Harnessing Digital Twins for Sustainable Agricultural Water Management: A Systematic Review

Harnessing Digital Twins for Sustainable Agricultural Water Management: A Systematic Review

This systematic review explores the use of digital twins (DT) for sustainable agricultural water management. DTs simulate real-time agricultural environments, enabling precise resource allocation, predictive maintenance, and scenario planning. AI enhances DT performance through machine learning (ML)...

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Bibliographic Details
Main Authors: Rameez Ahsen, Pierpaolo Di Bitonto, Pierfrancesco Novielli, Michele Magarelli, Donato Romano, Domenico Diacono, Alfonso Monaco, Nicola Amoroso, Roberto Bellotti, Sabina Tangaro
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Applied Sciences
Subjects:
digital twin
artificial intelligence
machine learning
precision agriculture
Online Access:https://www.mdpi.com/2076-3417/15/8/4228
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