{
  "id": "AIBD-0198",
  "title": "Observe Technologies' camera AI registers behavioral change when gill disease hits two Scottish salmon farms",
  "summary": "University of Stirling study, 2023 season: fish activity rose from 25.6% to 43.6% (Farm A) and 24.9% to 32.6% (Farm B) after gill health deteriorated; proliferative gill disease drove it.",
  "date_observed": "2023-10-13",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
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  "account": "Researchers at the University of Stirling's Institute of Aquaculture applied Observe's algorithm to feed-camera video at two commercial Atlantic salmon marine farms in Scotland. Co-authors were from Observe Technologies (Richmond, UK), with Innovate UK funding in partnership with Observe and AKVA Group. The algorithm, a patented convolutional neural network (EP3644717), ran on video in every cage, with 5 and 4 extra cameras in one cage per farm. It outputs “activity” (%), combining fish abundance, speed and shoal cohesion. Gill health, operational welfare indicators, mortality and specific feeding rate were scored weekly. Data were collected from 10 May to 10 September 2023 at Farm A and 22 June to 13 October 2023 at Farm B. Gill health issues arose at both farms in summer 2023. Mean activity in the two months before was 25.6 ± 10.5% (A) and 24.9 ± 7.0% (B). It rose for two months after to 43.6 ± 15.1% and 32.6 ± 9.6%, with fish moving to the cage center. A mixed model found proliferative gill disease the main driver. The paper proposes behavior as a non-invasive welfare indicator but reports no alert preceding diagnosis or changed treatment.",
  "category": "general benefit",
  "unexpected": false,
  "purpose": "Extract group behavior (abundance, speed, shoal cohesion) from feed-camera video as a non-invasive indicator of fish health and welfare.",
  "system": "Observe Technologies behavioral monitoring algorithm (patented convolutional neural network, EP3644717)",
  "model_version": null,
  "developer": "Observe Technologies, Richmond, UK",
  "deployer": "Two commercial Atlantic salmon marine farms in Scotland, studied by the University of Stirling",
  "location": null,
  "domain": "Aquaculture / fish welfare",
  "segment": "Atlantic salmon sea cages",
  "benefit_type": "Improved Knowledge Discovery",
  "taxonomy_note": null,
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      "reason": "Gill disease was scored weekly by conventional means. The paper does not report any farm decision changed by the activity signal."
    },
    {
      "group": "personal",
      "depth": null,
      "reason": "No outcome for farm staff or fish welfare beyond the behavioral correlation is documented."
    }
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    "statement": "The vendor's neural network quantified a behavioral response that coincided with gill disease already identified by weekly scoring. The study shows correlation, not an alert that changed what happened. Vendor staff co-authored the peer-reviewed paper."
  },
  "evidence": [
    {
      "kind": "peer-reviewed study",
      "citation": "Burke M, Nikolic D, Fabry P, Rishi H, Telfer T, Rey Planellas S. Precision farming in aquaculture: assessing gill health in Atlantic salmon (Salmo salar) using a non-invasive, AI-driven behavioural monitoring approach in commercial farms. Aquaculture Science and Management 2:15 (2025). doi:10.1186/s44365-025-00020-8",
      "title": "Precision farming in aquaculture: assessing gill health in Atlantic salmon (Salmo salar) using a non-invasive, AI-driven behavioural monitoring approach in commercial farms",
      "url": "https://doi.org/10.1186/s44365-025-00020-8",
      "date": "2025-08-15",
      "written_by": "independent",
      "quote": "After gill health was compromised, the activity rose significantly for two months in all cages with a mean of 43.6 ± 15.1% and 32.6 ± 9.6%, respectively."
    }
  ],
  "replication": {
    "produced_by": [
      "Feed cameras in all cages plus 4–5 extra cameras in one cage per farm",
      "Weekly gill scoring, welfare indicators, mortality and feeding-rate records",
      "A summer 2023 gill-health episode at both farms"
    ],
    "must_hold": [
      "Gill disease severe enough to alter shoaling and distribution",
      "Camera coverage of the cage volume"
    ],
    "echoes": []
  },
  "paired_incident": null,
  "headline": "Observe's AI registers salmon activity rising with gill disease",
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    "status": "unknown",
    "date": null,
    "note": "No later report on the Observe algorithm's use on these or other farms after the 2023 season was found.",
    "quote": null,
    "url": null
  },
  "value": null,
  "developer_country": "United Kingdom",
  "deployer_country": "United Kingdom",
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    {
      "date": "2026-10-21",
      "change": "Country of the developer and the deployer added from the organization's own site or a registry.",
      "source": "https://find-and-update.company-information.service.gov.uk/company/10500815; https://pmc.ncbi.nlm.nih.gov/articles/PMC12369403/",
      "editor": "AIBD"
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      "date": "2026-10-21",
      "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
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}