ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W1, 31-38, 2016
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W1/31/2016/
doi:10.5194/isprs-annals-IV-2-W1-31-2016
 
05 Oct 2016
INTEGRATING DYNAMIC DATA AND SENSORS WITH SEMANTIC 3D CITY MODELS IN THE CONTEXT OF SMART CITIES
K. Chaturvedi and T. H. Kolbe Technische Universität München, Chair of Geoinformatics, 80333 Munich, Germany
Keywords: Smart Cities, Semantic 3D City Models, CityGML, Dynamizers, Sensor Web Enablement Abstract. Smart cities provide effective integration of human, physical and digital systems operating in the built environment. The advancements in city and landscape models, sensor web technologies, and simulation methods play a significant role in city analyses and improving quality of life of citizens and governance of cities. Semantic 3D city models can provide substantial benefits and can become a central information backbone for smart city infrastructures. However, current generation semantic 3D city models are static in nature and do not support dynamic properties and sensor observations. In this paper, we propose a new concept called Dynamizer allowing to represent highly dynamic data and providing a method for injecting dynamic variations of city object properties into the static representation. The approach also provides direct capability to model complex patterns based on statistics and general rules and also, real-time sensor observations. The concept is implemented as an Application Domain Extension for the CityGML standard. However, it could also be applied to other GML-based application schemas including the European INSPIRE data themes and national standards for topography and cadasters like the British Ordnance Survey Mastermap or the German cadaster standard ALKIS.
Conference paper (PDF, 2542 KB)


Citation: Chaturvedi, K. and Kolbe, T. H.: INTEGRATING DYNAMIC DATA AND SENSORS WITH SEMANTIC 3D CITY MODELS IN THE CONTEXT OF SMART CITIES, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W1, 31-38, doi:10.5194/isprs-annals-IV-2-W1-31-2016, 2016.

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