1. Mike Botts – October 2008 1 Open Geospatial Consortium Sensor Web Enablement GWG Plenary October 16, 2008 Dr. Mike Botts mike.botts@uah.edu Principal Research Scientist University of Alabama in Huntsville

2. Helping the World to Communicate Geographically What is SWE? SWE is technology to enable the realization of Sensor Webs –much like TCP/IP, HTML, and HTTPD enabled the WWW SWE is a suite of standards from OGC (Open Geospatial Consortium) –3 standard XML encodings (SensorML, O&M, TML) –4 standard web service interfaces (SOS, SAS, SPS, WNS) SWE is a Service Oriented Architecture (SOA) approach SWE is an open, consensus-based set of standards

3. Helping the World to Communicate Geographically Why SWE? Break down current stovepipes Enable interoperability not only within communities but between traditionally disparate communities –different sensor types: in-situ vs remote sensors, video, models, CBRNE –different disciplines: science, defense, intelligence, emergency management, utilities, etc. –different sciences: ocean, atmosphere, land, bio, target recognition, signal processing, etc. –different agencies: government, commercial, private, Joe Public Leverage benefits of open standards –competitive tool development –more abundant data sources –utilize efforts funded by others Backed by the Open Geospatial Consortium process –350+ members cooperating in consensus process –Interoperability Process testing –CITE compliance testing

4. Helping the World to Communicate Geographically What are the benefits of SWE? Sensor system agnostic - Virtually any sensor or model system can be supported Net-Centric, SOA-based –Distributed architecture allows independent development of services but enables on-the-fly connectivity between resources Semantically tied –Relies on online dictionaries and ontologies for semantics –Key to interoperability Traceability –observation lineage –quality of measurement support Implementation flexibility –wrap existing capabilities and sensors –implement services and processing where it makes sense (e.g. near sensors, closer to user, or in- between) –scalable from single, simple sensor to large sensor collections

5. Mike Botts – July 2006 5

6. Helping the World to Communicate Geographically Basic Desires Quickly discover sensors and sensor data (secure or public) that can meet my needs – based on location, observables, quality, ability to task, etc. Obtain sensor information in a standard encoding that is understandable by my software and enables assessment and processing without a-priori knowledge Readily access sensor observations in a common manner, and in a form specific to my needs Task sensors, when possible, to meet my specific needs Subscribe to and receive alerts when a sensor measures a particular phenomenon

7. Helping the World to Communicate Geographically Latest SWE Application 1. Greed sensor described using SensorML, enabling plug-n-play and on-demand processing 2. Real-time and archived observations accessed through SOS 3. SAS notifies FEDS when threshold is reached 4. Additional sensors/actuators tasked using SPS and necessary action initiated

8. Helping the World to Communicate Geographically Decision Support Tools - vendor neutral - extensive - flexible - adaptable Heterogeneous sensor network In-Situ monitor s Bio/Chem/Rad Detectors Surveillance Airborne Satellite - sparse - disparate - mobile/in-situ - extensible Models and Simulations - nested - national, regional, urban - adaptable - data assimilation M. Botts -2004 Sensor Web Enablement - discovery - access - tasking - alert notification web services and encodings based on Open Standards (OGC, ISO, OASIS, IEEE) Sensor Web Enablement Framework

9. Helping the World to Communicate Geographically History -1- SensorML initiated at University of Alabama in Huntsville: NASA AIST funding OGC Web Services Testbed 1.1: Sponsors: EPA, NASA, NIMA Specs: SensorML, SOS, O&M Demo: NYC Terrorism Sensors: weather stations, water quality OGC Web Services Testbed 1.2: Sponsors: EPA, General Dynamics, NASA, NIMA Specs: SOS, O&M, SensorML, SPS, WNS Demo: Terrorist, Hazardous Spill and Tornado Sensors: weather stations, wind profiler, video, UAV, stream gauges 1999 - 20002001 Specs advanced through independent R&D efforts in Germany, Australia, Canada and US SWE WG established Specs: SOS, O&M, SensorML, SPS, WNS, SAS 20022003-2004

10. Helping the World to Communicate Geographically History -2- OGC Web Services Testbed 3.0: Sponsors: NGA, ORNL, LMCO, BAE Specs: SOS, O&M, SensorML, SPS, TML Demo: Forest Fire in Western US Sensors: weather stations, wind profiler, video, UAV, satellite SAS Interoperabilty Experiment 2005 OGC Web Services Testbed 4.0: Sponsors: NGA, NASA, ORNL, LMCO Specs: SOS, O&M, SensorML, SPS, TML, SAS Demo: Radiation, Emergency Hospital Sensors: weather stations, wind profiler, video, UAV, satellite 2006 2007 SWE Specifications approved: SensorML – V1.0.1 TML – V1.0 SOS – V1.0 SPS – V1.0 O&M – V1.0 SAS – V0.0 WNS – Best Practices OGC Web Services Testbed 5.1 Sponsors: NGA, NASA, Specs: SOS, SensorML, WPS Demo: Streaming JPIP of Georeferenceable Imagery; Geoprocess Workflow Sensors: Satellite and airborne imagery EC07: in-situ sensors, video

11. Helping the World to Communicate Geographically SWE Specifications Information Models and Schema –Sensor Model Language (SensorML) for In-situ and Remote Sensors - Core models and schema for observation processes: support for sensor components and systems, geolocation, response models, post measurement processing –Observations and Measurements (O&M) – Core models and schema for observations; archived and streaming –Transducer Markup Language (TML) – system integration and multiplex streaming clusters of observations Web Services –Sensor Observation Service - Access Observations for a sensor or sensor constellation, and optionally, the associated sensor and platform data –Sensor Alert Service – Subscribe to alerts based upon sensor observations –Sensor Planning Service – Request collection feasibility and task sensor system for desired observations –Web Notification Service –Manage message dialogue between client and Web service(s) for long duration (asynchronous) processes –Sensor Registries (ebRIM)– Discover sensors and sensor observations

12. Helping the World to Communicate Geographically Status Current specs are in various stages –SensorML/SWE Common – Version 1.0.1 (V2.0 underway) –TML – Version 1.0 –Observations & Measurement – Version 1.0 (V2.0 underway) –WNS – Request for Comments –SOS – Version 1.0 (V2.0 about to be initiated) –SPS – Version 1.0 (V2.0 underway) –SAS – Ready for final vote (may skip V1.0 for V2.0) Approved SWE standards can be downloaded: –Specification Documents: http://www.opengeospatial.org/standardshttp://www.opengeospatial.org/standards –Specification Schema: http://schemas.opengis.net/http://schemas.opengis.net/

13. Helping the World to Communicate Geographically Why is SensorML Important? –Discovery of sensors and processes / plug-n-play sensors – SensorML is the means by which sensors and processes make themselves and their capabilities known; describes inputs, outputs and taskable parameters –Observation lineage – SensorML provides history of measurement and processing of observations; supports quality knowledge of observations –On-demand processing – SensorML supports on-demand derivation of higher-level information (e.g. geolocation or products) without a priori knowledge of the sensor system –Intelligent, autonomous sensor network – SensorML enables the development of taskable, adaptable sensor networks, and enables higher-level problem solving anticipated from the Semantic Web

14. Helping the World to Communicate Geographically Executing SensorML Processes Flexibility of execution engine Flexibility of execution location SensorML – UAH Open Source Execution Engine – Compute server (e.g. NGA IPL) – COTS (e.g. ERMapper, Matlab, etc.) – Web services (e.g. BPEL, Grid) – Client – Web Service – Middleware – On-board sensor or platform

15. Mike Botts – January 2008 15 SWE Visualization Clients can render graphics to screen SensorML SOS OpenGL SensorML-enabled Client (e.g. STT) Stylers SLD For example, Space Time Toolkit executes SensorML process chain on the front-end, and renders graphics on the screen based on stylers (uses OGC Style Layer Description standard)

16. Mike Botts – January 2008 16 Incorporation of SWE into Space Time Toolkit Space Time Toolkit has been retooled to be SensorML process chain executor + SLD stylers

17. Mike Botts – March 2008 17 SWE Portrayal Service can “render” to various graphics standards SensorML For example, a SWE portrayal service can utilize a SensorML front- end and a Styler back-end to generate graphics content (e.g. KML or Collada) However, it’s important that the data content standards (e.g. SWE) exist to support the graphical exploration and exploitation ! SOS KML SWE Portrayal Service Google Earth Client Stylers SLD Collada

18. Mike Botts – March 2008 18 SWE to Google Earth (KML – Collada) AMSR-E SSM/I LIS TMI MAS

19. Helping the World to Communicate Geographically Demo: Radiation Attack on NY OWS4 Demonstration Project (Fall 2006) –Purpose of Demo: illustrate discovery, access to and fusing of disparate sensors –Client: UAH Space Time Toolkit –Services: SOS – in-situ radiation sensors SOS – Doppler Radar SOS – Lagrangian plume model WCS – GOES weather satellite SensorML – discovery and on-demand processing WMS – Ortho Imagery Google Earth – base maps –See all OWS4 demos (interactive)See all OWS4 demos –Download this demo (AVI: 93MB):Download this demo

20. Helping the World to Communicate Geographically Demo: Northrop Grumman PulseNet PulseNet Demonstration –Purpose of Demo: PulseNet was an end- to-end demonstration and test of SWE capabilities for legacy sensor systems –Client: PulseNet client (NGC) –Services: SOS – weather stations SOS – MASINT sensors (seismic, magnetic, radiation, acoustic, etc.) SOS – web cam SPS – web cam SensorML – sensor descriptions –download this demo (wmv:30 MB)download this demo

21. Helping the World to Communicate Geographically Demo: Satellite Data NASA –Purpose of Demo: illustrate access to satellite observations and on-demand geolocation –Client: UAH Space Time Toolkit –Services: SOS – satellite footprints (UAH) SOS – aircraft observations (NASA) SOS – satellite observations (UAH) SensorML – on-demand processing (UAH) Virtual Earth – base maps –Download this demo

22. Helping the World to Communicate Geographically Demo: NASA/NWS Forecast Model

23. Helping the World to Communicate Geographically Demo: NASA/NWS Forecast Model -2- NASA assimilation of AIRS satellite data into weather forecast model –Purpose of Demo: illustrate the refinement of regional forecast models based on SensorML and SWE services –Client: Web-based client (NASA) –Services: SOS – NAM forecast model SOS – phenomenon miner(NASA) SAS – phenomenon miner (NASA) SOS – AIRS satellite observations (UAH) SOS – footprint intersections (UAH) SensorML – On-demand processing (UAH) –Download this demo

24. Helping the World to Communicate Geographically Demo: Robot Control University of Muenster SPS Robot Demo –Purpose of Demo: demonstrate streaming of commands to SPS controlling a robot and retrieval of streaming video from the robot camera using SOS –Client: IFGI Video Test Client IFGI SPS Test Client –Services: SOS – video from robot (52 North) SPS – video camera control (52 North) –Download this demo:Download this demo

25. Helping the World to Communicate Geographically Demo: SPOT Image SPOT SPS and JPIP server –Purpose of Demo: illustrate dynamic query of SPS; show on-demand geolocation of JPIP stream using SensorML –Client: UAH Space Time Toolkit –Services: SPS – satellite imagery feasibility [archived or future] (SPOT) WCS/JPIP server – streaming J2K image with CSM parameters encoded in SensorML (SPOT) SensorML – On-demand geolocation (UAH) Virtual Earth – base maps –Download this demo (AVI-divx:16MB)Download this demo

26. Helping the World to Communicate Geographically Demo: Tigershark UAV-HD Video SensorML OpenGL SensorML-enabled Client (e.g. STT) Stylers SLD Tigershark SOS JP2 NAV The Tigershark SOS has two offerings: (1) time-tagged video frames (in JP2) and (2) aircraft navigation (lat, lon, alt, pitch, roll, true heading) both served in O&M. A SensorML process chain (using CSM frame sensor model) geolocates streaming imagery on- the-fly within the client software (enabled with SensorML process execution engine)

27. Helping the World to Communicate Geographically Demo: Tigershark UAV-HD Video -2- Empire Challenge 2008 –Purpose of Demo: illustrate on-demand geolocation and display of HD video from Tigershark UAV –Client: UAH Space Time Toolkit –Services: SOS – Tigershark video and navigation (ERDAS) SOS – Troop Movement (Northrop Grumman) SensorML – On-demand processing (Botts Innovative Research, Inc.) Virtual Earth – base maps –Download this demoDownload this demo

28. Helping the World to Communicate Geographically Tigershark Geolocation

29. Helping the World to Communicate Geographically Demo: Real-time Video streaming UAH Dual Web-based Sky Cameras –Purpose of Demo: demonstrate streaming of binary video with navigation data; on-demand geolocation using SensorML –Client: 52 North Video Test Client UAH Space Time Toolkit –Services: SOS – video and gimbal settings (UAH, 52 North) SPS – Video camera control (52 North, UAH) SensorML – On-demand processing (UAH) Virtual Earth – base maps –Download this demoDownload this demo

30. Helping the World to Communicate Geographically Application: DLR Tsunami Warning System

31. Helping the World to Communicate Geographically Application: NASA Sensor Web

32. Helping the World to Communicate Geographically Application: NASA Sensor Web -2-

33. Helping the World to Communicate Geographically Application: Sensors Anywhere (S@NY)

34. Helping the World to Communicate Geographically Other Known Applications -1- Community Sensor Models (NGA/CSM-WG) –SensorML encoding of the CSM; CSM likely to be the ISO19130 standard CBRNE Tiger Team (DIA, ORNL, JPEO, NIST, STRATCOM) –SensorML and SWE as future direction, with CCSI from JPEO and possibly IEEE1451 SensorNet (Oak Ridge National Labs) –funded project to add SWE support into SensorNet nodes for threat monitoring –Developing SensorNet/SWE architecture for North Alabama (SMDC, DESE, UAH, ORNL) PulseNet (Northrop Grumman TASC) –demonstrated end-to-end application of SensorML/SWE for legacy surveillance sensors (demonstrated at EC07 and EC08) Sensor Web (SAIC - Melbourne, FL) –Developing end-to-end SWE components for MASINT and multi-sensor intelligence (demonstrated at EC08) European Space Agency –developing SensorML profiles for supporting sensor discovery and processing within the European satellite community –establishing SPS and SOS services for satellite sensors NASA –funded 30 3-year projects (2006) based on RFP citing SensorML and Sensor Webs; additional RFP in 2008 –5 SBIR topics with SensorML and Sensor Web cited –Received 2008 Business Innovative of Year Award for Sensor Web 2.0 based on SWE (new proposals under review) Empire Challenge 2007 & 2008 –PulseNet demonstrated at EC07 –SAIC Sensor Web and OGC SWE Pilot Project participated at EC08

35. Helping the World to Communicate Geographically Other Known Applications -2- Sensors Anywhere (S@NY), OSIRIS, and NSPIRES –Using SensorML and SWE within several large European Union sensor projects Marine Metadata Initiative, OOSTethys, GOMOOS, Q2O (NOAA) –Implementing and demonstrating SWE in several oceans monitoring activities –Developing SensorML models and encodings for supporting QA/QC in ocean observations Israeli Ministry of Defense –Testing/implementing TML for sensor data Department of Homeland Security –In 2007 SBIR, requested SensorML and SWE proposals ASUS Wireless Home Monitoring System –$23 billion/year company in Taiwan building commercial Zigbee Home Monitoring system using SWE DLR German-Indonesian Tsunami Warning System Others –Landslide monitoring in Germany –Water quality monitoring in Europe and Canada –Mining and water management in Australia –Building monitoring in Australia –SWE a part of GEOSS and CEOS activities –Hurricane monitoring at NASA –Vaisala weather sensor vendor joined OGC and creating SensorML descriptions of their sensor systems

36. Helping the World to Communicate Geographically Directions Needed Real, permanent implementations –Operational services and encodings, not just demos Online semantic dictionaries and ontologies –Term definitions in dictionaries –Ontologies connecting terms –Share dictionary with public where possible Discovery –Sensor discovery, as well as service discovery –Consider discovery closer to sensor for fine grained temporal-spatial search (e.g. for UAV video) Process Definition Library –Define common process models in SensorML –IPL and others can then support these models Sensor component and observation profile –Not necessary but useful for improved interoperability and ease of implementation Continued tool development Commitment to Use –Can go long way toward getting sensor and software vendor commitment Flexibility of execution location

37. Helping the World to Communicate Geographically Conclusions SWE has been tested and has proven itself –Useful, flexible, efficient, extensible –Simple to add to both new and existing legacy systems –Enables paradigm shifts in access and processing of observations SWE is getting buy-in from scattered sensor communities –A commitment from the IC and DoD communities could provide the inertia to realize the full benefits (i.e. abundance of data, available of tools) –The IC and DoD communities will benefit from contributions in the public sectors –Sensor vendors will contribute directly to Sensor Web only after user community commitment –SWE open to improvements by the user communities Tools are being developed to support SWE –Tools will ease buy-in –Tools will assist in realizing the full benefits of SWE SWE is ready to meet the challenges of the IC and DoD communities

38. Helping the World to Communicate Geographically Relevant Links Open Geospatial Consortium http://www.opengeospatial.org Sensor Web Enablement Working Group http://www.ogcnetwork.net/SWE SWE Public Forum http://mail.opengeospatial.org/mailman/listinfo/swe.users SensorML information http://www.ogcnetwork.net/SWE/SensorML SensorML Public Forum http://mail.opengeospatial.org/mailman/listinfo/sensorml

39. Helping the World to Communicate Geographically Additional Slides

40. Helping the World to Communicate Geographically Sensor Web Vision -1- Sensors will be web accessible Sensors and sensor data will be discoverable Sensors will be self-describing to humans and software (using a standard encoding) Most sensor observations will be easily accessible in real time over the web

41. Helping the World to Communicate Geographically Sensor Web Vision -2- Standardized web services will exist for accessing sensor information and sensor observations Sensor systems will be capable of real-time mining of observations to find phenomena of immediate interest Sensor systems will be capable of issuing alerts based on observations, as well as be able to respond to alerts issued by other sensors

42. Helping the World to Communicate Geographically Sensor Web Vision -3- Software will be capable of on-demand geolocation and processing of observations from a newly-discovered sensor without a priori knowledge of that sensor system Sensors, simulations, and models will be capable of being configured and tasked through standard, common web interfaces Sensors and sensor nets will be able to act on their own (i.e. be autonomous)

43. Mike Botts – January 2008 43 SensorML Process Editors Currently, we diagram the process (right top) and then type the XML version; soon the XML will be generated from the diagram itself (right bottom) Currently, SensorML documents are edited in XML (left), but will soon be edited using human friendly view (below)

44. Mike Botts – March 2008 44 Java Class Generator Tool Programmer needs add only execution code Takes an instance of a SensorML ProcessModel and generates the template for the Java class that can execute the ProcessModel

45. Mike Botts – March 2008 45 SensorML Table Viewer Will provide simple view of all data in SensorML document Web-based servlet or standalone; upload SensorML file and see view Ongoing effort: initial version in May 2008 Future version will support resolvable links to terms, as well as plotting of curves, display of images, etc

46. Mike Botts – March 2008 46 Simple SensorML Forms for the Mass Market User fills out simple form with manufacturer name and model number, as well as other info. Then detailed SensorML generated.

47. Mike Botts – March 2008 47 Where and how SensorML can be used

48. Mike Botts – March 2008 48 Supports description of Lineage for an Observation Observation SensorML Within an Observation, SensorML can describe how that Observation came to be using the “procedure” property

49. Mike Botts – March 2008 49 On-demand processing of sensor data Observation SensorML processes can be executed on-demand to generate Observations from low-level sensor data (without a priori knowledge of sensor system) SensorML

50. Mike Botts – March 2008 50 On-demand processing of higher-level products Observation SensorML SensorML processes can be executed on- demand to generate higher-level Observations from low-level Observations (e.g. discoverable georeferencing algorithms or classification algorithms) Observation

51. Mike Botts – March 2008 51 SensorML can support generation of Observations within a Sensor Observation Service (SOS) Observation SensorML For example, SensorML has been used to support on-demand generation of nadir tracks and footprints for satellite and airborne sensors within SOS web services SOS Web Service request

52. Mike Botts – March 2008 52 SensorML can support tasking of sensors within a Sensor Planning Service (SPS) SensorML For example, SensorML will be used to support tasking of video cam (pan, tilt, zoom) based on location of target (lat, lon, alt) SPS Web Service request

53. Mike Botts – March 2008 53 SWE Visualization Clients can render graphics to screen SensorML SOS OpenGL SensorML-enabled Client (e.g. STT) Stylers SLD

54. Mike Botts – March 2008 54 SWE Portrayal Service can “render” to various graphics standards SensorML For example, a SWE portrayal service can utilize a SensorML front-end and a Styler back-end to generate graphics content (e.g. KML or Collada) SOS KML SWE Portrayal Service Google Earth Client Stylers SLD Collada