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Tecnalia. Inspiring Business

Tecnalia. Inspiring Business

Mathematics and technology join forces in artificial intelligence

2012.06.11

TECNALIA and BCAM sign an agreement to strengthen their capacity to transfer knowledge to the Basque business.

Artificial intelligence helps solve complex problems in areas such as transport, energy, health, etc.

Bilbao, May 14, 2012. Basque Center for Applied Mathematics, BCAM, and TECNALIA  research alliance, have signed an agreement to launch a joint research line focused on artificial intelligence and stochastic processes, consonant with the interests and activities of both institutions. The agreement formalizes a first project focused on applying these techniques to pattern recognition in security applications, optimal control of industrial systems and energy sustainability of communications equipments. One of the immediate consequences arising from this agreement is the publication of a joint research position between the two centers.

Artificial intelligence helps solve complex optimization problems in an efficient way in areas as diverse as transport, energy, industrial systems, health, entertainment, economy, banking, robotics and logistics. Conceptually, consists essentially artificial intelligence algorithms, processes or techniques which when executed, result in actions that maximize a performance measure determined by the initial information and knowledge / experience gained on the problem at hand.

Specifically, some of the algorithms based on artificial intelligence try to alleviate the computational complexity needed to solve highly complex problems inspired behaviors observed in nature. Thus, these algorithms, grouped in the so-called "computational intelligence", combine and exploit concepts and principles derived from biology, genetics, materials science, neurology and sociology.

The artificial intelligence is one of the strategic research areas of TECNALIA that is currently using these techniques in a multitude of scenarios and applications such as road network planning before courts and / or traffic incidents, improving urban mobility in smart cities, economic and commercial advice to companies, the analysis of massive data consumption or the deployment of wind farms, among many others.

Furthermore, statistical learning methodologies are useful in areas where you need to decide with limited information. This is a research area with important applications that BCAM develops with important applications on automated systems (hardware), such as pattern recognition in text documents, medical images, or the cataloging and classification of documents.

Such methods can be implemented as algorithms in automated surveillance systems in sensor networks, to detect or follow materials, objects or unwanted behavior. It is also useful tools in assisting decision making in resource allocation policies for projects, aid to PYMEs, etc. In addition, this research area will be used to apply mathematics in problems of optimization and optimal control posed by the industry, mobility, sustainability communications and self-connectivity of intelligent cities.


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