Data Intelligence technologies focus on collection, distribution, storage and especially analysis of data in complex contexts, with the specific aim of discovering characteristics, trends, relationships and, ultimately, non-evident knowledge underlying the data. This is especially relevant in Big Data environments, but also in any context in which the data obtained can improve understanding of critical processes in a particular domain. Some modern Artificial Intelligence techniques, such as Machine Learning or Visual Analytics, are very relevant in certain Data Intelligence application.
Data Intelligence in Industry
Both in the discrete manufacturing industry and in the continuous processes industry, there is a very high unexploited potential for underlying knowledge which can be obtained by applying Data Intelligence on already available data. We take historical scenarios and temporal series of high complexity (in number of variables, in sample frequency, in volume of information, in type of data, in heterogeneous sources), as well as data produced in real time, to show the domain experts patterns and trends allowing them to anticipate faults (e.g., preventative and prescriptive maintenance) or to improve their production strategies.
Energy and Data Intelligence
Energy is an important field where Data Intelligence is applied. In aspects of energy efficiency, it contributes greater understanding of the patterns, trends and relationships of the different variables affecting consumption and efficiency. Data Intelligence also has a big role to play in the monitoring of external variables, such as availability and variations in energy prices, or even in the analysis of data to optimise and improve patterns of consumption in burning issues, such as electric vehicles or the circular economy.
Sources of Unstructured Information
The analysis of unstructured information, with non-existent, unknown, incompatible, dispersed or chaotic formal structures, is a major line of work in Data Intelligence. We work in these highly challenging environments to discover those non-evident patterns and trends, such as patterns of behaviour and opinion on the internet, in smart city environments, in cybersecurity attacks, in medical and bio-health environments, etc.
- Noteworthy Projects
Status and Recommendations of Technological and Data-Driven Innovations in Cancer Care: Focus Group Study
Journal of Medical Internet Research
Meaningful Big Data Integration for a Global COVID-19 Strategy
IEEE Computational Intelligence Magazine
An effective numerical strategy for retrieving all characteristic parameters of an elastic scatterer from its FFP measurements
Journal of Computational Physics
Three-Dimensional Calvarial Growth in Spring-assisted Cranioplasty for Correction of Sagittal Synostosis
The Journal of Craniofacial Surgery
Quality of data measurements in the big data era: Lessons learned from MIDAS project
IEEE Instrumentation & Measurement Magazine
Development of a new generation of equipment for the steel industry with the objective of responding to market needs
Develops a sensor that allows more accurate and robust information to be obtained on the actual machining situation in order to obtain a thorough prediction of tool wear.
Generates scientific-technological knowledge in the field of surfaces and surface treatment technologies and solves strategic challenges with a digitised vision
It develops technology to make industry and industrial products resilient to cyber-attacks throughout their life cycle and promotes the development of the Basque Cybersecurity Industry
Throughout Europe, many people are handicapped by reduced capabilities that are either permanent or temporary