Download - Semantic Web Enabled Smart Farming
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Semantic Web Enabled Smart FarmingSemantic Machine Learning and Linked Open Data Application for Agricultural and Environmental Informatics
CSIRO COMPUTATIONAL INFORMATICS
Raj Gaire | Research Software Engineer
22 October 2013
IN COLLABORATION WITH
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Smart Farm
• Informed Farming• Precision agriculture
– Sensors, information system, decision support systems
– System exists within a farm-gate
• Connected Farm• Devices in the farm are connected with each other and the world using
internet
• Farmers are connected to the farm devices, other farmers and experts
• Things (e.g. Cattle) in the farm can be monitored remotely.
• Integrated Farm• Includes Farmers in the supply chain - suppliers, logistics, consumers – back
to the farmers to complete the loop.
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Kirby ‘Smart’ Farm
• Location Armidale, NSW, Australia
• Farm Area: 739 Hectares (or 1827 Acres)
• Smartfarm Area: 269 Hectares (or 665 Acres)
• Livestock: Cattle, Sheep
• Devices: 100 Soil Sensors
2 Weather Stations
Cattle ear tags
Flex, Alix PC, 3G Modem etc.
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What do farmers want?
• Measurement data produced by 100 sensor every couple of minutes?
• Weather measurement produced every couple of minutes?
• Cattle location updated frequently?
• Farmers are interested in the alerts about the things in the farm.• Cattle leave the farm
• When to sow
• Current market value of their livestock
• Soil in a paddock is compacted
• Researchers/Experts are interested in the data.
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Our Architecture
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Smartfarm Ontology
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Data Dimensions
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GSN Extended
• Geo-Spatial Analysis• Implemented using R and Java packages
• Event (Alert) Processing• Extended GSN to process event descriptions and produce alerts
• Synchronous and Asynchronous events
• Farms can create their own events
• Semantic Web Enablement• Sensor data stored in MySQL
• Linked data are produced using defined URIs
• Statistical data are stored in Virtuoso triple store
– Provides open access to everyone, analyse data using SPARQL
– VisualBox and Google APIs for visualisation
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Event Detection
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Web Form… …. …. ….… …. …. ….… . Submit
Event Manager
Event Description
Storage
Event Evaluator
Event VirtualSensor
Message Queue
GSN Storage
Event Description
Alerts
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Important Links
PURPOSE LINK
Homepage (ROOT) http://smartfarm-ict.it.csiro.au
Semantics http://smartfarm-ict.it.csiro.au/semantics.jsp
Latest Data http://smartfarm-ict.it.csiro.au/latest
Specific Latest Data ROOT/dataset/sensornets/kirby-farm/type/{id} [/latest
Time Series Data Cube ROOT/dataset/sensornets/kirby-farm/{type}/{id} [/year/{year}/[month/{month}/[day/{day}/[hour/{hour}]]]]
VisualBox Home http://kirbyfarm-virtuoso.dyn.dhs.org/visualization/
SPARQL endpoint http://kirbyfarm-virtuoso.dyn.dhs.org:8890/sparql
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Visualisation
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Future Works
• SPARQL based access to dynamically generated data cubes
• Machine Learning over the Data
• Integrate satellite data
• Social Farming
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Machine Learning Opportunities
• Cost of Sensor Networks
• Variations are possibly correlated and predictable• Soil variation, elevation -> soil ec, temp, vwc
• BOM forecast -> farm weather
• Data collected over last 2 years • Use to generate predictive model
• Produce sensor data without sensors.
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Because data from Sensor networks in farms worth more than the sensor networks!
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Acknowledgement
Kerry Taylor
Laurent Lefort
Michael Compton
David Henry
Ali Salehi
David Lamb
Gregory Falzon
Derek Schneider
Ashley Saint
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Computational InformaticsRaj GaireResearch Software Engineer
t +61 2 6216 7090e [email protected] www.csiro.au/CCI
CSIRO COMPUTATIONAL INFORMATICS
Thank you