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<p>Manual processing of fish videos from underwater cameras can be very time-consuming, which currently limits the use of video-based monitoring. Recent advances in computer vision allow artificial intelligence (AI) methods to automatically classify environmental conditions, detect the presence of fish, classify species and estimate their total body length and swimming direction. However, despite the promises of AI to automate these labor-intensive tasks, there remain important technical and practical challenges. In this article, we present key findings, guidelines and limitations for the use of AI for automated monitoring of river fish using underwater camera videos.</p>

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KI-gestütztes Videomonitoring aquatischer Ökosysteme - Chancen, Grenzen und Praxisanforderungen

  • 期刊论文

  • 发表日期：

    2025年11月4日

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  • Jeffrey A. Tuhtan,
  • Bernd Mockenhaupt,
  • Frederic de Schaetzen,
  • Rodrigo W. Issa,
  • Adrien Bertaud,
  • Damien Sidler,
  • Henning Müller,
  • Christian Haas

摘要

Manual processing of fish videos from underwater cameras can be very time-consuming, which currently limits the use of video-based monitoring. Recent advances in computer vision allow artificial intelligence (AI) methods to automatically classify environmental conditions, detect the presence of fish, classify species and estimate their total body length and swimming direction. However, despite the promises of AI to automate these labor-intensive tasks, there remain important technical and practical challenges. In this article, we present key findings, guidelines and limitations for the use of AI for automated monitoring of river fish using underwater camera videos.