Ontology-driven complex event processing for real time algal bloom detection AOW Dec 2011 Jonathan Yu Kerry Taylor and Brad Sherman.

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Presentation transcript:

Ontology-driven complex event processing for real time algal bloom detection AOW Dec 2011 Jonathan Yu Kerry Taylor and Brad Sherman

Chaffey dam CSIRO.

Chaffey dam CSIRO.

Chaffey Dam affected by algal blooms CSIRO.

Proof-of-concept and Example Complex Event Definition Given a set of data streams which monitor a range of parameters – Total Phosphorus (TP), Total Nitrates (TN), Meteorological conditions, Temperature range in the water column; Able to define some complex high-level events (e.g. potential algal bloom), given the aggregation of low-level factors (e.g. Rise in TP, TN) Working from a database curated from a study on Chaffey Dam in the 1990s CSIRO.

Ontology-driven complex event system CSIRO. 1. Composes CE Sensor Network Ontology-enabled User Interface Semantic Mediator GSN VSensors Ontologies SSN Ontology Domain Ontology 7.Updates UI with notification 3. Deploys CE to GSN as VSensor via translation 4. Interface with sensors capture VSensor entities capture sensor / data sources 6. Matching event notification generated 2. Submits CE definition captures notification captures CE definition 8. Views notifications 5. Sensor streams data Users Reasoner

Future work Still work to be done to finish developing domain ontologies to allow for complex events to be defined Mapping the SSN-XG ontology with the relevant ‘sensors’ – in this case we simulate sensors using the Chaffey Dam historical dataset Deploying on a live sensor network Application of this approach to other water quality monitoring challenges – in this domain, driving force is in determining what kinds of response required. CSIRO.

Questions Jonathan Yu Research Engineer Environmental Information Systems Group CSIRO Land and Water phone: (03) CSIRO.