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Using Artificial Intelligence to Tackle Sustainable Development and Climate Change Challenges

Medium: Buch
ISBN: 978-3-032-34039-9
Verlag: Springer
Erscheinungstermin: 06.12.2026
vorbestellbar, Erscheinungstermin ca. Dezember 2026

This book brings together cutting-edge research and practice at the intersection of artificial intelligence, sustainability, and climate action. This book reflects the growing role of AI as a powerful tool to enhance decision-making, optimize resource use, and develop innovative responses to the climate crisis

Featuring contributions from an international community of researchers, this book showcases how AI-driven approaches are being developed and applied across diverse sectors and contexts. The chapters explore a wide range of topics, including environmental monitoring, climate risk assessment, sustainable urban systems, smart energy solutions, governance frameworks, and AI-enabled education and capacity-building.


Produkteigenschaften


  • Artikelnummer: 9783032340399
  • Medium: Buch
  • ISBN: 978-3-032-34039-9
  • Verlag: Springer
  • Erscheinungstermin: 06.12.2026
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2026
  • Serie: Climate Change Management
  • Produktform: Gebunden
  • Seiten: 928
  • Format (B x H): 155 x 235 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

AI for Authentic Sustainable Marketing and Consumer Trust in the Age of Climate Misinformation.- Real-Time Urban Odour Risk Maps via ML Surrogates Trained on CFD.- Measuring the Meaning: A Framework for Evaluating Cognitive and Discursive Characteristics of LLMs’ Narratives in Sustainability.- The Ethics of Generative AI: Navigating the Intersection of AI and Cybersecurity- ANN-Driven Optimization of Pervious Concrete for Resilient and Sustainable Urban Pavements.- A Multi-Modal AI Framework for Predicting Urban Flood Risk Under Climate Change Scenarios.- FinTech, Artificial Intelligence, and Sustainability: A Bibliometric Keyword-Driven Study Toward the Green Transition.- Comparison of Machine Learning Algorithms for Optimizing Glazing Thermal Properties and Building Energy Performance.- Carbon Footprint of Brain Tumour Segmentation with U-Net Across Multiple Energy Grids: Can filtering reduce emissions in the dataset training?.- Quantum Machine Learning for Mobile Charging as a Service in Net-Zero Cities.