Cloud-Edge Collaborative-Based Digital Twin System for Hardware Limited IIoT Scenario

As the demand for more efficient intelligent manufacturing models continues to grow, the manufacturing industry is in urgent need of improving the intelligence and informatization of manufacturing models. Digital Twin, as an emerging intelligent technology, can enhance the intelligence of the Industrial Internet of Things (IIoT) in manufacturing industry by providing virtual-physical mapping and real-time interaction. However, the current deployment of Digital Twin in practical industrial scenarios is challenging due to limited resources on local hardware and high computing loads in the cloud center. To address these challenges, this paper has established an edge-cloud collaborative Digital Twin System that includes the Edge Digital Twin (EDT) mode in IIoT Scenario. EDT mode enables Digital Twin System to complete most of its tasks with fewer computing resources without relying on three-dimensional (3D) modeling. The remaining tasks need to upload the EDT to the cloud. After combining the 3D model of the cloud, the complete Digital Twin can be obtained. Experimental results show that the proposed solution is verified through a case of intelligent exterior inspection of air conditioner units in a laboratory setting. The results of experiments showed that the established system not only addressed the challenge of deploying Digital Twin on local hardware with limited resources but also relieved the computational pressure on the cloud and reduced the overall task latency.