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Komplexa inbyggda system i realtid

Lärande och optimering

Medicinsk teknik

Modellbaserad konstruktion av inbäddade system

Programmeringsspråk

Programvarutestlaboratorium

Resurseffektivisering

Säkerhetskritisk teknik

Teknisk matematik

Artificiell intelligens och intelligenta system

Automatiserade mjukvaruspråkutveckling och mjukvaruteknik

Certifierbara bevis och justifieringsteknik

Cyber-fysisk systemanalys

Datakommunikation

Digitalisering

Formell modellering och analys av inbyggda system

Förnybar energi

Heterogena system

Industriell programvaruteknik

Into DeeP

The long term goal of the project is to inspire Swedish industry to investigate how big data analytics can enable a new phase in process optimization.

Avslutat

Start

2018-04-02

Avslut

2018-12-28

Huvudfinansiering

Forskningsinriktning

Projektansvarig vid MDH

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Description of the project

Deep learning, artificial intelligence and big data analytics have the potential to bring the next leap in productivity, quality, and automation to Swedish process industry. More specifically, Deep Learning introduces a great new opportunity to handle the challenges of process industry. Setting out from the need of competence in the participating companies, the project partners will cooperate to develop web based learning modules to introduce Deep learning and artificial intelligence to a larger audience, focusing on Swedish process industry.

The long term goal of the project is to inspire Swedish industry to investigate how big data analytics can enable a new phase in process optimization.

Marketing of the learning modules will be done through a wide network of partners where the strategic innovation programs PiiA, Produktion 2030, STRIM and IoT Sweden play an important role together with clusters, trade unions and -organisations. The Into DeeP project builds on experience, knowledge and results from the project DEEP, Deep Process Learning (Vinnova, 2017-01970).

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