用肉眼观察检测河流中的大型塑料物体:现有知识综述

Nani Anggraini, Irfan Tawakkal, Djusdil Akrim, I. Rachman, Toru Matsumoto
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引用次数: 0

摘要

目前,全世界都面临着水体塑料污染的问题。塑料垃圾已成为海洋、沿海和河流环境中的大量污染物,对水生生物构成了重大威胁。在塑料监测中,目视观察是一种常用的方法,可用于测量数量、成分和分布,识别新出现的趋势,以及设计预防措施或缓解策略。本研究试图从当前研究趋势和方法的角度,对近期有关用目视观测检测大型塑料物体的研究进行回顾,并提出有前景的未来研究方向。本研究采用文献计量学方法和定性内容分析法,对 108 篇关于检测水中垃圾物体的文章进行了系统的识别和综述。研究结果表明,依靠人工智能(AI),利用无人机设备和摄像头,通过机器学习和深度学习方法进行处理,自动检测物体开始成为视觉观测的一种趋势,并提供了很好的准确性结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visual Observation to Detect Macroplastic Object in River: A Review of Current Knowledge
Currently, the world is facing the problem of plastic pollution in water bodies. Plastic waste has become an abundant pollutant in the marine, coastal and river environments, making it a major threat to aquatic life. Visual Observation in plastic monitoring is a popular method used to measure quantity, composition, and distribution, identify emerging trends, and design preventive measures or mitigation strategies. This study attempts to review recent studies regarding visual observation for detecting macroplastic objects in terms of current research trends and methodologies and suggests promising future research directions. This study used a systematic method with a bibliometric approach and qualitative content analysis to identify and review 108 articles on detecting litter objects in the water. The study results show that automatic object detection is starting to become a trend in visual Observation by relying on artificial intelligence (AI) with UAV devices and cameras that are processed using Machine Learning and Deep Learning methods which provide promising accuracy results.
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