On-line and Adaptive Mathematical Signal Processing and Learning for Uncovering the Big Data Universe
Big Data emerges as the world’s newest resource for competitive advantage, encapsulating the dramatic rise of statistical and computational technology that allows for the acquisition and analysis of massive datasets on everything, from industrial infrastructures to online social interactions. Big Data arrives from multiple instruments and sources at immense velocity, volume, and variety, transforming the way people perceive the world and capitalize on new sources of knowledge. However, as the sources of Big Data grow, current data processing systems struggle to keep pace. This is especially true, given the imperative need to faster transform insight into action, with unmatched analytics capabilities on veracious data we can trust, while adapting easily to heterogeneous, high-dimensional Big Data, structured and unstructured, at rest and evolving, on cloud and in mixed environments. V4-ICARUS aspires to contribute to the development of a systematic framework to manage and extract knowledge from Big Sensor Data automatically recorded by multiple scientific instruments, in multi-source environments.
The V4-ICARUS project is funded by the Hellenic Foundation for Research and Innovation (HFRI) and the General Secretariat for Research and Technology (GSRT) in the framework of the "1st Call for H.F.R.I. Research Projects to Support Faculty Members & Researchers and Procure High-Value Research Equipment", under Grant Agreement no. 1725.