Reinforcement Learning-Driven Digital Twin for Zero-Delay Communication in Smart Greenhouse Robotics

Reinforcement Learning-Driven Digital Twin for Zero-Delay Communication in Smart Greenhouse Robotics

This study presents a networked cyber-physical architecture that integrates a Reinforcement Learning-based Digital Twin (DT) to enable zero-delay interaction between physical and digital components in smart agriculture. The proposed system allows real-time remote control of a robotic arm inside a hy...

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Bibliographic Details
Main Authors: Cristian Bua, Luca Borgianni, Davide Adami, Stefano Giordano
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Agriculture
Subjects:
digital twin
zero-delay network
negative delay
remote control
wearable device
smart agriculture
Online Access:https://www.mdpi.com/2077-0472/15/12/1290
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