A Cloud-Fog Automation architecture for USVs reports 86% collision classification accuracy and improved latency over conventional approaches via a three-layer Cloud-Edge-IoT design.
Empowering Robotic Training with Kinesthetic Learning and Digital Twins in Human–Centric Industrial Systems,
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CFTel proposes a cloud-fog-edge architecture for scalable, low-latency telerobotics by integrating 5G URLLC, edge intelligence, embodied AI, and digital twins to overcome limitations of pure cloud-based systems.
citing papers explorer
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Leveraging Cloud-Fog Automation for Autonomous Collision Detection and Classification in Intelligent Unmanned Surface Vehicles
A Cloud-Fog Automation architecture for USVs reports 86% collision classification accuracy and improved latency over conventional approaches via a three-layer Cloud-Edge-IoT design.
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CFTel: A Practical Architecture for Robust and Scalable Telerobotics with Cloud-Fog Automation
CFTel proposes a cloud-fog-edge architecture for scalable, low-latency telerobotics by integrating 5G URLLC, edge intelligence, embodied AI, and digital twins to overcome limitations of pure cloud-based systems.