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Applications of Artificial Intelligence in Forest Operations Engineering Research: A Systematic Review

Articolo
Data di Pubblicazione:
2026
Citazione:
Applications of Artificial Intelligence in Forest Operations Engineering Research: A Systematic Review / Forkuo, G.O., Picchio, R., Proto, A.R., Borz, S.A.. - In: CURRENT FORESTRY REPORTS. - ISSN 2198-6436. - 12:1(2026). [10.1007/s40725-026-00275-x]
Abstract:
AI enables more accurate and efficient solutions to complex forest engineering challenges. However, practical implementation remains constrained by the "black box" nature of AI, poor model generalizability across diverse ecosystems, and heavy computational demands and large datasets required—which are often incompatible with a typical forest manager's workflows and budget. Future advancements must focus on explainable AI, external validation, benchmarking, and user-friendly, edge-computing systems to transition AI from theoretical research to practical, operational forestry tools. These will further enhance sustainable forest management and engineering practices, guiding impactful future research and application.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Forkuo, Gabriel Osei; Picchio, Rodolfo; Proto, Andrea Rosario; Borz, Stelian Alexandru
Autori di Ateneo:
PROTO Andrea Rosario
Link alla scheda completa:
https://iris.unirc.it/handle/20.500.12318/168066
Pubblicato in:
CURRENT FORESTRY REPORTS
Journal
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URL

https://link.springer.com/article/10.1007/s40725-026-00275-x
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