DroneAI for Resilient Nature | 12.62 MB
Title: DroneAI for Resilient Nature
Author: Mika-Petri Laakkonen
Category: Nonfiction, Science & Nature, Science, Earth Sciences, Geography, Computers, Advanced Computing, Artificial Intelligence, Biological Sciences, Environmental Science
Language: English | 233 Pages | ISBN: 9783032190086
Description:
This proceedings volume supports the European drone and artificial intelligence industries in advancing solutions for the agrifood and natural resources sector. It addresses some of the most critical global challenges: food security, food safety, environmental conservation and sustainable production, water-resource management, and the restoration of biological diversity. The chapters highlight advances in AI acceleration, top-level integration with foundational technologies, the sustainability of edge AI systems, and the requirements for deploying generative AI. A strong emphasis is placed on scientific methodology, ensuring transparency, reproducibility, and the validity of the research presented. The chapters here showcase practical use cases supported by rigorous validation strategies, including comparisons with ground-truth data. The book provides objective and reliable parameters for monitoring ecosystem resilience, particularly in the aftermath of natural disasters.
This proceedings volume supports the European drone and artificial intelligence industries in advancing solutions for the agrifood and natural resources sector. It addresses some of the most critical global challenges: food security, food safety, environmental conservation and sustainable production, water-resource management, and the restoration of biological diversity. The chapters highlight advances in AI acceleration, top-level integration with foundational technologies, the sustainability of edge AI systems, and the requirements for deploying generative AI. A strong emphasis is placed on scientific methodology, ensuring transparency, reproducibility, and the validity of the research presented. The chapters here showcase practical use cases supported by rigorous validation strategies, including comparisons with ground-truth data. The book provides objective and reliable parameters for monitoring ecosystem resilience, particularly in the aftermath of natural disasters.
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