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
A novel method for error analysis in radiation thermometry with application to industrial furnaces
A Novel Machine Learning-Based Methodology for Tool Wear Prediction Using Acoustic Emission Signals
A Cyber-Physical Data Collection System Integrating Remote Sensing and Wireless Sensor Networks for Coffee Leaf Rust Diagnosis
Status and Recommendations of Technological and Data-Driven Innovations in Cancer Care: Focus Group Study
Journal of Medical Internet Research
Provides society with safe and healthy environments in areas of daily life for citizens, public buildings, hospitals, schools and other places of daily use
The project focused on developing new epidemiological methodologies and tools for analysis and decision making during the COVID19 pandemic
Development and use of the latest technologies for comprehensive omics analysis and AI in data integration, moving towards the identification of biological fingerprints (biomarkers) and personalised or precision medicine in the Basque Country
Generates scientific-technological knowledge in the field of surfaces and surface treatment technologies and solves strategic challenges with a digitised vision
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.
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