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Artificial Intelligence and Sustainability

Omnipresent digitalization in sustainable development results in increasing amounts of data in all relevant areas of environmental informatics, like renewable energy, environmental health, circular economy, green IT, transport, logistics, agriculture, photovoltaic, heating networks, power grids, urban ecology, nature-based solutions, building industries etc. . Applications of artificial intelligence are able to process these data as high dimensional data in very big data sets, to analyze them with goals for predictions, for recognition and interaction challenges for a more sustainable environmental protection under climate change, energy transformation and pollution conditions.

The goal of the workshop is to bundle up experts of Artificial Intelligence into a discussion on actual AI technologies which are successful in all these environmental applications and in further development on the AI-technologies.

Target group:

  • Researchers from universities and industrial companies
  • Industrial and communal partners, which are applying AI methods
  • Students, Ph-D’s and Post Docs.

Subject areas in Environmental AI for the workshop:

  • Sensor systems, data collection and data storing
  • Data preprocessing, data reduction and data analysis
  • Machine learning techniques and applications
  • Environmental modelling and data generation
  • Expert knowledge integration and scientific data models
  • Decision systems
  • Deep learning
  • Evolutionary AI
  • Image processing and recognition
  • Adaptive systems and self-learning systems
  • Unsuperwised AI

Contributions should be written in English. The workshop language is English.


Prof. Dr. Grit Behrens, Bielefeld University of Applied Sciences

Prof. Dr.-Ing. Carsten Gips, Bielefeld University of Applied Sciences

Please contact the organizer in case you are not sure whether your working topic is of interest for this special track!

Important rules for submissions and dates can be found here.