State of the Art State of the Art Citisim Smart City 3D Simulation and Monitoring Platform ITEA3 – Project Citisim Citisim Consortium Page 1 of 152 State of the Art Document Properties Authors Citisim Partners Date 2018-08-29 Visiblity Public Status Final Citisim Consortium Page 2 of 152 State of the Art History of Changes Release Date Author, Organization Changes 0.0 26/12/2016 Emine Ferraro, ARGEDOR SotA - Initial Document 0.1 21/01/2017 Emine Ferraro, ARGEDOR SotA - GIS, 3D Modelling 0.2 01/02/2017 George Suciu, BEIA SotA - Smart Cities– an overview 0.3 02/02/2017 Ignacio Brodin SotA - Data Visualization PRODEVELOP Frameworks for IoT and for 2D and 3D modelling 0.4 10/02/2017 George Suciu, BEIA SotA - State of the art in IoT 0.5 21/02/2017 George Suciu, BEIA SotA - Relevant European research projects 0.6 26/02/2017 George Suciu, BEIA SotA - State of the art in GIS Technologies 0.7 13/03/2017 Carmen Rusu, Luigi Mistodie, SotA - 3D City Modelling Marius Ivanov, ALTFACTOR 0.8 03/04/2017 Emine Ferraro, ARGEDOR SotA - Review and acronyms 0.9 10/04/2017 Jorge Luján, ABALIA SotA - Review, Relevant European research projects 0.10 18/04/2017 Amelia del Rey, SotA - Review as WP2 Leader PRODEVELOP 0.11 25/04/2017 Jesús Martínez, ANSWARE SotA - Data sources and Augmented reality 0.12 27/04/2017 Carmen Rusu, Marius Ivanov, SotA - Reviewed contribution of Luigi Mistodie, ALTFACTOR references 0.13 27/04/2017 George Suciu, BEIA SotA - Review contributions, references list of abbreviations and acronyms, conclusions for 7.1 and 7.2 0.14 02/05/2017 Carmen Rusu, ALTFACTOR SotA - Added abbreviations and acronyms 0.15 05/05/2017 Carmen Rusu, ALTFACTOR SotA - Reviewed footnotes in 6.1- 6.4 chapter 0.16 08/05/2017 Marcello Leida, TAIGER SotA - Added domain ontologies review 1.0 01/08/2017 Pedro Ferrer, PRODEVELOP Final Document Citisim Consortium Page 3 of 152 State of the Art Release Date Author, Organization Changes 2.0 29/08/2018 Carlos Jiménez, ABALIA Final version, including other ITEA3 projects related to the challenge Smart cities Citisim Consortium Page 4 of 152 State of the Art List of Figures Figure 1: Characteristics of a Smart City ..............................................................................16 Figure 2: Research challenges between Big Data and profiling ............................................35 Figure 3: Simple bar charts are great if the user needs to rapidly compare different quantities. .............................................................................................................................................37 Figure 4: Scatter plots help show correlation between variables – this example shows the relationship between total store sales (vertical) and sales from a specific promotion (horizontal). The colours represent different product types ...................................................38 Figure 5: Basic time series graph plotting sales and gross profit over a month. ....................38 Figure 6: Displaying a growth rate and icon next to a KPI - in this case entrants in a race ....38 Figure 7: Basic pie chart showing proportions of medical patients who spent time in different types of hospital rooms.........................................................................................................39 Figure 8: Area chart comparing the uptake over time for different software versions following their initial release ................................................................................................................39 Figure 9: Radar chart captures the relative importance of different customer churn drivers for a telecom company both in 2013 and in 2012 in a quickly consumable format. ....................40 Figure 10: Ranked list of top 10 music tracks by number of streams over a time period. ......40 Figure 11: Map of bubbles, each one is in a city, and the volume represents a measure. .....41 Figure 12: Bubble-scatter chart showing marketing campaigns by value generated (horizontal) and invested cost (vertical), as well as duration the campaign ran for (bubble size). ............42 Figure 13: Heat grid displaying average revenue per user (colour scheme) across customers, by both geographic market (vertical) and type of mobile device used (horizontal). ...............42 Figure 14: Dashboard built with CARTO ...............................................................................46 Figure 15: Appearance of Dashboard made with Kibana ......................................................47 Figure 16: Beats components architecture ...........................................................................48 Figure 17: Pie chart, time series and top ten list visualization build with Kibana ...................53 Figure 18: Reconstructed 3D objects and Buildings .............................................................65 Figure 19: 3D City model by Aerial Images and Cadastral Map ............................................67 Figure 20: 3D Building model from one eye stereo camera ..................................................67 Figure 21: 3D Model for Yarmouk University ........................................................................69 Figure 22: VNG Model extents .............................................................................................70 Figure 23: City model reconstruction from car image sequences ..........................................72 Figure 24: Video only 3D reconstruction with the backpack system ......................................73 Figure 25: Video depth results of the (left) “Stair” and (right) “Great Wall” sequences ..........74 Figure 26: Reconstruction buildings......................................................................................74 Figure 27: View from above and details of large scale reconstructions .................................75 Figure 28. - 3D model of Yokohama City ..............................................................................76 Figure 29: Textured 3D model of Castle Landenberg ...........................................................76 Figure 30: Residuals at image plan and visual overlay accuracy direct vs. integrated geo- referencing solution ..............................................................................................................77 Figure 31: Reconstructed model and a photograph of the building from the same perspective .............................................................................................................................................78 Figure 32: Rendered city model correctly intersected with a DTM triangulation (left); 3D city model with manually applied textures from terrestrial and airborne images (right) ................78 Figure 33: Textured point cloud model with laser and Images ..............................................79 Figure 34: Vehicle with camera (left); Dense 3D reconstruction (right) .................................80 Figure 35: System configuration of MMS (TYPE-S) (left); MMS measurement data (right) ...80 Figure 36: Super-imposition of directly georeferenced terrestrial laser scanner data and aerial LIDAR (left) and virtual city model (centre) with result after alignment (right) ........................81 Figure 37: Terrestrial laser scans of the building facades (left) and terrestrial ortho-photos wrapped on the facades (right) .............................................................................................81 Citisim Consortium Page 5 of 152 State of the Art Figure 38: Realistic Views of Main Campusf .........................................................................82 Figure 39: Texture mapped model of the Berkeley Campus .................................................83 Figure 40: Solution for creating a virtual 3D City model generation using ANN .....................83 Figure 41: Output Image of 3D Computer City ......................................................................84 Figure 42: LoDs of CityGML .................................................................................................85 Figure 43: Relation between LoDs .......................................................................................86 Figure 44: Example of different LoDs in the BLOM3D™ [78]. BlomLOD1™ (upper left), BlomLOD™ (upper right), BlomLOD3™ (bottom left), BlomLOD4™ (bottom right) ...............88 Figure 45: Mixed-LoD 3D city model of Munich by NAVTEQ as a combination of the Enhanced 3D City Model, and 3D Landmarks. ......................................................................................89 Figure 46: GlTF Adoption in web frameworks .......................................................................93 Figure 47: GlTF format specification .....................................................................................93 Figure 48: Browser support of WebGL .................................................................................96 Figure 49: Browser support of WebGL .................................................................................97 Figure 50: Cesium library layers ...........................................................................................99 Figure 51: Cesium Globe with New York City building model using 3D Tiles ........................99 Figure 52: View of Berlin city model with OSMBuildings. .................................................... 102 Figure 53: Kudan Product snapshot ................................................................................... 105 Figure 54: Example of graphical representation