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      • But fully embracing and investing in AI plus automation can significantly produce more seafood to feed the growing world population, while reducing the cost and environmental footprint of aquaculture operations. Done right, AI means fish farmers can earn more and finally have more time to spend with their families.
      thefishsite.com/articles/a-practical-guide-to-using-ai-in-aquaculture
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  2. Jan 27, 2020 · But fully embracing and investing in AI plus automation can significantly produce more seafood to feed the growing world population, while reducing the cost and environmental footprint of aquaculture operations.

  3. Oct 10, 2023 · AI techniques can play a significant role in monitoring the health status of fish in aquaculture settings. By analyzing various data sources and patterns, these techniques can help detect early signs of diseases, assess overall fish health, and enable timely intervention.

  4. Mar 1, 2023 · Artificial intelligence (AI) has become increasingly relevant in aquaculture research and production in recent years – with both startups and established companies developing new AI-based applications for the industry.

  5. Jun 30, 2024 · By creating effective AI models and algorithms, addressing concerns with data sharing, complexity, cost, privacy, and data security, AI can help aquaculture operations become more sustainable and efficient while also providing a stable and secure supply of high-quality seafood for the growing global population.

  6. 1 day ago · Accordingly, startups in the aquaculture sector are using AI technology to help farmers to enhance production and sustainability. Among them is a Canada-based startup called Wittaya Aqua. Its data ...

  7. Mar 8, 2024 · In aquaculture, AI can play a crucial role in various aspects such as precision farming, fish health management, feeding systems, harvesting processes, supply chain optimization, environmental monitoring, data-driven practices, breeding programs, and genetic improvement.

  8. Nov 24, 2021 · For aquaculture, I’ve simplified this into production, fish health and water quality. Feed, mortalities and maintaining water quality are also the largest cost centres for farmers and so no surprise that these are the pain points trying to be solved by AI. Some of the first software for aquaculture was focused on basic digitization.

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