by Johann Steszgal (Steszgal Informationstechnologie GmbH), Peter Kieseberg (St. Pölten UAS) and, Andreas Holzinger (University of Natural Resources and Life Sciences Vienna)

Reduction of food waste is an important target for reducing the human footprint and achieving better utilisation of natural resources. The healthcare sector especially offers a lot of potential for more sustainable handling of food. In this article we present major challenges for food waste reduction in real-world healthcare environments, as well as a solution approach.

by Refiz Duro (Austrian Institute of Technology), Hanns Kirchmeir (E.C.O. Institut für Ökologie Jungmeier), Anita Zolles (Bundesforschungs- und Ausbildungszentrum für Wald, Naturgefahren und Landschaft) and Günther Bronner (Umweltdata)

Changing climatic circumstances have a significant impact on forests: besides higher temperatures, more intense and frequent storms and drought spells affect forest growth. To see what the future is bringing, and to be able to deal with forest conservation and management, it is necessary to answer the question “how quickly do trees grow in an environment of climate change?” We take on a challenge to answer this question by integrating state-of-the-art data collection and AI-based methods.

by Refiz Duro, Rainer Simon (AIT Austrian Institute of Technology GmbH) and, Christoph Singewald (Syncpoint GmbH)

Climate change, pandemics and unstable geopolitical and economic circumstances on the global level are complex challenges necessitating approaches leveraging technological advances and human cross-domain expertise and experience. One piece of the puzzle addressing these challenges is to provide efficient services assisting decision and policy makers with insights extracted from the available data. Combining AI-based natural language processing and computer vision services with human-centred annotation and information enrichment service to build knowledge graphs for reconnaissance has a prospect to make a difference in the safety and security domain. But what does such an implementation look like, and shouldn’t such services already be integrated into most decision-making processes?

by Andrea Esuli (ISTI-CNR)

ISTI-CNR released a new web application for the manual and automatic classification of documents. Human annotators collaboratively label documents with machine learning algorithms that learn from annotators’ actions and support the activity with classification suggestions. The platform supports the early stages of document labelling, with the ability to change the classification scheme on the go and to reuse and adapt existing classifiers.