The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data.

In the world of finance, where every decision can have significant ramifications, the possibility of predicting market movements is invaluable. Traditionally, analysts have relied on a combination of data analysis, market trends, and expert insights to make informed predictions.

Due to its multivariate and multipurpose use and reuse, data’s worth is dramatically increasing, leading to an era characterized by the generation of data marketplaces towards accessing, selling, sharing, and trading data and data assets.

Syncronicity project IEEE Internet of Things Journal

Nowadays, the Internet of Things (IoT) ecosystem is experiencing a lack of interoperability across the multiple competing platforms that are available.

Conference Paper for the Global IoT Summit 2019 (GIoTS) in Aarhus, Denmark.

Conference Paper for the International Symposium on Wireless Personal Multimedia Communications at Lisboa

Conference: 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), At Genoa, Italy 10.1109/EEEIC.2019.8783709, 2019/06/13

ATOS Blog: https://atos.net/en/blog/artificial-intelligence-second-phase-iot-part-1