This book presents selected papers from the 39th International Conference EnviroInfo 2025, held at the University of Potsdam, Germany, September 17th-19th, 2025. It explores the latest advancements in applied informatics, environmental informatics, and relevant sustainability practices with a special focus on the topic "Open Data, Open Science, and Open Society. The conference's goal is to promote collaboration, transparency, and inclusivity in addressing global challenges in the areas of green computing, sustainable software engineering, circular economy and business intelligence. As such, the papers presented here cover essential elements of shaping a greener future while also highlighting the transformative power of digital tools and data-driven strategies in addressing environmental problems that transcend geopolitical boundaries.

From climate change and biodiversity loss to water scarcity and pollution, the book examines how digital inclusion can empower communities, enhance decision-making, and promote sustainable development on a global scale. It also explores the societal aspects of environmental informatics, including environmental informatics, e.g. in developing countries. As an essential resource for researchers, professionals, and policymakers interested in leveraging ICT to address pressing environmental challenges and achieve sustainable development, it offers valuable insights, thought-provoking discussions, and innovative approaches to creating a sustainable and eco-friendly digital society in keeping the global sustainable development goals.

Presents new research at the intersection of environmental science and computational sustainability Provides new ICT methods and tools for environmental research Offers interdisciplinary approaches to environmental sciences and computational sustainability

Autorentext

Volker Wohlgemuth is a Full Professor of Industrial Environmental Informatics at the School of Engineering Technology and Life, University of Applied Sciences, HTW Berlin, Germany. His research interests include material flow management, modelling and simulation, industrial symbiosis, and environmental management information systems.

Stefan Naumann is a Full Professor of Computer Science, Mathematics, and Environmental / Sustainability Informatics at the Trier University of Applied Sciences, Environmental Campus, Birkenfeld, Germany. His research interests include the environmental impacts of information technology and environmental informatics in general.

Grit Behrens is a Professor of Applied Computer Science at University of Applied Science, Bielefeld, Germany. Her research interests inlcude environmental informatics, machine learning, data mining and web engineering. In 2011, she cofounded the Solar Computing Lab at Campus Minden and led several projects on AI-applications in the field of photovoltaics. Since 2016, she has been the Head of Interdisciplinary Development of Applications in the Area of Environmental Informatics research initiative at the University of Applied Sciences, Bielefeld.

Anna Zagorski is a Research Associate at the German Federal Environment Agency, where she works on green IT topics. Her main areas of expertise are Blue Angel software, green coding techniques, and software-related obsolescence.

Maximilian Höb is a Scientist at the Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities, and a Lecturer at Ludwig-Maximilians-University, Munich. His research focuses on the analysis of containerized high performance computing applications, specifically their resource usage and energy efficiency. He also investigates exascale-ready and data-centric containerized infrastructures and quantum computing, especially to enable hybrid QC-HPC workflows.

Inhalt

.Chap 1: An Adaptive Ant Colony System for Skip Loader Operations in Roll-on/Roll-off Logistics.- Chap 2: Towards Reliable Corrosion Forecasts in Waterway Infrastructure (LSTM-Based Models).- Chap 3: Comparison of Incremental Machine Learning Methods and Graph Neural Networks for Field-Calibration of Air Quality Sensors.- Chap 4: An open-source, AI-based monitoring station for insect monitoring.- Chap 5: Ethical Challenges in Artificial Intelligence: An Analysis Considering the Asilomar AI Principles with a Focus on Sustainability.- Chap 6: Artificial intelligence and machine learning in environmental authorities - potentials, challenges and recommendations.- Chap 7: A platform for machine learning in environmental agencies - Use Cases, User Roles, Functions.- Chap 8: Analysis and Optimization of the CO2 Footprint of Machine Learning Models.- Chap 9: Evaluating the Energy-Performance Trade-Offs of Quantized Large Language Model Agents.- Chap 10: Analysis and Optimization of a Web-Based HMI on an Embedded Building Automation System.- Chap 11: Programming Practices Influencing Software Energy Efficiency A Systematic Literature Review.- Chap 12: Evaluating Performance and Energy Efficiency of RISC-V and x86 Processors for Java Workloads.- Chap 13: Sustainability Assessment Guidance for Digital and Energy Services Infrastructure.- Chap 13: Novel Approaches for Estimating Building Survival Probability: Compositional and Parametric Modeling.- Chap 14: Supporting a Sustainable and Inclusive Urban Agriculture Federation using Dashboarding.- Chap 15: Digital Product Passport for Insect Meal: Enhancing Sustainability and Traceability in Feed Value Chains.