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NSERC Presents 2 Minutes with Emil M. Petriu

Faculty of Engineering, University of Ottawa, in partnership with Larus Technologies Corp.


Video Name

2 Minutes with Emil M. Petriu


NSERC Communications



Release Date

February 16, 2016


Emil M. Petriu and Larus Technologies Corp. jointly developed the Larus Technologies predictive risk-aware decision support system,Total::Insight™. This system analyzes data and produces accurate predictions and information to help decision-makers manage a large amount of sensor data. The technology has been applied to defence, security, health care and infrastructure protection, with local and international recognition and application. This partnership earned Dr. Petriu one of NSERC's Synergy Awards for Innovation in 2015.

Emil M. Petriu

The most important infrastructures today in Canada, for instance, are health care—they are energy, transportation and security itself. So Larus Technologies had to develop something that is providing today a decision support system which is able to handle the big amount, the big amount of data, to make sense of all that information and provide support in real time for decision makers.

Rami Abielmona

The Total::Insight is what we call the DSS: decision support system. The goal was, how do we bring all this data together and try to fuse it or correlate it in some way so that we can present it to the user in a more refined manner?

Emil M. Petriu

Definitely, Larus Technologies have the firsthand knowledge of the real-life applications, which are not common for a university professor.

Rami Abielmona

Let's say you've got a building that you're trying to protect, and of course there's sensors that are monitoring that particular critical infrastructure.

Emil M. Petriu

So that all type of data—sensory data—which are specific to different applications. But in general there are video sensors, audio sensors, GPS sensors, sensors from satellites, sensors from under water.

Rami Abielmona

So Total::Insight will basically take all these different data sources, extract the relevant features, then we fuse those features using proprietary algorithms that we've designed here at Larus.

And then once you've fused it, you have it in a state where you can make decisions; you can make classification type decisions, predictions; you could make associations; you can start recommending some responses.

We are applying this at Larus Technologies within the defence and security realm, but we have also applied it, as I mentioned, in environmental perception, in health applications, and in financial applications.

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