Artificial Intelligence and Sustainability
Introduction
As climate change accelerates and environmental challenges become more complex, the need for innovative, data-driven solutions is greater than ever. Artificial Intelligence (AI) offers powerful tools to support sustainability goals by enabling smarter environmental monitoring, predictive modeling, efficient resource management, and optimized decision-making.
The special track “Artificial Intelligence and Sustainable Development” aims to explore the intersection between AI and Environmental Engineering. It will provide a platform for researchers, practitioners, and policymakers to share their latest findings, methodologies, and applications that utilize AI to promote sustainable development and address pressing environmental issues.
Key goals of this track include:
- Showcasing the potential of AI in achieving the UN Sustainable Development Goals (SDGs),
- Promoting data-driven solutions for environmental protection and climate adaptation,
- Fostering interdisciplinary collaboration between environmental scientists, engineers, data specialists, and decision-makers.
Target Audience – Who Should Attend?
This track is designed for a broad range of participants who work at the intersection of technology and sustainability, including:
- Researchers and academics in environmental engineering, computer science, earth sciences, biology, and sustainability studies,
- AI and IT professionals developing predictive models, machine learning algorithms, and intelligent systems,
- Engineers and practitioners in water management, air quality control, renewable energy, and waste management,
- Policy makers and public administration representatives responsible for environmental planning and regulation,
- Tech startups and companies offering AI-based environmental solutions,
- Students and PhD candidates interested in the application of AI for sustainability.
Thematic Areas for Workshops/Sessions in Environmental AI
- Machine learning for climate change prediction and impact modeling
- AI applications in air quality monitoring and emission control
- Smart water management and hydrological modeling using AI
- Intelligent energy systems and renewable energy forecasting
- Waste management and recycling optimization with AI
- AI for sustainable urban development and smart cities
- Environmental risk assessment: floods, droughts, and wildfires prediction
- Computer vision in satellite imagery analysis and remote sensing
- AI-supported biodiversity monitoring and ecosystem protection
- Environmental simulation and scenario analysis using AI tools
- Autonomous drones and robotic systems for environmental monitoring
- AI in life cycle assessment (LCA) and carbon footprint analysis
- Big data analytics and early warning systems for environmental hazards
- Natural resource management powered by AI
- Ethical considerations of AI in environmental applications
- AI-driven process optimization for green and circular industries
- Human-AI interfaces in environmental education and awareness
- Climate-resilient infrastructure design supported by AI
- Natural language processing (NLP) in climate policy and media analysis
- Transdisciplinary approaches: AI, sustainability, and policy integration
Publication Opportunities
Based on the papers submitted to EI 2025 (long or short papers) we will propose selected papers of this workshop for a publication process with ELSEVIR for a special Issue in the Elsevier Journal “Environmental Modelling & Software” CiteScore 9.3, Impact Factor 4.8.
Special Track Chair
- Grit Behrens, University of Applied Sciences Bielefeld, Germany, grit.behrens@fh-bielefeld.de
- Cezary Orlowski, WSB University in Gdansk, Poland, corlowski@wsb.gda.pl
- Kostas Karatzas, Aristotle University of Thessaloniki, Greece, kkara@auth.gr