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<p>To improve the museum experience for tourists, this study proposes a data visualization model based on Apache ECharts. This model utilizes the museum's basic information and JavaScript libraries to construct visual data charts, and integrates the You Only Look Once version 5 (YOLOv5) network optimized by the ShuffleNet V2 module with attention mechanism enhanced Ant Colony Optimization (ACO) algorithm for real-time crowd monitoring and route planning. Results show that the YOLOv5 network in the system achieves an iteration accuracy of 94.8%. recognition accuracy of the real-time crowd monitoring system is 92.1%, with an average response time of only 87&#xa0;ms. The proposed improved ACO algorithm achieves an accuracy rate of over 80% in customizing personalized routes for tourists. The average response time for the wayfinding system to find personalized routes for tourists is 120&#xa0;ms. These results indicate that the proposed model can meets the requirements for real-time performance and accuracy in museum information graphic expression, providing new ideas for information graphic representation and pathfinding map design, and contributing to the further development of data visualization research.</p>

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Information graphic expression and wayfinding map design in digital media for museums

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月23日

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  • Ruyi Wan

摘要

To improve the museum experience for tourists, this study proposes a data visualization model based on Apache ECharts. This model utilizes the museum's basic information and JavaScript libraries to construct visual data charts, and integrates the You Only Look Once version 5 (YOLOv5) network optimized by the ShuffleNet V2 module with attention mechanism enhanced Ant Colony Optimization (ACO) algorithm for real-time crowd monitoring and route planning. Results show that the YOLOv5 network in the system achieves an iteration accuracy of 94.8%. recognition accuracy of the real-time crowd monitoring system is 92.1%, with an average response time of only 87 ms. The proposed improved ACO algorithm achieves an accuracy rate of over 80% in customizing personalized routes for tourists. The average response time for the wayfinding system to find personalized routes for tourists is 120 ms. These results indicate that the proposed model can meets the requirements for real-time performance and accuracy in museum information graphic expression, providing new ideas for information graphic representation and pathfinding map design, and contributing to the further development of data visualization research.