Transcript Slide 1

Mike Botts – August 2008

Sensor Web Enablement (SWE) and SensorML

August 2008

Mike Botts [email protected]

VAST Team - NSSTC University of Alabama in Huntsville

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Mike Botts – August 2008

The “Big Hammer” Approach to Sensor Fusion (circa 1991)

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Benefits and Challenges of Standards

• • • • Mike Botts – May 2008 Ideally the benefits of standards are that they: – Enable interoperability of data and information – Enable development and thus availability of tools (commercial and open source) for meeting a variety of needs – Enable supply of commodity hardware/software from a variety of vendors – Enable rapid deployment … plug-and-play – Allow one to focus on the real job and not the technology Some possible challenges with standards are: – Standard may not exist when you need it and developing them is too slow for your needs – Buying into a standard too early can result in • • • Choosing a losing standard (e.g. Betamax, HD-DVD) Investment of effort that you may not be able to afford Tools don’t exist to realize immediate benefits Some successful standards – WWW (html, httpd, TCP-IP, etc) – USB, – Microsoft Windows, Linux, and MacOS – jpeg, mpeg The best standards are those we don’t need to think about anymore 4

Relative return on effort

early implementer Mike Botts – May 2008

Standards Buy-In Decision Chart Standards-based Do-it-yourself

sweet-spot implementer – Do-it-yourself may result in faster but limited return – Return on standards tends to increase with time

Time

– Early implementers may see delayed return on investment – Sweet-spot implementers may reap maximum benefit for least effort 5

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Open Geospatial Consortium

• • • • • The Open Geospatial Consortium, Inc (OGC) is an international industry consortium of 334+ companies, government agencies and universities participating in a consensus process to develop publicly available interface specifications and encodings. Open Standards development by consensus process Interoperability Programs provide end-to-end implementation and testing before spec approval Standard encodings (e.g. GML, SensorML, O&M, etc.) – – – – Geography Markup Language (GML) – Version 3.2

Style Layer Description language (SLD) SensorML Observations and Measurement (O&M) Standard Web Service interfaces; e.g.: – – – Web Map Service (WMS) Web Feature Service (WFS) Web Coverage Service (WCS) – – – Catalog Service Open Location Services – used by communications and navigation industry Sensor Web Enablement Services (SOS, SAS, SPS) Mike Botts – May 2008 7

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Basic Desires •

Quickly

discover sensors and sensor data

(secure or public) that can meet my needs – location, observables, quality, ability to task

Obtain sensor information

in a standard encoding that is understandable by me and my software

Readily

access sensor observations

and in a form specific to my needs in a common manner,

Task sensors

, when possible, to meet my specific needs

Subscribe to and

receive alerts

particular phenomenon when a sensor measures a

Helping the World to Communicate Geographically

Sensor Web Enablement Framework

Heterogeneous sensor network Airborne Satellite In-Situ monitors

- sparse - disparate

Surveillance Bio/Chem/Rad Detectors

- mobile/in-situ - extensible

Models and Simulations Sensor Web Enablement

- discovery - access - tasking - alert notification web services and encodings based on Open Standards (OGC, ISO, OASIS, IEEE)

Decision Support Tools

- nested - national, regional, urban - adaptable - data assimilation M. Botts -2004 - vendor neutral - extensive - flexible - adaptable

Helping the World to Communicate Geographically

Background -1-

SensorML initiated at University of Alabama in Huntsville: NASA AIST funding 1999 - 2000 OGC Web Services Testbed 1.1:

Sponsors: EPA,

NASA, NIMA

Specs: SOS, O&M,

SensorML

Demo: NYC

Terrorist

Sensors: weather

stations, water quality 2001 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 2002

Specs advanced

through independent R&D efforts in Germany, Australia, Canada and US

Sensor Web Work

Group established

Specs: SOS, O&M,

SensorML, SPS, WNS, SAS

Sensors: wide

variety 2003-2004

Helping the World to Communicate Geographically

Background -2-

OGC Web Services Testbed 3.0:

Sponsors: NGA,

ORNL, LMCO, BAE

Specs: SOS, O&M,

SensorML, SPS, TransducerML

Demo: Forest Fire

in Western US

Sensors: weather

stations, wind profiler, video, UAV, satellite SAS Interoperabilty Experiment 2005 SWE Specifications toward approval: SensorML – V0.0

TransducerML – V0.0

SOS – V0.0

SPS – V0.0

O&M – Best Practices SAS – Best Practices 2006 OGC Web Services Testbed 4.0:

Sponsors: NGA,

NASA, ORNL, LMCO

Specs: SOS, O&M,

SensorML, SPS, TransducerML, SAS

Demo: Emergency

Hospital

Sensors: weather

stations, wind profiler, video, UAV, satellite OGC Web Services Testbed 5.1

Sponsors: NGA, NASA, Specs: SOS,SensorMLDemo: Streaming JPIP

of Georeferenceable Imagery; Geoporocessing Workflow

Sensors: Satellite and

airborne imagery 2007

Helping the World to Communicate Geographically

Brief Video Interlude •

Discovery of SWE services using registry

Access and portrayal of SWE Observation data

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, georegistration, response models, post measurement processing

Observations and Measurements (O&M)

observations – Core models and schema for

TransducerML

observations – adds system integration and multiplex streaming clusters of • 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

desired observations – Request collection feasibility and task sensor system for

Web Notification Service

–Manage message dialogue between client and Web service(s) for long duration (asynchronous) processes

Sensor Registries

– Discover sensors and sensor observations

Helping the World to Communicate Geographically

Status •

Current specs are in various stages –

SensorML (and SWE Common) – Version 1.0.1

TransducerML – Version 1.0

Observations & Measurement – Version 1.0

WNS – Request for Comments

SOS – Version 1.0

SPS – Version 1.0

SAS – Being released for vote

Approved SWE standards can be downloaded: –

Specification Documents: http://www.opengeospatial.org/standards

Specification Schema: http://schemas.opengis.net/

Helping the World to Communicate Geographically

Helping the World to Communicate Geographically

What is SensorML?

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XML encoding for describing sensor processes

– Including sensor tasking, measurement, and post-processing of observations – Detectors, actuators, sensors, etc. are modeled as physical processes

Open Standard

– – Approved by Open Geospatial Consortium in 2007 – Supported by Open Source software (COTS development ongoing)

Not just a metadata language

– enables on-demand execution of algorithms

Describes

– Sensor Systems – Processing algorithms and workflows Mike Botts – August 2008 18

Why is SensorML Important?

Importance:

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 Mike Botts – August 2008 –

Intelligent, autonomous sensor network

– SensorML enables the development of taskable, adaptable sensor networks, and enables higher-level problem solving anticipated from the Semantic Web 19

Atomic Processes

Processes that are considered Indivisible either by design or necessity

SensorML Processes Non-Physical Processes

Processes where physical location or physical interface of the process is not important (e.g. a fast-Fourier process)

Physical Processes

Processes where physical location or physical interface of the process is important (e.g. a sensor system)

Composite Processes

Processes that are composed of other processes connected in some logical manner Mike Botts – August 2008 20

Example Atomic Processes

• • • • • • • Transducers ( detectors , actuators, samplers, etc.) Spatial transforms (static and dynamic) – – Vector, matrix, quaternion operators “Sensor models” • • • scanners, frame cameras, SAR polynomial models (e.g. RPC , RSM) tie point model – – Orbital models Geospatial transformations (Map projection, datum, coordinate system ) Digital Signal Processing / image processing modules Decimators, interpolators, synchronizers, etc.

Data readers, writers, and access services Derivable Information (e.g. wind chill ) Human analysts Mike Botts – August 2008 21

Example Composite Processes

• • • • Sensor Systems , Platforms Observation lineage – from tasking to measurement to processing to analysis Executable on-demand process chains: – geolocation and orthorectification – algorithms for higher-level products • e.g. fire recognition, flood water classification, etc.

– Image processing, digital signal processing Uploadable command instructions or executable processes Mike Botts – August 2008 22

Status of SensorML and SWE Common

Mike Botts – August 2008 –

SensorML history

• Influenced by interoperability challenges for satellite sensors at NASA • Started at UAH in 1998 under NASA AIST funding; brought into OGC in 2000 • Approved as Public Discussion Paper (2002) • Approved as Recommended Paper (2004) • OGC 05-086 approved as Best Practices Document in Bonn (Nov 2005) • OGC 05-086r3 approved as Version 0.0 Technical Specification in July 2006 • OGC 07-000 approved as Technical Specification Version 1.0 on June 23, 2007 –

Current: document (OGC 07-000)

• Approved Version 1.0 of SensorML and SWE Common data types • Official document available at OGC ( http://www.opengeospatial.com

) • Official Reference Schema resides online at http://schemas.opengis.net/ • Doc and schema also available at http://vast.uah.edu/SensorML 23

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Where and how can SensorML processes be used?

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SensorML provides metadata suitable for discovery of sensors and processes

Find all

remote sensor systems

measuring in the

visible spectral

range with

ground resolution less than 20m

.

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Discovery Based on SensorML

Credit: Northrop Grumman PulseNet Project

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Specific Discovery Needs

• • Unique resource ids used throughout SWE; – sensor centric example: • • • • Find sensors that can do what I need (returns id=“ urn:ogc:id:sensor:123 ”) Get me a full description of this sensor urn:ogc:id:sensor:123 Now, find a service (SPS) that lets me task this sensor urn:ogc:id:sensor:123 Find all services (SOS) where I can get observations from this sensor urn:ogc:id:sensor:123 • Find all processes that can be applied to this sensor output to generate the information I require Catalog profiles for each need: – SPS, SOS, SAS services – sensors and processes – observations – terms (either through dictionaries or ontologies) Mike Botts – April 2008 Page 27

Need for Term Definitions used in SensorML and SWE

• • • • • • Observable properties / phenomena / deriveable properties (“urn:ogc:def:property:*) – – temperature, radiance, species , exceedingOfThreshold, earthquake, etc.

rotation angles, spectral curve, histogram, etc.

Capabilities, Characteristics, Interfaces, etc. (“urn:ogc:def:property:*”) – – – Width, height, material composition, etc.

Ground resolution, dynamic range, peak wavelength, etc.

RS-232, USB-2, bitSize, baud rate, base64, etc.

Sensor and process terms (“urn:ogc:def:property:*”) – – – IFOV, focal length, slant angle, etc.

Polynomial coefficients, matrix, image, etc.

QA/QC terms and tests Identifiers and classifiers (“urn:ogc:def:identifierType:*; urn:ogc:def:identifier:*” ) – – Identifiers – longName, shortName, model number, serial number, wingID, missionID, etc.

Classifiers – sensorType, intendedApplication, processType, etc.

Role types (“urn:ogc:def:role:*”) – – Expert, manufacturer, integrator, etc.

Specification document, productImage, algorithm, etc.

Sensor and process events (“urn:ogc:def:classifier:eventType:*”) – Deployment, decommissioning, calibration, etc.

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SensorML Supports description of Lineage for an Observation Observation

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Within an Observation, SensorML can describe how that Observation came to be using the “procedure” property

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On-demand processing of sensor data SensorML Observation

Mike Botts – April 2008

SensorML processes can be executed on-demand to generate Observations from low-level sensor data (without a priori knowledge of sensor system)

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SensorML – Sensor Systems

IR radiation System - Aircraft Sensor 1 Scanner Attitude Sensor 2 IMU Location Sensor 3 GPS Digital Numbers Pitch, Roll, Yaw Tuples Lat, Lon, Alt Tuples Mike Botts, Alexandre Robin, Tony Cook - 2005 Mike Botts – August 2008 31

AIRDAS UAV Geolocation Process Chain Demo AIRDAS data stream

(consisting of navigation data and 4-band thermal-IR scan-line data) Mike Botts – August 2008

AIRDAS data stream geolocated using SensorML-defined process chain

(software has no a priori knowledge of sensor system) 32

On-demand processing of higher-level products SensorML Observation

Mike Botts – April 2008

SensorML processes can be executed on demand to generate higher-level Observations from low-level Observations (e.g. discoverable georeferencing algorithms or classification algorithms)

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Observation

TMI & MODIS footprints

On-demand Geolocation using SensorML

AMSR-E SSM/I MAS TMI

Geolocation of satellite and airborne sensors using SensorML

Mike Botts – April 2008 Cloudsat Page 34 LIS

Clients can discover, download, and execute SensorML process chains SOS

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SensorML-enabled Client (e.g. STT) SensorML SLD

OpenGL

Stylers For example, Space Time Toolkit is designed around a SensorML front-end and a Styler back end that renders graphics to the screen

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Incorporation of SensorML into Space Time Toolkit Space Time Toolkit

being retooled to be SensorML process chain executor + stylers Mike Botts – April 2008 Page 36

SensorML-Enabled Web Services

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SensorML can support generation of Observations within a Sensor Observation Service (SOS) request SOS Web Service SensorML Observation

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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

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Incorporation of SensorML into Web Services SensorML process chains have been used to drive on-demand data within services (e.g. satellite nadir tracks, sensor footprints, coincident search output)

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SensorML can support tasking of sensors within a Sensor Planning Service (SPS) request SPS Web Service SensorML

Mike Botts – April 2008

For example, SensorML will be used to support tasking of video cam (pan, tilt, zoom) based on location of target (lat, lon, alt)

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SPS control of Web Cam

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Dual VASTCAMS (1 & 2)

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3D Reconstruction of Storms using SensorML Multi-directional views 3D Reconstruction of storms

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SensorML for Portrayal

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SOS SWE Visualization Clients can render graphics to screen SensorML-enabled Client (e.g. STT) SensorML SLD

OpenGL

Stylers

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SWE Portrayal Service can “render” to various graphics standards SOS SWE Portrayal Service SensorML SLD Stylers

KML Collada

Google Earth Client 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)

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Mike Botts – March 2008 TMI

SensorML to Google Earth (KML – Collada)

AMSR-E SSM/I MAS LIS 47

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SensorML Support Activities

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SensorML Navigation

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Current Tool Development and Support for SensorML

• • • • •

SensorML Forum

– mail list for SensorML discussion (300+ active members from various backgrounds) https://lists.opengeospatial.org/mailman/listinfo/sensorml

Open Source SensorML Process Execution Engine

– Along with open-source process model library, provides execution environment for SensorML described algorithms

Open Source SensorML editor and process chain development client

– on-going development of tools to allow human-friendly editors for SensorML descriptions

SensorML-enabled decision support client

– Open source Space Time Toolkit is SensorML-enabled and will be available to discover, access, task, and process sensor observations; use as is or as template for COTS development

SensorML white papers and tutorials

– being written and released on an array of SensorML topics – – Describing a Simple Sensor System Creating New Process Models ; Mike Botts – August 2008 50

SensorML Process Editors

Currently, SensorML documents are edited in XML (left), but will soon be edited using human friendly view (below) 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) Mike Botts – August 2008 51

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 Mike Botts – August 2008 52

Mike Botts – August 2008

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.

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Mike Botts – August 2008

Where are SWE and SensorML currently being used?

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Example Known Activities using SWE -1-

• • • • • •

Community Sensor Models (NGA)

– SensorML encoding of the CSM; CSM likely to be the ISO19130 standard

Multi-Intelligence Metadata Standards (DIA)

– – – MASINT committed to SensorML and SWE as future direction Conducting a Sensor Standards gap analysis on SensorML, 1451, and other CBRNE sensor standards (DIA, ORNL, JPEO, UAH, NIST)

OGC OWS5.1 Georeferenceable Imagery (NGA/NASA)

– demonstrating use of SensorML within JPEG2000 and JPIP for support of geolocation of streaming imagery (30 GB imagery) – demonstrating SWE workflow for processing data

Oak Ridge National Labs SensorNet

– – funded project is adding SWE support in SensorNet nodes for CBRNE threat monitoring Demonstrating SensorNet/SWE for North Alabama (SMDC, DESE, UAH, ORNL)

Northrop Grumman IRAD (NGC TASC)

– demonstrated end-to-end application of SensorML/SWE for legacy surveillance sensors in field [PulseNet]

Empire Challenge 08 (NGA – Seicorp - JFCOM)

– Testing and demonstrating SWE services and SensorML encodings for sensor observation processing and integration in 2008 demonstration event; initial testing was in EC 07

Helping the World to Communicate Geographically

Example Known Activities using SWE -2-

• • • • • •

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

Canadian GeoConnections Projects

– using SensorML in water monitoring network

Sensors Anywhere (SAny) and OSIRIS

– Using SensorML and SWE within several large European Union sensor projects

Marine Metadata Initiative, OOSTethys, Q2O

– – Testing and demonstrating SensorML and SWE in oceans monitoring Developing SensorML models and encodings for supporting QA/QC in ocean observations

NASA ESTO

– funded 30 3-year projects on Sensor Webs; 5 SBIR topics with SensorML and Sensor Web called out (including 2 at NSSTC)

Hurricane Missions (NASA MSFC)

– testing SensorML for geolocation and processing of satellite and airborne sensors, and SWE for access to observations – Investigating further use for future mission monitoring

Helping the World to Communicate Geographically

Example Known Activities using SWE -3-

Others

– – – – – – – – – – – SPOT Image converting DIMAP format to SensorML Landslide monitoring in Germany Water quality monitoring in Europe Mining and water management in Australia Building monitoring in Australia SWE being investigated within Office of Under Secretary of Defense/Intelligence (OSD/I) SWE a part of GEOSS activity SWE a part of CEOS effort Recent Air Force Research Lab SBIR mentioned Sensor Web focus Recent Department of Homeland Security SBIR specifically cited SensorML and SWE Vaisala Weather Station manufacturer recently joined OGC and started to create SensorML descriptions of sensors

Helping the World to Communicate Geographically

Mike Botts – August 2008

Relevant Links

Open Geospatial Consortium Standard Documents http://www.opengeospatial.org/standards OGC Approved Schema http://schemas.opengis.net/ Sensor Web Enablement Working Group http://www.opengeospatial.org/projects/groups/sensorweb SensorML information http://vast.uah.edu/SensorML SensorML Public Forum http://mail.opengeospatial.org/mailman/listinfo/sensorml 58