Städte sehen sich durch den Klimawandel einer zunehmenden Komplexität und einer Vielzahl an Krisen gegenüber. Steigende Temperaturen und häufigere Extremwetterereignisse belasten die urbane Infrastruktur erheblich. Verstädterung und Bevölkerungswachstum verschärfen diese Herausforderungen, indem sie den Flächenbedarf erhöhen und die Ressourcennutzung intensivieren. Versiegelte Flächen verhindern die natürliche Wasserversickerung und verschärfen Hochwassergefahren. Zudem führen urbane Wärmeinseln zu erhöhtem Energieverbrauch und Gesundheitsrisiken.

During the corona pandemic, the role of science was seen as something very important in broad sections of society. Unfortunately, this appears to be less the case with regard to climate change. Increasingly, subjective and emotionally based statements are dominating the discussion, which must be viewed extremely critically in view of the complex interactions and extreme effects. On the other hand, great hope is being placed in science to master the complex challenges with the help of artificial intelligence (AI). With the public appearance of generative AI (GenAI) in the form of ChatGPT, a new, partly critical discussion is being held, although AI-based technologies have already made impressive progress as a result of scientific research for many years and numerous developments are already in real use. On the one hand, science is expected to provide insights and recommendations for the responsible use of AI. On the other hand, the use of AI in research work is also discussed critically because it is used, for example, in the application phase of research projects or to evaluate the data obtained and to write down and communicate the results. This gives rise to questions such as “How valid are scientific achievements that are produced with (the help of) AI?” Especially when using generative AI, there is a risk that the own creation process will degenerate due to uncontrolled use, excessive dependency and distortion of results [1], because activities that go beyond routine processes are conveniently left to generative AI, which can be a problem especially when processing complex tasks. An analysis of the authors of around 30 master’s theses from 2023 and 2024 in an international engineering master’s program showed that around 1/3 of the theses are strongly influenced by GenAI results, recognizable by the usual listing form, the text style and the lack of reference to the task. These papers were also among the 1/3 with the lowest grading. Without guidance on the effective use of GenAI, its use does not appear to lead to improved performance, but instead encourages the unthinking copying of text modules.

On the other hand, observations of the use of generative AI in everyday teaching and research show that GenAI can promote complexity competence in particular when used in a targeted manner on the basis of appropriate training. The authors use GenAI in various contexts of their research, increasingly to support the solution of complex problems and tasks in complex environments. The main area of application is water management and increasingly the analysis of urban areas to adapt to water-related challenges caused by climate change. The main focus here is on the massive impact of extreme weather events such as heavy rainfall and prolonged periods of drought on urban and regional infrastructure as well as forest and agricultural areas. These main areas of application are not only highly complex in thematic terms. Solutions must be implemented at urban and municipal level, and here too, the spatial, infrastructural and organizational environment is highly complex. It is against this background that the observations described in the use of generative AI were made, the theoretical framework described in this article was created and the hypothetical analysis was carried out, for which empirical evidence is still pending, but in preparation.

Um den Herausforderungen der immer komplexer werdenden globalen Umwelt- und Gesellschaftskrisen gerecht zu werden, steigt die Notwendigkeit, Nachhaltigkeit auch im Projektmanagement zu verankern. Die Methode OktoPus führt die Projektleitung mit Team strukturiert während des gesamten Projektes zur ganzheitlichen Nachhaltigkeitsintegration im Projektmanagement, gegliedert in die acht OktoPus-Cluster Nachhaltigkeitsverständnis, Mindset, Stakeholder-Integration und Kommunikation sowie Projektziele, -planung, -durchführung und -abschluss.

Die Anwendung von KI-Tools beschleunigt die Umsetzung von mehr Nachhaltigkeit sowohl durch mehr Effizienz als auch eine gesteigerte Ergebnisqualität. Je nach OktoPus-Cluster kommen verschiedene KI-Teilbereiche und Funktionen, wie Natural Language Processing, Research & Optimization, Data Analytics und Image Understanding zum Einsatz. Insbesondere Natural Language Processing dominiert in allen OktoPus-Clustern.

Economy and society are currently exposed to multi-layered multi-crises. Against the backdrop of the covid pandemic, a growing shortage of skilled workers, increasing armed conflicts or persistent refugee flows, cities and municipalities in particular have to deal with resulting local impacts. Parallel to these highly dynamic crisis events, cities and municipalities continue to be called upon to face the now established challenges of climate change, sustainability and digitalization. More and more, there are organizational and also psychological overloads in coping with everyday tasks as a result of increasing complexities. Because of the excessive demands, there is a retreat to familiar and routinerelated everyday work and the neglect of the search for adequate solutions to the increasingly complex problems. Especially in the field of municipal infrastructure, which requires rapid and comprehensive adaptation to the manifold impacts of climate change, this excessive demand increasingly leads to recourse to rather simple solutions, which, however, do not justice to the complexity of the situation. During two certificate courses at Hof University of Applied Sciences (Germany) on the development of climate-adapted urban planning and on successful digitalization in municipal water management, a novel tool for dealing with complex situations was developed to practice on examples. It was observed among the approximately 70 participants in both courses that used this method two to three times already led to a visible change in the perception and assessment of complex situations, without the need for psychologically accompanied training of change behavior.

An der Hochschule Hof wird derzeit ein neues Gebäude für das Institut für Wasser- und Energiemanagement gebaut (Fertigstellung 2023). Die Zielsetzung, das Gebäude möglichst vollständig mit Erneuerbaren Energien zu versorgen, wurde bereits frühzeitig in die Ausschreibung und später in die Architektur integriert. So kann eine Plattform für zukünftige Forschungs- und Entwicklungsarbeiten im Bereich der Gebäudeversorgung, -Regelung und -Optimierung dezentraler Konzepte geschaffen und als Vorzeigeobjekt der Allgemeinheit präsentiert werden. Das energetische Versorgungskonzept
beinhaltet neben thermischer Anlagentechnik (Solarthermie, Luft/Wasser- und Sole/Wasser-Wärmepumpen) auch elektrische Komponenten, wie Photovoltaik, Windkraft und gekoppelte photovoltaisch-thermische Lösungen. Aktuelle Forschungsschwerpunkte, wie die Sektorenkopplung des elektrischen Eigenverbrauchs mittels Wärmepumpen, tragen ebenso wie die Verwendung eines großen thermischen Schichtenspeichers (ca. 157 m³) mit anwendungsoptimierten Einströmgeometrien zur effizienteren Nutzung von erneuerbaren Energien bei. Ein Batteriespeicher und zwei externe Eisspeicher dienen sowohl Forschungszwecken, als auch zur Steigerung der Versorgungssicherheit. Es wird die energetische Kopplung des energieintensiven Laborbetriebs mit dem Gesamtsystem vorgestellt, durch welche forschungsseitige Wärme- und Kältebedarfe und Bereitstellung thermischer bzw. elektrischer Energie aus Brennstoffzellen-, Blockheizkraft- und Brennerversuchsständen optimal verquickt werden können.