04829nam 2201129z- 450 991063779340332120231214132841.03-0365-5963-9(CKB)5470000001631602(oapen)https://directory.doabooks.org/handle/20.500.12854/94568(EXLCZ)99547000000163160220202212d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierEnergy Consumption in a Smart CityBaselMDPI - Multidisciplinary Digital Publishing Institute20221 electronic resource (270 p.)3-0365-5964-7 A Smart City is the perfect environment to study and exploit the interactions between actors because its architecture already integrates vaious elements to collect data and connect to its citizens. Furthermore, the proliferation of web platforms (e.g., social media and web fora) and the increased affordability of sensors and IoT devices (e.g., smart meters) make data related to a large and diverse set of users accessible, as their activities in the digital world reflect their real-life actions. These new technologies can be of great use for the stakeholders as, on the one hand, they provide them with semantically rich inputs and frequent updates at a relatively cheap cost and, on the other, form a direct channel of communication with the citizens. To fully exploit these new data sources, we need both novel computational methods (e.g., AI, data mining algorithms, knowledge representation) that are suitable for analyzing and understanding the dynamics behind energy consumption and also a deeper understanding of how these methods can be integrated into the existing design and decision processes (e.g., human-in-the-loop processes).Therefore, this Special Issue welcomed original multidisciplinary research works about AI, data science methods, and their integration in existing design/decision-making processes in the domain of energy consumption in Smart Cities.Research & information: generalbicsscPhysicsbicsscbuilding energy flexibilityHOMER softwarepeak clippingload shiftingenergy savingbuilding performance assessmentindoor environment qualityoccupants' satisfactionpost-occupancy evaluationGreen Building Indextropical climatebuilding performance simulationCO2 emissionoccupant's comfortwindow allocationclimate changeenergy consumptionbuilding energy loadthermal loadfuture weatheroperative temperaturecooling loaddaily energy needsolar gainsnZEBhistorical buildingsTRNSYSbuildings retrofittingbuildings officeeconomic feasibilityRenewable Energy Systems (RESs)Zero Energy District (ZED)Digital Twin (DT)Building Information Modelling (BIM)Geographic Information System (GIS)Revit software'sasymmetric duty cycle controlbifilar coilpulse duty cycle controlinduction heatingmetal meltingphase shift controlpulse density modulationseries resonant invertervariable frequency controlbuilding operation and maintenanceextended realityvirtual realityaugmented realitymixed realityimmersive technologiesdigital twinsmetaversepositive energy districtdistrict energy infrastructuredecarbonisation of neighbourhoodsGISenergy transitionsmart city policycarbon emission intensitydigital transformationgreen innovationdifference-in-differencesResearch & information: generalPhysicsNastasi Benedettoedt1302975Mauri AndreaedtNastasi BenedettoothMauri AndreaothBOOK9910637793403321Energy Consumption in a Smart City3035414UNINA