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Digital Twins play a crucial role in bridging the physical and virtualworlds. Given the dynamic and evolving characteristics of the physical world, ahuge volume of data transmission and exchange is necessary to attainsynchronized updates in the virtual world. In this paper, we propose a semanticcommunication framework based on You Only Look Once (YOLO) to construct avirtual apple orchard with the aim of mitigating the costs associated with datatransmission. Specifically, we first employ the YOLOv7-X object detector toextract semantic information from captured images of edge devices, therebyreducing the volume of transmitted data and saving transmission costs.Afterwards, we quantify the importance of each semantic information by theconfidence generated through the object detector. Based on this, we propose tworesource allocation schemes, i.e., the confidence-based scheme and theartificial intelligence-generated scheme, aimed at enhancing the transmissionquality of important semantic information. The proposed diffusion modelgenerates an optimal allocation scheme that outperforms both the averageallocation scheme and the confidence-based allocation scheme. Moreover, toobtain semantic information more effectively, we enhance the detectioncapability of the YOLOv7-X object detector by introducing new Efficient LayerAggregation Network-HorNet (ELAN-H) and SimAM attention modules, while reducingthe model parameters and computational complexity, making it easier to run onedge devices with limited performance. The numerical results indicate that ourproposed semantic communication framework and resource allocation schemessignificantly reduce transmission costs while enhancing the transmissionquality of important information in communication services.

YOLO-based Semantic Communication with Generative AI-aided Resource Allocation for Digital Twins Construction