ILED is a software tool for machine learning complex event definitions from temporal data

Fetch your data

1. Provide examples

Gather examples to learn from, in the form of time-stamped event streams

Embed your knowledge

2. Describe your target language

Specify generic patterns to compose the rules form

Recognise events in realtime

3. Perform learning

ILED uses machine learning techniques to automatically extract rules defining interesting events from data

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4. See results

get the learnt event definitions as a set of logical rules

In which domains can I use ILED?

If you have streams of data and interesting events that can be detected from those streams, ILED can help you. Indicative streams of data and corresponding detectable events include:

  • Transaction data (from online shops, credit cards) used to detect fraud, false orders, suspicious interaction.
  • Events recognized from cameras (such as abrupt motion, people running, smoke rising) for detection of possible collision, dangerous driving, crisis detection.
  • Events recognized from other sensors (speed, proximity, acceleration, sound, temperature) to detect traffic congestion.
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ILED has been used for learning in the follow domains

Do you have any questions ?

See more technical details here now!
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