Decision Analytics for Sustainable Development in Smart Society 5.0: Issues, Challenges and Opportunities PDF
Preview Decision Analytics for Sustainable Development in Smart Society 5.0: Issues, Challenges and Opportunities
Asset Analytics Performance and Safety Management Series Editors: Ajit Kumar Verma · P. K. Kapur · Uday Kumar Vikram Bali Vishal Bhatnagar Joan Lu Kakoli Banerjee Editors Decision Analytics for Sustainable Development in Smart Society 5.0 Issues, Challenges and Opportunities Asset Analytics Performance and Safety Management SeriesEditors AjitKumarVerma,WesternNorwayUniversityofAppliedSciences,Haugesund, RogalandFylke,Norway P.K.Kapur,CentreforInterdisciplinaryResearch,AmityUniversity,Noida,India UdayKumar,DivisionofOperationandMaintenanceEngineering,Luleå UniversityofTechnology,Luleå,Sweden The main aim of this book series is to provide a floor for researchers, industries, assetmanagers,governmentpolicymakersandinfrastructureoperatorstocooperate and collaborate among themselves to improve the performance and safety of the assets with maximum return on assets and improved utilization for the benefit of societyandtheenvironment. Assets can be defined as any resource that will create value to the business. Assets include physical (railway, road, buildings, industrial etc.), human, and intangibleassets(software,dataetc.).Thescopeofthebookserieswillbebutnot limitedto: (cid:129) Optimization,modellingandanalysisofassets (cid:129) ApplicationofRAMStothesystemofsystems (cid:129) Interdisciplinaryandmultidisciplinaryresearchtodealwithsustainabilityissues (cid:129) Applicationofadvancedanalyticsforimprovementofsystems (cid:129) Applicationofcomputationalintelligence,ITandsoftwaresystemsfordecisions (cid:129) Interdisciplinaryapproachtoperformancemanagement (cid:129) Integratedapproachtosystemefficiencyandeffectiveness (cid:129) Lifecyclemanagementoftheassets (cid:129) Integratedrisk,hazard,vulnerabilityanalysisandassurancemanagement (cid:129) Adaptabilityofthesystemstotheusageandenvironment (cid:129) Integrationofdata-information-knowledgefordecisionsupport (cid:129) Productionrateenhancementwithbestpractices (cid:129) Optimizationofrenewableandnon-renewableenergyresources ReviewProcess Theproposalforeachvolumefollowsmulti-prongedreviewprocess.Thefirstlevel ofreview(singleblind)isconductedbytheserieseditorswhomayormaynotdecide toenlistthehelpofeditorialboardmembersforasecondlevelofreview.Proposals mayalsoundergoathirdlevelofpeerreview(doubleblind)ifrecommendedbythe SeriesEditors. The series follows Ethics Statement found in the Springer standard guide- lines here. https://www.springer.com/us/authors-editors/journal-author/journal-aut hor-helpdesk/before-you-start/before-you-start/1330#c14214 Moreinformationaboutthisseriesathttps://link.springer.com/bookseries/15776 · · · Vikram Bali Vishal Bhatnagar Joan Lu Kakoli Banerjee Editors Decision Analytics for Sustainable Development in Smart Society 5.0 Issues, Challenges and Opportunities Editors VikramBali VishalBhatnagar IMSEngineeringCollege DepartmentofComputerScience Ghaziabad,India andEngineering NSUTEastCampus(AmbedkarInstitute JoanLu ofAdvancedCommunicationTechnologies DepartmentofComputerScience andResearch) SchoolofComputingandEngineering Delhi,India CentreforPlanning AutonomyandRepresentation KakoliBanerjee ofKnowledge DepartmentofComputerScience UniversityofHuddersfield andEngineering Huddersfield,UK JSSAcademyofTechnicalEducation Noida,India ISSN 2522-5162 ISSN 2522-5170 (electronic) AssetAnalytics ISBN 978-981-19-1688-5 ISBN 978-981-19-1689-2 (eBook) https://doi.org/10.1007/978-981-19-1689-2 ©TheEditor(s)(ifapplicable)andTheAuthor(s),underexclusivelicensetoSpringerNature SingaporePteLtd.2022 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,theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor theeditorsgiveawarranty,expressedorimplied,withrespecttothematerialcontainedhereinorforany errorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregardtojurisdictional claimsinpublishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSingaporePteLtd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore Preface The world is encountering a vast technological shift from the traditional method- ologytoIoT-basedsensor-enabledhigh-technologysolutionswhichareeasy,simple, andaccurateinprecisionforprovidingtheoutput.TheinclusionoftheIoTmakes the usage easier and demands simultaneously usage of security aspect which may preservetheprivacyoftheusers.Theinclusionoftheblockchaintechnologywhich ishash-basedfunctionimplicationhelpsinprovidingauniqueidentificationtothe ownerwhichhelpshimgetanownershiprightwhichisamatterofconcernintoday’s scenario. The usage of intelligent analytics in form of decision analytics helps in making an accurate and correct decision with usage of advanced deep learning, nature-inspired,andgeneticalgorithms. Society5.0isahuman-centredsocietythatintegrateseconomicadvancessuchas increaseddemandforresources,longerlifeexpectancyandincreasedinternational competitiveness, combining cyberspace and physical space with addressing social challengesthroughamechanismsuchasGHGpollutionreduction,costmitigation associatedwithageingsociety,andthepromotionofsustainableindustry. Thisbookaimsatmultidisciplinaryresearchforsustainabledevelopmentinsmart societyusingdecisionanalytics.Thegoalistoapplydecisionanalyticsprinciplesto determinehigh-qualitydecisionelementstoimprovedeliveringvaluesusingmultiple statistical approaches. Decision analytics is the methodical quantitative and visual approach to address data science principle for sustainable development of smart societies.Thedigitizationbringstransformationaccelerationofecosystembyadap- tationofinnovation,valuecreation,andstrategicmarketdecisionstowardscreation ofsustainablesocieties. Usingdecisionanalytics,thisbooktargetsmultidisciplinaryanalysisforsustain- able growth in smart society. The aim is to apply decision analytics concepts to define high-quality decision elements to increase value distribution using various statistical approaches. Decision analytics is the methodical quantitative and visual methodology for discussing smart societies’ theory of data science for sustainable growth.Digitizationbringsaccelerationofecosystemchangebyadaptingcreativity, valuegeneration,andstrategicbusinesschoicesforsustainablecommunities. v vi Preface Smart infrastructure’s key aim is to achieve optimum resource utilization and boostefficiency.However,therearenumerouschallengesfacingadoptionofasmart infrastructureconcept,particularlyindevelopingcountriessuchaslocationandlack ofhumanskills,financing,andwell-developedbusinessmodels.SmartHealthcareis agroundbreakingidea,whichinevitablyaffectsmultiplesenses—Culture:encour- aginghealthcarefacilitiescanclearlyhelptobuildahealthysocietyinwhichpeople are more concentrated on proper diet and physical activity. Government: imple- menting smart healthcare and patients can benefit from effective therapies at the lowestcost. Smart manufacturing problems include security issues in smart manufacturing, device convergence, interoperability, safety in human–robot cooperation, multilin- gualism,andinvestmentreturninemergingtechnologies. Smartcitiesconsistofdynamic,networkedassembliesofemergingtechnology, ICTnetworks,andIoTsensorstomanagenumerouscity-wideservicesandstructures andmaximizeresourceuse.Becausesmartcities’IoTdevicesneedinterconnection acrossvarioustypesofnetworks,theyrevealthevastamountofsecurityrisksand there are more possible entry points for network-wide attackers. Smart city IoT devicesconsistofthousandsormillionsofinterconnectedIoTdevicesthatcapture andtransmitdata.Asaresult,malevolentintruderswillexploitthesmartcitystructure tobuildanddistributeself-propagatingmalwarethatcanpropagatethroughseveral linked networks. Attackers can quickly manipulate private information, including users’ financial healthcare and bank passwords. They are also able to conduct differentformsofcryptographyattackswiththeintentionofdestroying:(i)secrecy toretrieveinformationandtracksystemoperation,suchasillicitdatacollectionby eavesdropping or monitoring message traffic; (ii) honesty to alter information and adjust system environment, such as unauthorized access to sensitive information. Smartcitiesrequirearangeofmodules,includinguniversalsensorsystems,hetero- geneousnetworks,vastlibraries,andefficientdatacentrestocapture,move,store, andsmartlyprocessreal-timeinformation.Smartcitieswilldelivernewapplications andprogramstoimproveresidents’day-to-daydecision-making,energyuse,transit, housing, and education. Smart city application is responsible for providing people with a liveable, sustainable, climate-friendly, and engaging atmosphere. Smart energyseekstomanageenergyandresourceuseeffectivelyandexpandstheuseof sustainableenergysourcesbasedonanintegratedandresilientsupplystructureand insight-drivenandpioneeringstrategicplanningapproaches.ICTplaysanimportant role in the growth and activity of smart building, where real-time reaction to the ever-increasingdatastreamisfocusedonanalyticsanddatamanagement.Inother words,thesmartbuilding’ssensors,displaysandcontrolscancaptureandinterpretthe datageneratedinreal-timemodetokeepitundercontrol.Oneofsmartbuilding’skey applicationsistocontrolenergyappliancesbyautomaticallyrespondingtointernal policyandexternalsignalstominimizeenergyusageandimproveenergyreliability. Ineverydaypractices,smartpeopletypicallyimplementinnovativeandgreentech- nologies,developinnovativeprogramsandgoods,explorenewwaysofexchanging knowledge,andengageactivelyindecision-making.Oneofthemajorcities’greatest problems is developing an effective, smart traffic management scheme. Moreover, Preface vii trafficcongestiontriggersnumerousproblemssuchaswastedtime,risingemissions and safety worries, and impacting economic growth and residents’ quality of life. Smarttrafficdefinitionisasuccessfulwaytotacklethisbasicproblembytakingaswift decisionbasedonsensors,mobiledevices,licenseplatereaders,andCCTVcameras. Smart culture will transform healthcare landscape. It will communicate and exchangeknowledgebetweenusersofmedicaldataandusesartificialintelligence to promote freedom. It further encourages the use of self-driving taxis and public transit buses in versatility. Sensors and Artificial Intelligence are used in smart citytomanagehighways,bridges,tunnels,anddams.Inthis,itfacilitatescashless transactionsandusesblockchaintransmissiontechnologies. DistributedDenial-of-Service(DDoS)attacksaroseasoneofthemainsecurity threatsforpublicwebservers,wherecloudcomputingvendorsareresponsiblefor delivering customer services. DDOS attacks also impact various facets of smart cities. Enabled devices and smart objects typically communicate in heterogeneous settings due to the variety of vendors and organizations developing these devices underdiversespecifications,protocols,andtechnicalneeds.Asaresult,proposing anappropriateapproachthatcansatisfyallsmartcitydevices’protectionstandards, homogeneity,andinteroperabilitycriteriaisverydifficult.Thisisbecauseend-to-end connectivitysuffersfromlink,whichalsoinvolvesgatewaysorproxies. This book covers sustainable development in smart society’s 5.0 using data analytics.Thedataanalyticsistheapproachofintegratingdiversifiedheterogeneous dataforpredictiveanalysistoaccreditinnovation,decision-making,businessanal- ysis, and strategic decision-making. The data science brings together the research inthefieldofdataanalytics,onlineinformationanalytics,andbigdataanalyticsto synthesize issues, challenges, and opportunities across smart society 5.0. Accord- ingly,thebookoffersaninterestingandinsightfulreadforresearchersintheareas of decision analytics, cognitive analytics, big data analytics, visual analytics, text analytics,spatialanalytics,riskanalytics,graphanalytics,predictiveanalytics,and analytics-enabledapplications. Chapter 1 discusses about the standards of the healthcare industry affecting the economic performance and quality of life of a country. The new technological advancements and the services ensure patient’s and practitioner’s satisfaction. The remote monitoring, stress analysing, cancer detection, and proactive diagnose have been made possible with the evolution of new technologies. This chapter highlights various technological aspects in the healthcare industry and discusses abouttherelatedworkpresentedbydifferentresearchers.Theaim,applications,and challenges faced by the implementation of technologies like robotics and artificial intelligence, augmented reality, blockchain technologies, Internet of Things, and three-dimensional printing have been highlighted. The chapter presents a quick glance at the various intelligent healthcare systems developed based on presented technologies along with significance and challenges of data analytics in the healthcareindustry. Chapter2discussesaboutthefruitflieswhicharethecommonpestsfoundinfruits andvegetables.Theyinvadeintothefruitcausingseveredamagetofarmers.Thefruits invadedbyfruitfliesarerejectedintheexportmarket.Theperformanceofdeepnets viii Preface isveryhighbutthenegativesideofthataretheproblemsassociatedwithtrainingthe data.AssociatedwithDeepnetsisthecomplexityofthenetworkandthevanishing gradient problem. These are overcome using Transfer Learning. Here, pretrained networksareused.Thesetakelessertimesincetheyarealreadypretrainedandthus the time taken also reduces. This also has the advantage of delivering increased accurate results when compared with the traditional neural networks. It has been proventhatDeepNetworksgiveveryefficientandaccurateresultswhenclassifying images.Inthisproject,weproposetotrainthegherkinsdatasetusingtheResNets toidentifyfruitfly-infectedgherkins.WehaveusedTransferLearningapproachto traintheclassifier.WehavealsobuiltaFlaskwebframework-basedwebapplication tohelpusersuploadgherkins imagesandgetbackpredictions.Inthischapter,we discussamethodwhichcouldhelpgherkinindustriesandfarmersgainhigherprofits intheirrespectivebusinessesforlong-termsustainabledevelopment. Chapter 3 discusses about the countries that are budging towards environment- friendlycongestion;EVsareprocuringsupplementaryreputationbeyondtheworld. Unlikeorthodoxvehiclesthatcouldbereplenishedwithoutcompletefuellingsetup at anticipated locations, some of the positive features of electric vehicles are that theycanberefuelledatseveralplaceslikehomes,offices,shoppingmalls,parking areas, etc. However, appropriate and suitable charging arrangement is required to buildattheselocations.Awidespreadanddefinitelynearbychargingnetworkwillbe utmostimportantforhugeadoptionofelectricvehicles.Thedevelopmentofastrong charging structure network is broadly known as a vital necessity for a huge-scale evolutiontoelectromobility.Thisarrangementwillnotonlygiveadditionalcharging choices for drivers but would also encourage alertness and range self-confidence among approaching electric vehicle holders. As to acclimate towards progress of growingextentalongwithcomplexdesignofElectricVehicle(EV)FastCharging Station (FCS), also tendency of elegant city, this chapter elucidates an application that is based on the acceptance of cell phone Internet as well as mobile station to comprehendintellectualbookingstructureofelectricvehiclefastchargingstation. Withinthisapplication,thestructurerecognizesuser’svehicledetails,showsnearby stations, helps to book slot as per his/her convenience, provides routing guidance, andstartsthechargingprocess. Chapter4discussesaboutdocumentsthatcontainatremendousquantityofimpor- tanthumaninformation.Theuseofautomatictextclassificationisnecessitatedby the fast rise in the quantity of machine-readable documents for public or private access. In a standard text categorization system, preprocessing is one of the most importantelements.Thisarticlewilllookattheinfluenceofpreprocessingontext classification from a variety of perspectives, including classification accuracy, text domain,textlanguage,anddimensionreduction.Textcategorizationisakeydiffi- culty for knowledge-based technologies since it touches on all of artificial intelli- gence’solddemons:theknowledgeengineeringbottleneck,scalabilityissues,simple transferacrossvariousapplications,andcost-effectivesystemdesign.Byspecifying a document, information retrieval (IR) systems have typically avoided all of these difficulties.Messageclassificationisatextcategorizationproblemthathaspiqued machinelearning’sinterest.Thecategorizationofbrieftextmessagesisoneelement Preface ix ofmessageclassificationthatposesaspecialproblem.Thetechniqueofcategorizing documentsintospecifiedgroupsbasedontheircontentisknownastextclassifica- tion.Itistheprocessofautomaticallycategorizingnaturallanguagedocumentsinto preset groups. Text categorization is a prerequisite of both text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which change text in some way, such as creating new documents. Existing super- visedlearningmethodsfortextclassificationrequirealargenumberofdocuments tolearncorrectly. Chapter 5 discusses about the Data Owners who can store their documents on multipledistributedserversindistributedsystems.Itallowstheuseofdatabysitting anywhere on any computer in and from multiple servers. The efficient hunt for distributed documents offering data protection on ownership documents is also a verydemandingmission.Onepotentialalternativeisthatofdataprotectionindexing (PPI) for the current method. Documents are transmitted via many private servers collectivelymanagedbythecloud/publicserverinthisframework.Userswantingto providesuchdocumentsaskforpubliccloud,whichthenreturnsalistofapplicants whichisaprivateserverlisttotheirusers.Afteralistiscollected,userscanaccess documentsonaparticularprivateserver,butdocumentsarestoredonaprivateserver inplaintextform,whichviolatestheirprivacy.Butthesystemproposedimproves thesecurityandefficiencyofthiscurrentsystem. Chapter6discussesthattrafficisincreasingontheroads,andtheaccidentcases arealsoincreasing.Forcontrollingthis,thecamerasareinstalledatvarioustraffic signals or various road intersections in the smart cities. The image captured from thesecameraswillhelptodetecttheruleviolators.Thishasbeendonebyusingan AutomaticNumberPlateRecognition(ANPR)systemwhichisanautomatedsystem andwillbeabletodetectthevarioustypesoftrafficruleviolations.Thenumberplate hasbeendetectedafteridentifyingthevehicle.Fromthenumberplate,thevehicle owner’sinformationhasbeencollectedandthee-challanhasbeengenerated.This generatede-challanwillthenbesenttotheregisteredemailIDfortheinformation andthefinetowardsthetrafficruleviolation. Chapter7discussesabouttheagriculturefield,thepresenceofplantdiseaseand organic deficiency causes major harm and loss to farmers. The conventional way ofdetectingplantpathogensisthroughvisualchecking.Visualcheckingismostly done after major damage to the crop, so treatments will be of limited or no use. To prevent the plant from severe damage and to achieve sustainable development in the farming sector, farmers must detect an infection before it is visible. This is achievedbyprematurediseasediagnosis.Byconsideringthisproblemasachallenge, theproposedsystemprovidesasolutionbyusingtheconceptofInternetofThings to achieve sustainability in the smart farming domain. The proposed system aims at the development of an automated tool to identify whether the plant is normal or diseased.The main goal of theresearch work isthedesign and development of anInternetofThings(IoT)-basedhandheldtooltodetectpigeonpeadiseases.The proposedsystemattemptstodesignanddevelopanautomatedtoolthatsensesthe presence of disease in the plants using various sensors like temperature, humidity, andcolour.Identificationofplantdiseaseisdonethroughsensorreadings.
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