{"id":8557,"date":"2023-07-24T09:31:14","date_gmt":"2023-07-24T09:31:14","guid":{"rendered":"https:\/\/komorebi.ai\/?page_id=8557"},"modified":"2024-01-10T14:59:40","modified_gmt":"2024-01-10T14:59:40","slug":"tun-ai","status":"publish","type":"page","link":"https:\/\/komorebi.ai\/en\/tun-ai\/","title":{"rendered":"TUN – AI"},"content":{"rendered":"
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TUN-AI: Tuna biomass estimation with Machine Learning models trained on oceanography and echosounder FAD data<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Fisheries Research, 2022<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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This study uses data from echo-sounder buoys <\/strong>attached to drifting Fish Aggregating Devices (dFADs) used by tuna purse-seine fisheries to estimate tuna biomass.<\/strong> The researchers combined FAD logbook data, oceanographic data, and echo-sounder buoy data<\/strong> to train and evaluate different Machine Learning models and establish a pipeline, TUN-AI,<\/strong> to process this data.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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A Machine Learning method, TUN-AI, for accurate tuna biomass estimation, benefiting the fishing industry, fishery management organizations, and conservation efforts.<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Where does it apply?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The findings of this study are applicable primarily to the fishing industry, specifically tuna purse-seine fisheries<\/strong> where dFADs and echo-sounder buoys are used. They can utilize this model to more accurately estimate tuna biomass and make informed decisions<\/strong> about fisheries operations.\n

\nThese insights could also be valuable to fishery management organizations, conservation groups, and regulatory bodies, aiding in the development of sustainable fishing policies and practices.<\/strong>\n

\nFurthermore, the methodology may also be relevant to related fields and industries where tracking and estimating biomass or population data of certain species is essential, like wildlife management or environmental study areas.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Why does it matter?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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This study provides a more accurate and reliable method for estimating tuna biomass,<\/strong><\/a> towards a more sustainable fisheries operation.\n

\nBy applying Machine Learning models to various data types (FAD logbook data, oceanographic data, echo-sounder buoy data), the study enhances the potential for gaining valuable insights into tuna behavior and abundance.<\/strong> The methodology can potentially be applied to other fisheries and species,<\/strong> contributing to ocean conservation efforts.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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TUN - AI<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Fisheries Research, 2022<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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V\u00edctor Gallego<\/a>, Alberto Torres<\/a>, David Gordo<\/a>, Manuel Navarro<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Other publications<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Adversarial Machine Learning: Bayesian Perspectives\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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AI in drug development: a multidisciplinary perspective\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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How do tuna schools associate to dFADs? A study using echo-sounder buoys to identify global patterns<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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A Bayesian approach to enhance defense against security threats in Machine Learning systems, applicable across cybersecurity, unsupervised learning and natural language processing.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The review explores the use of AI, particularly Bayesian approaches, in speeding up and reducing the cost of drug development across all stages.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Machine Learning to analyze tuna behavior around Fish Aggregating Devices, providing insights to enhance sustainable fishing, marine biology research and conservation policies.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tGame Theory, Cybersecurity<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tDrug Development, Decision Support<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

TUN-AI Fisheries Research, 2022 Resumen Este estudio utiliza datos de boyas ecosonda fijadas a Dispositivos de Agregaci\u00f3n de Peces a la deriva (dFAD) utilizados por las pesquer\u00edas atuneras para estimar la biomasa de at\u00fan. Los investigadores combinaron datos de los cuadernos de pesca de los dFAD, datos oceanogr\u00e1ficos y datos de boyas ecosonda para entrenar […]<\/p>","protected":false},"author":1,"featured_media":3233,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"yoast_head":"\nTUN - AI - Komorebi AI<\/title>\n<meta name=\"description\" content=\"TUN-AI, un m\u00e9todo de aprendizaje autom\u00e1tico que estima con precisi\u00f3n la biomasa de at\u00fan en beneficio de la industria pesquera.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/komorebi.ai\/en\/tun-ai\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"TUN - AI - Komorebi AI\" \/>\n<meta property=\"og:description\" content=\"TUN-AI, un m\u00e9todo de aprendizaje autom\u00e1tico que estima con precisi\u00f3n la biomasa de at\u00fan en beneficio de la industria pesquera.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/komorebi.ai\/en\/tun-ai\/\" \/>\n<meta property=\"og:site_name\" content=\"Komorebi AI\" \/>\n<meta property=\"article:modified_time\" content=\"2024-01-10T14:59:40+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/komorebi.ai\/wp-content\/uploads\/2022\/08\/pexels-francesco-ungaro-2289409-1-scaled-e1691133981692.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1478\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/komorebi.ai\/es\/tun-ai\/\",\"url\":\"https:\/\/komorebi.ai\/es\/tun-ai\/\",\"name\":\"TUN - 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