Using Explicit Semantic Representations for User Programming of Sensor Devices

Kerry Taylor and Patrick Penkala

CSIRO ICT Centre

Melbourne, 1st December 2009

Image: Burdekin Sensor Network, Pavan Sikka & Google

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

Context

• lots of pics of sensors

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

SSN-XG: Semantic Sensor Network Incubator Group

Commenced 1 March 2009.Two main objectives:(a) the development of ontologies for describing sensors, and(b) the extension of the Sensor Model Language (SML), one of the four SWE languages, to support semantic annotations.

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

Aim: To address real-time programming, tasking and querying sensors and sensor networks

• Represent the semantics of the command language in an ontology

• Use generic software tools, plus device-specific “transformer” and communication code modules

• Assume a stateless model (declarative queries)

• simplicity• amenability to optimisation• multi-user sharing (detect query

subsumption, for example)

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

Case Study: an Automatic Weather Station

• Environdata WeatherMaster1600

• sensors for:• air temperature,• relative humidity,• wind speed, • wind direction

• + 3 simulated sensors: voltages of the battery and solar panel and the activity of the serial port.

• proprietary command-line language of about 50 commands

• request-response interaction style over a serial port.

• Data is time-stamped and logged: for each of the four sensors at once.

• 104 kilobytes memory, FIFO

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

Environdata Command Language

Main Commands:• STORAGE to measure data and

log in memory• “STORAGE 13 CURRENT 2 3 0

0 1 EHOUR 1 0” • command 13 logs the current

wind direction in memory 2 every hour.

• MEM to retrieve data from memory

• “MEM 4 SPECIFIC 2010 11 30 09 00 00 2010 12 01 09 00 00”

• requests logged data in MEM 4 for the given 24 hour period

• R for current values for all sensors

• “R”

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

1. Model the Commands in an Ontology

queryCurrentData

queryPeriodData

setStorageFunction

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

2. Phrase queries using ontology terms in a device-independent query tool

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

3. Classify query and instantiate

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

4. Execute and see the results!

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

Benefits

• Offers a device-independent route to sensor programming, but avoids standardising to lowest common model.

• Validates queries by classification• Is self-documenting language through semantic context.• Can accommodate (some) evolution without coding.• Can also use the ontology modelling and DL reasoning to

• Represent variation in query capability amongst similar devices• Allocate queries to devices that are sufficiently capable• Admit alternative “syntaxes” (or terminology) for same functions• Discover sensors by function, location, latency, frequency,

accuracy, data format, custodian,...• Optimise wrt query subsumption (e.g. logging frequency)

• Can extend to composition, substitution, spatial and temporal reasoning etc

(see Compton et al in Proc Semantic Sensor Networks 2009)

CSIRO. Australasian Ontology Workshop. Melbourne, 1 December 2009

Future Work

Phenomics: Start with a particular observable trait or phenotype and work back to discover the causal gene.

Contact UsPhone: 1300 363 400 or +61 3 9545 2176

Email: enquiries@csiro.au Web: www.csiro.au

Thank you

CSIRO ICT CentreKerry TaylorResearch Scientist

Phone: 02 6216 7038Email: Kerry.Taylor@csiro.auWeb: www.ict.csiro.au

SSN-XG: www.w3.org/2005/Incubator/ssn/