Fields of Application

Environment & Energy

The success of the energy revolution depends to a large extent on the digitalization of the increasingly complex energy networks. AI technologies have enormous potential for predicting energy demand, analyzing the relevant mass data and optimizing the interaction between generation, network, storage and consumption. To this end, concepts and solutions are developed to establish process models for critical infrastructures in the energy sector and to implement them in a secure integrated data and service platform. Forecasting methods based on these models support a secure energy supply and the security of energy systems.

News

What condition are the world's oceans in? To find out, numerous autonomous underwater buoys are drifting through the oceans and collecting data. In…

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DFKI's Machine Learning (ML) Computing Center has been extended by another high-performance computing system for AI algorithms. With the seventh…

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Numerous sensor systems in the North Sea record wind, humidity, hours of sunshine and many other environmental parameters. In the future, Artificial…

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Projects

PlantMap

The PlantMap project goal is a high-resolution spatiotemporal 3D map representation of individual plants –

the PlantMap. Such a map will be filled with plant data taken by autonomous robots navigating…

Artificial intelligence for energy technologies and applications in production

The KI4ETA project aims to achieve energy efficiency measures and operational optimization in production through the targeted use of AI. To achieve this goal, seven subprojects are developing an…

Cooperative Development of a Comprehensive Integrated Autonomous Underwater Monitoring Solution

In the CIAM project, autonomous underwater vehicles (AUVs) are being developed that are capable of autonomous inspection missions with a travel distance of 500km. This eliminates the need for supply…

Change Event Based Sensor Sampling

The project aims to accelerate Natural Science research process through part automatization of execution of experimentation by AI powered Change Event based Sensor Sampling (ChESS), e.g. for systems…

Use of innovative data analysis and artificial intelligence for udder health management, incorporating the latest research approaches in bulk milk analysis and image-based animal identification

The IQexpert project aims to develop an artificial intelligence-based expert system for strategic udder health management (XTE) in dairy cows. The system assists the farmer as a "digital expert" by…

Experimental environment for industrial-grade development of semantic environment perception.

The fusion of data with high spatial and temporal resolution and their interpretation are essential innovation drivers for the realisation of more sustainable processes in plant cultivation. Here,…

Deep-Learning for Multimodal Sensor Fusion

The main objective of DeeperSense is to significantly improve the capabilities for environment perception of service robots to improve their performance and reliability, achieve new functionality, and…

EnvMon-Short

Technical evaluation of a robotic measurement system for the spatial-temporal high-resolution in-situ classification of SONAR data using neural networks

Current lake monitoring is limited to punctual…

NEW APPROACH TO UNDERWATER TECHNOLOGIES FOR INNOVATIVE, LOW-COST OCEAN OBSERVATION

The deep ocean, below 200 m water depth, and the open ocean environment above it, are largest habitats but least observed ones of our planet. These highly dynamic systems provide critical climate…

National Research Data Infrastructure for Engineering Sciences

NFDI4Ing is one of the funded consortia of the NFDI initiative of DFG (https://www.dfg.de/en/research_funding/programmes/nfdi/index.html).

NFDI4Ing brings together the engineering communities and…

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz