Vortexa data scientist, Kit Burgess, delivered a seminar on Real-Time Algorithmic Tracking of Global Waterborne Vessels & Commodities at the Nanyang Technological University (NTU), Singapore to a multi-disciplinary audience drawn from across academia and research institutions on 10 January. We wrap up the event highlights below.
Starting from the basic construct of a vessel's automatic identification system (AIS), Kit introduced to the audience the building blocks of Vortexa's cargo-tracking model, which tracks the live positions and activities of nearly 10,000 oil and gas tankers (from 5,000 DWT and above). Today our models are able to detect complex ship-to-ship (STS) transfers between multiple vessels, and handle incomplete datasets such as missed vessel signals or draught readings.
Kit also spoke about the mechanisms at work behind our product grade prediction models, as Vortexa delivers grade-by-grade information for crude and refined products carried on board tankers globally. The combination of proprietary cargo data, combined with machine learning algorithms including classification and regression neural network analyses, have been found to be particularly useful for high-accuracy predictions.
Finally he also touched upon the in-house energy industry domain expertise that Vortexa combines with its powerful algorithms that ultimately help achieve a higher level of comprehensiveness and accuracy in tracking.
We would like to especially thank the School of Electrical and Electronic Engineering (EEE) in NTU for the opportunity to share our knowledge with the community.