Technische Universität München Lehrstuhl für Geoinformatik
Integrating Dynamic Data and Sensors with Semantic 3D City Models
Kanishk Chaturvedi, Thomas H. Kolbe
Geospatial Sensor Web Conference Münster, Germany 30 August, 2016
Chair of Geoinformatics Technische Universität München Germany
Technische Universität München Lehrstuhl für Geoinformatik
Semantic 3D City Models ► Semantic 3D City Models
● Relevant objects of the urban space are classified and their spatial and thematic properties will be described
● Are key for Urban Information Modelling
► CityGML (OGC international standard since 2008) ● Data model (UML) + Exchange format (based on GML3) ● Different thematic areas + Levels of Detail concept (LOD0 - LOD4) ● 3D geometry, 3D topology, semantics, and appearance
► CityGML is very useful in environmental & energy simulations, disaster management, training simulators ● In most simulations, time plays an important role, i.e. dynamic and
time-varying properties ► Time-varying properties are not yet supported in CityGML 30.08.2016 Dynamizers for semantic 3D city models 2
Technische Universität München Lehrstuhl für Geoinformatik
Time-varying properties ► Slower Changes
● History or evolution of cities/city models versioning concept
► Highly dynamic changes ● Variations of spatial properties: change of a feature’s geometry,
both in respect to shape and to location (e.g. moving objects) ● Variations of thematic attributes:
changes of physical quantities like energy demands, mean temperature, solar irradiation; air quality in streets and buildings
● Variations with respect to sensor or real-time data
30.08.2016 Dynamizers for semantic 3D city models 3
Source:C. García-Ascanio and C. Maté, “Electric power demand forecasting using interval time series: A comparison between VAR and iMLP,”Energy Policy
Technische Universität München Lehrstuhl für Geoinformatik
30.08.2016 Dynamizers for semantic 3D city models 4
Sensors Databases
Dynamizers
Spatial Properties Thematic Properties Appearance Properties
External Files
Tabulated data e.g. from simulation results or sensors
Buildings Transportation Objects
Water Bodies Vegetation City Objects
Technische Universität München Lehrstuhl für Geoinformatik
Dynamizer – A New CityGML Feature Type ► attributeRef refers to a specific
property of a static CityGML object which value will then be overridden/ replaced by the (dynamic) values specified in the ‘Dynamizer’ feature.
► startTime and endTime denote time span for which Dynamizer provides dynamic values
► Dynamizer composes of AbstractTimeseries: ● Allows represent time-variant values in
different and generic ways ● E.g. Timeseries, Sensor observations etc.
30.08.2016 Dynamizers for semantic 3D city models 5
gml:AbstractFeature
AbstractCityObject
Dynamizer + attributeRef :URI + startTime :TM_Position + endTime :TM_Position
Abstract Timeseries
+dynamicData
Technische Universität München Lehrstuhl für Geoinformatik
Example Scenario
30.08.2016 Dynamizers for semantic 3D city models 6
Estimated (in kwh)
Heat Demand
JAN-15 61578
FEB-15 52148
MAR-15 41011
.
.
.
.
.
.
DEC-15 64984
<cityObjectMember> <Building gml:id = "building1">
<gen:doubleAttribute name = "HeatDemand"> <gen:value = xxx />
</gen:doubleAttribute> </Building> </cityObjectMember>
<cityObjectMember> <dyn:Dynamizer> <dyn:attributeRef> //Building [@gml:id = 'building1']/doubleAttribute[@name = 'HeatDemand']/gen:value</dyn:attributeRef> <dyn:startTime> 2015-01-01T00:00:00Z </dyn:startTime> <dyn:endTime> 2015-12-31T00:00:00Z </dyn:endTime> <dyn:dynamicData>.. </dyn:dynamicData> </dyn:Dynamizer> </cityObjectMember>
CityGML object
Dynamizer
Source of dynamic data
Replacing dynamic attributes using XPath
Technische Universität München Lehrstuhl für Geoinformatik
Dynamic Data from Sensors ► An important source of dynamic data may be sensor
services. ► Two popular standards
● OGC Sensor Observation Services (SOS) ● Open standard, part of OGC Sensor Web Enablement (SWE) ● Allows querying real-time sensor data and sensor data timeseries. ● Observation responses are encoded in O&M standard
● OGC SensorThings API ● Very lightweight standard to interconnect the Internet of Things
devices, data and applications over the web ● Built on OGC SWE and O&M standards ● Provides REST services and compact data encodings in JSON format
30.08.2016 Dynamizers for semantic 3D city models 7
Source : http://www.opengeospatial.org/ogc/markets-technologies/swe Source : http://www.sensorup.com/
Technische Universität München Lehrstuhl für Geoinformatik
Integrating Sensors and Observations
30.08.2016 Dynamizers for semantic 3D city models 8
gml:AbstractFeature
AbstractCityObject
Dynamizer + attributeRef :URI + startTime :TM_Position + endTime :TM_Position
Abstract Timeseries
+dynamicData SensorConnection
+ serviceType :stringAttribute + linkToObservation :URI[0..1] + linkToSensor: URI[0..1] + sensorID : stringAttribute
0..1
+linkToSensor
+sensorLocation
0..1
0..n
Technische Universität München Lehrstuhl für Geoinformatik
<cityObjectMember> <dyn:Dynamizer gml:id = "HeatDemandTimeseries" > <dyn:attributeRef>//RoofSurface[@gml:id ='building1_roofSurface1'] /doubleAttribute[@name = ‘PV_Power_Generation'] /gen:value </dyn:attributeRef> <dyn:startTime>2016-01-01T00:00:00Z</startTime> <dyn:endTime>2016-12-01T00:00:00Z</endTime> <dyn:linkToSensor> <dyn:SensorConnection> <dyn:sensorID>. . . </dyn:sensorID> <dyn:serviceType>. . . </dyn:serviceType> <dyn:linkToObservation>. . . </dyn:linkToObservation> <dyn:linkToSensor>. . . </dyn:linkToSensor> <dyn:sensorLocation xlink:href=“#building1_roofSurface1“/> </dyn:SensorConnection> </dyn:linkToSensor> </dyn:Dynamizer> <cityObjectMember>
Example for a Sensor Connection
30.08.2016 Dynamizers for semantic 3D city models 9
Sensor (PV Panel) building1_roofSurface1
building1
Image source : http://www.royalgreengas.com/index.php/photovoltaic/residential-buildings
Unique Sensor ID SOS or SensorThings API
SOS GetObservation SOS DescribeSensor
Link to CityGML Object
Technische Universität München Lehrstuhl für Geoinformatik
Dynamizer + attributeRef :URI + startTime:TM_Position + endTime :TM_Position
30.08.2016 Dynamizers for semantic 3D city models 10
gml:AbstractFeature
AbstractCityObject
TimeseriesML:: TimeseriesTVP
0..1 +dynamicDataTVP
TimeseriesML:: TimeseriesDR
+dynamicDataTDR 0..1
CompositeTimeseries
TimeseriesComponent + repetitions:integer + additionalGap :TM_Duration[0..1]
AbstractTimeseries
1..* +component
+dynamicData
AtomicTimeseries
SensorConnection + serviceType :stringAttribute + linkToObservation :URI[0..1] + linkToSensor: URI[0..1] + sensorID : stringAttribute
0..1 +linkToSensor
+sensorLocation
0..1
0..n
{ordered}
0..1 1
SOS::GetObservationResponse + observationData :OM_Observation[1..*]
+observationData
0..1
context AtomicTimeseries inv: dynamicDataDR xor dynamicDataTVP xor observationData
Dynamizer ADE for CityGML 2.0
<<ADEElement>> AbstractCityObject
<<ADE>>
+dynamizers
0..*
Also allows including OGC TimeseriesML 1.0
Also allows representing Complex repetitive patterns
Technische Universität München Lehrstuhl für Geoinformatik
Summary ► Dynamizers enhance static city models by dynamic
property values ● by referencing a specific attribute (e.g. geometry, thematic or
appearance property) of an object ● overriding the static value of the referenced object attribute by
dynamic property values ► Dynamizers support multiple dynamic representations
● OGC TimeseriesML1.0, OGC O&M
► Establish explicit links to sensors ● Linking sensor observations with the respective city model objects ● Providing location of sensors as city objects
► Support also nested patterns for values based on statistics and general rules
30.08.2016 Dynamizers for semantic 3D city models 11
Technische Universität München Lehrstuhl für Geoinformatik
Publications ► Chaturvedi, K. and Kolbe, T. H., 2016. Integrating
Dynamic Data and Sensors with Semantic 3D City Models in the context of Smart Cities.
Accepted and to be published in 3DGeoInfo 2016 Conference, Athens, Greece.
► Chaturvedi, K. and Kolbe, T. H., 2015. Dynamizers – Modeling and Implementing Dynamic Properties for Semantic 3D City Models.
Published in 3rd Eurographics Workshop on Urban Data Modelling and Visualisation, TU Delft, The Netherlands.
30.08.2016 Dynamizers for semantic 3D city models 12