Contextualised Service Delivery in Internet of Things Smart Parking for Smart Ci<es Ali Yavari *, Prem Prakash Jayaraman †, Dimitrios Georgakopoulos † * RMIT University, Melbourne, Australia † Swinburne University of Technology, Melbourne, Australia [email protected]
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Contextualised Service Delivery in Internet of Things, Smart Parking for Smart Cities
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Sensors and other Internet-connected devices that are all connected to theinternetandtheyinteractintelligentlytomakethedevelopmentanddeliveryofnewservicesandproducts
ContextorcontextualinformaEonisanyinformaEonaboutanyenEtythatcanbeused to effecEvely reduce the amountof reasoning required (viafiltering,aggregaEon,andinference)fordecisionmakingwithinthescopeofspecificapplicaEons.
ContextualisaEon
• ContextualisaEon excludes irrelevant data fromconsideraEonandhas thepotenEal to reducedatafromseveralaspectsincludingvolume,velocity,andvarietyinIoTapplicaEons
• Scalable and real-Eme contextualisaEonof IoT data has thepotenEal tosignificantly improve data processing for large scale IoT applicaEons inSmartCiEes
• Weproposedanapproach to contextualise andquery Internet scale IoTdata and we exemplify the approach via a smart parking spacerecommenderapplicaEonforSmartCiEes.
• Theexperimental scenario in thispaper illustrates that contextualisaEonof IoTdatareducesqueryEmesfor IoTservices(suchasasmartparkingspacerecommender)bymorethan3EmesincomparisonwithasituaEonwherethequeryiscontextualisaEonagnosEc.