AURA通过时空与颜色特征融合，实时精准识别工业烟雾类型。
AURA: A Hybrid Spatiotemporal-Chromatic Framework for Robust, Real-Time Detection of Industrial Smoke Emissions
- 结合烟雾运动模式与颜色特征进行检测
- 提升复杂环境下烟雾识别准确率，降低误报
- 适合环保监管与工厂安全监控场景
本文提出AURA，一种新型混合时空-色彩框架，用于鲁棒、实时检测与分类工业烟雾排放。该框架克服了现有监测系统在区分烟雾类型和应对环境变化方面的不足。AURA同时利用烟雾的动态运动模式和独特颜色特征，显著提升检测精度并减少误报。该框架旨在通过精确自动化监测，大幅提升环境合规性、运营安全性和公共健康水平。
原文摘要 · Abstract (English)
This paper introduces AURA, a novel hybrid spatiotemporal-chromatic framework designed for robust, real-time detection and classification of industrial smoke emissions. The framework addresses critical limitations of current monitoring systems, which often lack the specificity to distinguish smoke types and struggle with environmental variability. AURA leverages both the dynamic movement patterns and the distinct color characteristics of industrial smoke to provide enhanced accuracy and reduced false positives. This framework aims to significantly improve environmental compliance, operational safety, and public health outcomes by enabling precise, automated monitoring of industrial emissions.
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