesthetwomainfunctionsofsmartwatchesonself-healthmanagement,sleep monitoring, and exercise monitoring; (4) hospital operations management – the chapteralsodiscussesIoTapplicationforhospitaloperationmanagementincluding assetandautomatedhospitalworkflowmanagement,sinceitcanfinallyimprovethe efficiencyandeffectofhealthcaredeliveryandthenbenefitpatientsanddoctors. Chapter 8 presents a use-case based on the development of an interactive, integrated, and adaptable visiting system for complex buildings and surrounding grounds (smart places). The system features a mobile application that allows the usertoaccessinformationfromseveralsmartplacesinasingleapplication,andan indoor location and tracking system that infers the user location during the smart placevisit.Thesystemcalculatesthetrackingandlocationoftheuserbasedonthe positioningofneighboringBLEdevicessensedviaBluetoothontheuser’smobile device. The approximate location, behavior, and interests, and hence the visiting profileofeachuser,canbeinferredbythesignalsfrommultiplebeaconsinstalledon thebuildingatspecificpre-definedpositions.Thesystemalsointegratesabackend x Introduction contentmanagementsystemtoallowthecreationandmanagementofsmartplaces informationandsupportsinformationimportfromBIMtools. Chapter9analyzescontemporarymachinelearningtechniquesforthecomputa- tion of market and asset liquidity risk for multiple-assets portfolios. Furthermore, this chapter focuses on the theoretical aspects of asset liquidity risk and presents two critically robust machine learning processes to measuring the market liq- uidity risk for trading securities as well as for asset management objectives. To that end, this chapter extends research literature related to the computation of market and asset liquidity risks by providing generalized theoretical modeling algorithms that can assess both market and liquidity risks and integrate both risks into multiple-assets portfolios settings. The robust modeling algorithms can have practical applications for multiple-securities portfolios, and can have many uses and application in financial markets, particularly in light of the 2007–2009 global financial meltdown in issues related to machine learning for the policymaking processandmachinelearningtechniquesfortheIoTdataanalytics.Inaddition,risk assessment algorithms can aid in advancing risk management practices and have importantapplicationsforfinancialtechnology(FinTech),artificialintelligence,and machinelearninginbigdataenvironments. The current IoT development involves ambient intelligence, which ensures that IoT applications provide services that are sensitive, adaptive, autonomous, and personalized to the needs of the users. A key issue of this adaptivity is context modeling and reasoning. Multiple proposals in the literature have tackled this problem according to various techniques and perspectives. Chapter 10 provides a reviewofcontextmodelingapproaches,withafocusonservicesofferedinambient assisted living (AAL) systems for persons in need of care. The chapter presents thecharacteristics ofcontextual information,services offered byAAL systems,as well as context and reasoning models that have been used to implement them. A discussionhighlightsthetrendsemergingfromthescientificliteraturetoselectthe mostappropriatemodeltoimplementAALsystemsaccordingtothecollecteddata andtheservicesprovided. IoT is a platform governed by information and communication technologies that facilitates affordable data communication among heterogeneous devices in large scale. However, computation rich applications running on IoT need specific considerations as user response plays key role in critical situations particularly in transportation,healthcareandsmartcities.Inthisview,Chap.11explainsindetails characteristics ofvarious softwarecomponents thatareinuseinIoTover existing communicationnetworks,andpresentsvariousproblemssolvingtechniquesforIoT applications in intelligent transport systems. Further, the role of algorithms and computational structures for development of efficient IoT application is illustrated indetailwiththreerealtimecasestudiesintransportationdomain. Chapter 12 considers the “Mobile Kukan Toukei™” (mobile spatial statistics) to examine characteristics of the and spatial movement patterns in specific tourist destinations in Nagoya City (Japan). This chapter also attempts to estimate visitor volumeandflowusingmovementdataacquiredbyWi-Fitrackingsensorsinstalled widely in tourism destinations. A Wi-Fi tracking sensor is a device that acquires
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