To be able to shape our future sustainably, we need clean, safe energy. To achieve this, there is an increasing reliance on artificial intelligence (AI) in the energy sector. Researching and testing artificial intelligence models for this sector has the potential to improve the use of energy in the long term through optimised energy efficiency or the collection, analysis and optimisation of measured values.  

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Green AutoML for Driver Assistance Systems

Green AutoML for Driver Assistance Systems

The aim of the GreenAutoML4FAS project is to design a holistic, carbon-efficient system for driver assistance systems
GLACIATION

GLACIATION

GLACIATION aims to reduce carbon emissions by developing a distributed knowledge graph that improves the efficiency of big data analysis.
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KI Mittelstand

KI-Trainer

The AI trainers of the Mittelstand 4.0 competence centres educates people about the topic of artificial intelligence with workshops, company visits, lectures, roadshows and many other offers.
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Leibniz AI Academy

Leibniz AI Academy

Development and establishment of a transcurricular, cross-disciplinary micro-degree program "Leibniz AI Academy" at Leibniz Universität Hannover (LUH).
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MoToRes

MoToRes

Route recommendations for individual user needs, regional specifics and optimal utilisation of transport and attractions.
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PEARL DNA

Pearl-DNA

PEARL-DNA will develop and assess a complete end-to-end chain of innovative solutions — contributing to improving speed, accuracy, energy efficiency, and costs associated with DNA data storage.
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SE²A

SE²A

An interdisciplinary research center with the purpose of investigating technologies for a sustainable and eco-friendly air transport system.
Logo of Swiftt Project

SWIFTT

SWIFTT will provide forest managers with affordable, simple and effective remote sensing tools backed up by powerful machine learning models. It will offer a holistic health monitoring service to detect and map various risks for forests and their managers