Design and Implementation of the Visual Management System for Intelligent Twin Grain Silos

DOI: https://doi.org/10.62517/jes.202602127

Author(s)

Yuanhang Wu*, Yunguang Zhang, Xuehao Zhang, Song Zhang, Luyang Tian, Yiwen Li

Affiliation(s)

School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou, Henan, China

Abstract

This paper, based on digital twin technology, designs and implements a lightweight intelligent grain silo visualization system to address issues in small and medium-sized grain depots, such as inaccurate environmental monitoring, lack of visualization methods, and untimely warning responses, providing a digital tool for clear observation and precise management. The system adopts a four-layer architecture and, with the help of IoT sensor devices, achieves real-time collection and monitoring of the grain depot environment. A 3D simulation of the grain depot is constructed based on the Unity3D engine. WebGL technology is utilized to enable lightweight, cross-platform deployment, and JSLIB bridging technology facilitates bidirectional communication between the Vue frontend and the Unity scene. Ultimately, a closed loop of data collection—transmission—processing—feedback is formed. Experimental results indicate that the system can monitor the grain depot environment in real time and issue timely warnings, providing an economically feasible technical solution for the digital transformation of small and medium-sized grain depots.

Keywords

Digital Twin; Grain Depot Management; Virtual-Physical Mapping; Unity3D; Internet of Things

References

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