Introduction To SensorML

1. Introduction To SensorML Alexandre Robin – October 2006

2. Standard way of describing wide range of sensors and sensor systems (platforms, sensor grids…) aElectronic Datasheet Allow precise description of complex systems Allow global cross-domain classification Allow local/specialized domain specific classification Keep simple case simple! (i.e. thermometer) Enable sensor discovery among high number of disparate sensors accessible through a network Integrate within OGC Sensor Web Enablement Framework SensorML – Design Objectives Alexandre Robin - October 2006

3. Describe precise lineage of data, with enough information to allow error propagation With small human intervention in the general case Automatic processing within a specific domain/profile Facilitate data processing and geo-location a Automatic Provide enough information to understand and simulate sensor behavior SensorML – Design Objectives Alexandre Robin - October 2006

4. SensorML –What can be described? Platforms and Constellations SML System Sensors & Models SML SystemSML Component • Raw Data • Nature • Structure • Encoding • Data Product • Nature • Structure • Encoding Data Processing SML ProcessModelSML ProcessChain Alexandre Robin - October 2006

5. SensorML –What can be described? • WHAT was measured? Phenomenology, Frequency Response • HOW was it measured? Calibration, Quality • WHERE was it measured? Geometry, Spatial Response & Sampling • WHEN was it measured? Temporal Sampling, Impulse Response • WHY was it measured? Application GeometryCharacteristics Frequency Response Alexandre Robin - October 2006

6. System – Weather Station AirTemperature Component 1Thermometer Digital Number Component 2Barometer AtmosphericPressure Digital Number Component 3Anemometer WindSpeed Digital Number WindChillTemp Component 4Processing SensorML – Sensor Systems Alexandre Robin - October 2006

7. System – Aircraft Platform GroundRadation InterleavedScanline Subsystem 2: INS GPS Data Tuple GPS Subsystem 1: Scanner AircraftPosition DetectorBand 1 DetectorBand 2 IMU IMU Data Tuple DetectorBand 3 DetectorBand 4 SensorML – Sensor Systems Alexandre Robin - October 2006

8. Keywords, Identifiers and Classifiers for classification and indexing in Registries and Catalogs Global Characteristics and Capabilities for quick view on System capabilities Relevant Contacts and Documents to point to additional knowledge and documentation Temporal, Legal and Security Constraints to make sure the document is used only when appropriate History to keep track of System changes such as calibration events or other modifications SensorML – Header Info Alexandre Robin - October 2006

9. Specify nature of measured phenomena. Points to dictionaries which provides robust cross-domain semantic associations Specify units of measure for each scalar component of the inputs and outputs Possibilities of grouping and defining arrays of values as input and output Define connections between components to describe their interactions within a System Specify quality of values and constraints (interval, enumeration) SensorML – Inputs, Outputs, Connections Alexandre Robin - October 2006

10. SensorML – Relative Positions Relative positions ofSystem components (Both location and orientation!) Platform IMU Scanner GPS Reference Frames ofSystem components (How it relates to hardware) Swath Alexandre Robin - October 2006

11. IdentifiersClassifiersConstraints Response Characteristics ContactsDocumentationReferences CharacteristicsCapabilities Geometry Timing Spatial FrameTemporal Frame SensorML – Detector Component Additional information used for detail discovery and link to other documents Identification and Classification terms for further discovery Detector Definition of coordinate frames attached to the sensor Response characteristics(calibration, error, frequency) Outputs Inputs Sensor timing (look rays times for a scanner = gives time sequence) Sensor internal geometry (look rays direction for a scanner or camera) Params Alexandre Robin - October 2006

12. SensorML – Detector Response Alexandre Robin - October 2006

13. Concept of SensorML Array can be used to describe arrays of any Component or System Powerful to describe large arrays of “almost” identical devices Ability to individually tweak elements of the array through an indexing mechanism SensorML – Component Array Alexandre Robin - October 2006

14. SensorML – Detector Array Alexandre Robin - October 2006

15. INSData ScanTime Adjusted Time + TimeInterpolator Look Up Table Look Ray Time Position of INS in LLA ScanIndex Look Up Table LLA To ECEF Look Ray Position Position of INS in ECEF IFOIGeometry EllipsoidIntersection LLAPoint T T Position in sensor CRS Position inECEF CRS SensorML – Processing Chain IMU and GPS sensor data Obtained from Sensor Geometry and Timing Obtained from Sensor Geometry (FOV…) Derived from relative positions of sensors Alexandre Robin - October 2006

16. Specify Data Structure (imagery, in-situ, spectral, …) Weather Data Temperature Wind Speed Pressure Time Scanline Spectrum Time Time DataArray … (x 720) DataArray … (x 250) Freq1 Radiance Radiance Freq2 Freq3 Radiance SensorML – Data Description Alexandre Robin - October 2006

17. Specify Data Structure (imagery) Image RGB (1024x768) DataArray … (x 768) DataArray … (x 1024) DataArray … (x 1024) DataGroup DataGroup R R G G B B SensorML – Data Description Alexandre Robin - October 2006

18. Specify Data Encoding (ASCII, Base64 binary, Raw binary) Specify parameters for each scalar value in the structure Can specify compression methods and encryption Data structure can be described in the interface section of a System/Component Data structure can be described separately along with the observation values SensorML – Data Description Alexandre Robin - October 2006

19. Relevant Links Open Geospatial Consortium http://www.opengeospatial.org SensorML http://vast.uah.edu/SensorML Questions? Alexandre Robin - October 2006