Tasmanian Scientists Develop AI System to Identify Lobsters by Shell Patterns
Scientists in Tasmania, Australia, have developed an artificial intelligence system that uses the unique patterns on a lobster's shell to identify individual animals, aiming to create a digital fingerprint for enhanced traceability and fraud prevention within the seafood supply chain.
Salt Lake City, UT, October 26, 2026 —
Scientists in Tasmania, Australia, have developed an artificial intelligence system designed to identify individual lobsters from patterns on their shells. The system aims to create a digital fingerprint for each animal, with the goal of improving traceability and helping prevent fraud in the seafood supply chain.
The approach relies on shell patterns as identifying features. In principle, linking an individual lobster to a digital record could help distinguish animals as they move through supply-chain processes. The summary provided does not specify what information a record would contain or how the system would be used by seafood businesses.
Details about the research team, the institution involved and when the system was developed were not provided. The summary also does not describe how the AI was trained, whether it has been tested in commercial conditions, or how accurately it identifies lobsters. It does not say whether the system is currently in use or remains under development.
The stated aims are enhanced traceability and fraud prevention. No specific fraud cases, supply-chain stages or types of seafood misrepresentation were identified in the information provided. The system’s expected effects, including whether it has already improved tracking or reduced fraud, were also not reported.
Further details about the technology’s operation and testing would be needed to assess its capabilities and practical application. For now, the reported development is an AI-based identification method that uses individual lobster shell patterns to support a digital-fingerprint approach to seafood traceability.
Story summarized from the original created by Frizz Flake on www.deseret.com, see more information here.
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