VADITA: Visual Analytics for Detecting Illegal Transport Activities

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Yi Shan, Aolin Guo, Zekai Shao, Tian Qiu, Xueli Shu, Qianhui Li, Siming Chen

Published: 2024, Last Modified: 05 Jan 2026VAST Challenge@VIS 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: This paper presents a visual analytics system designed to address the IEEE VAST Challenge 2024 Mini-Challenge 2. The system can support the matching and anomaly detection of multi-source heterogeneous spatio-temporal data, thereby enabling the detection of illegal transport activities. The primary contribution of the system lies in its analysis-driven interaction design.