From Sensor Web to Sensor GridFrom Sensor Web to Sensor Grid

Yaohang Li

Department of Computer ScienceNorth Carolina A&T State University

AgendaAgenda

Enabling Sensor WebSensor Markup LanguageFrom Sensor Web to Sensor GridResearch at NCAT

Sensors on the WebSensors on the Web

Sensor Web– Comprise diverse, location-aware environmental

sensing devices– Sensors

All connected to the webAll reporting positionAll reporting measureAll readable remotelyMost are accessible from the web in real timeSome controllable remotely

Web

Sensor Web at NCATSensor Web at NCAT

http://noaa.comp.ncat.edu/AggieWeather/index.html

SeaMonsterSeaMonster

http://seamonster.jun.alaska.edu/browser/

develop a wireless sensor web which will harvest high volumes of geospatial environmental data from on and around the Juneau Icefield in Southeast Alaska

Functions of Sensor WebFunctions of Sensor Web Sensor Discovery

– Location– Observable– Quality– Programmable– etc.

Obtain Sensor Information– Sensor Data Format– Programming Interface

Programming Sensors– According to Needs

Alerts and Notification– Notify a user when a particular phenomenon happened

Open Geospatial ConsortiumOpen Geospatial Consortium Open Geospatial Consortium

– An international, non-profit consensus standards organization

Tasks:– Standardize Sensor Web Services– Sensor Web Enablement

OGC Sensor Web Service Standards (APIs)– Sensor Registration Service

Discovery of sensors and sensor data

– Sensor Observation Service Access sensor information (SensorML) and sensor observations (O&M)

– Sensor Planning Service Task sensors or sensor systems

– Web Alert Service Asynchronous notification of sensor events (tasks, observation of phenomena)

SensorMLSensorMLSensorML

– An XML schema for defining the geometric, dynamic, and observational characteristics of a sensor

Characteristics of SensorML– Functional Model of Sensors

Not Detailed Hardware Description

– Hardware Independent Independent of OS (TinyOS, JVM, etc.) Independent of

– Handles Stationary and Dynamic Sensors– Handles in-situ and Remote Sensors

Information Provided by SensorMLInformation Provided by SensorML

General sensor information in support of data discovery Geolocation of the measure data Sensor observations

– Physical properties measured radiometry temperature concentration etc.

– Response characteristics temporal response

Sensor performance/quality characteristics– Accuracy and Precision– Threshold

Assumptions regarding the sensors

SensorML SemanticSensorML Semantic

From Sensor Web to Sensor GridFrom Sensor Web to Sensor Grid

Beyond Sensor Web– Sensor Web focuses on sensor data acquisition– Many Sensor Applications Want More

Information Fusion ProblemInformation Fusion Problem

How can we retrieve the valuable information from the large amount of distributed sensor data?– Sensor Fusion– Distributed Sensor Data Mining

Sensor Trustworthiness ProblemSensor Trustworthiness Problem

How can we trust the sensor data from the sensor web?– Sensor Correlation– Sensor data verification

Sensor Service Orchestration Sensor Service Orchestration ProblemProblem

How can we coordinate multiple, distributed sensor services?– Temporal-Spatial

Sensor Assimilation ProblemSensor Assimilation Problem

How can we feed distributed, heterogeneous sensor data to computational models to achieve real time processing/forecasting?

Sensor Grid: Integrating Sensor Sensor Grid: Integrating Sensor Networks and Grid ComputingNetworks and Grid Computing

Integrating Sensor Networks and Grid Computing– Give “eyes” and “ears” to a computational grid– Process, model, correlate, and mine real-time,

distributed information about phenomena in the physical world

– Permit on-the-fly modeling, decision and action

Applications– Environment monitoring– Prediction and early warning of natural disasters

Sensor GridSensor Grid

Figure from Chen-Khong Tham and Rajkumar Buyya

Sensor Grid: Physical World Sensor Grid: Physical World IT World IT World

Edge Server ApplicationsAntennaChip

RFID Tag Sensor

Hardware & PhysicsHardware & Physics

Information TechnologyInformation Technology

Sensor Data Archive

Sensor Grid vs. Sensor NetworkSensor Grid vs. Sensor Network

Service-Oriented Architecture Distributed Information Fusion

– Nodes in a sensor network are independently sensoring the environment

Redundant Information Some reading may be inaccurate

– Information Fusion Compute the most probable sensor reading

Distributed Autonomous Decision Making– Can be achieved through an adaptive learing process

Challenge of the Sensor GridChallenge of the Sensor Grid

EVENT SOURCES

Many types of event sources and sensors– RFID (handheld, portal, truck mount, etc.), barcode,

location, moisture, temperature, … Many sensor vendors

– Alien, Intermec, Matrics, ThingMagic, SAMsys, Zebra Many different frequencies, protocols, interfaces

– LF, HF, VHF, UHF, Microwave– Periodic, Aperiodic– Ethernet, PCMCIA, RS-232

Many devices in different locations to manage– Device health, device upgrade– Distributed management

Information Capture– Data format not consistent– Data is granular and redundant– Information based on observations from multiple

sensor sources

Ongoing NOAA Projects @ NCAT – Ongoing NOAA Projects @ NCAT – Earth Information System FrameworkEarth Information System Framework

New technologies emerging:– Service-oriented architecture, OpenDAP, HDF5, Google

Earth, GIS, GEOSS

Framework Approach– Applications can “plug-in” and extend functionality– Can support a broad set of applications with relatively

concise software

Earth Information SystemEarth Information System

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Uses Framework for Access

Viewing

Manipulation

Observations,Models,Policies

Predictions,Improved Models,Improved Policies

Earth System ScienceEarth System Science

“By taking the ‘whole systems’ approach, we are more likely to find sustainable solutions to environmental problems.”

Earth System ModelEarth System Model

Atmosphere ModelNon-transient eddy resolving planetary

wave

Terrestrial Carbon Cycle Model

Simplified TRIFFID

Ocean Carbon and Nutrient Cycle

ModelIncluding sediments

Cryosphere ModelDynamic ice sheet including fast flow.

Simple seaice

Terrestrial Hydrology ModelSimplified MOSES

scheme

Ocean Model3-D, non-eddy-

resolving, frictional geostrophic

Research @ NCATResearch @ NCAT

Workflow for a Sensor Grid– Sensor Orchestration– GridNexus

Ensemble-based Kalman Filter for Sensor Data Fusion

From Weather Nowcast to Weather Forecast

Acknowledgement– NOAA-ISET Center