Automated Shellfish Species, Size and Sex Identification System (AS3ID) (RD062)


This project aims to modify a prototype device which automatically identifies the species, size and sex of brown crabs and lobsters, so that it can be deployed on various types of fishing vessels. This will enable collecting verifiable data that could feed into stock assessments and more localised future fisheries management.

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The AS3ID or “Automated Species, Sex and Size Identification Device” is a scanning system designed to use industrial imaging technology to revolutionise the way that data to inform the management of shellfish stocks is generated. Measurements of shellfish such as lobsters, crabs and scallops are currently taken manually and this data is then used to understand the status of the populations being fished and ultimately to inform fisheries management. Collecting this data is time consuming and expensive. The AS3ID is being developed to automate the collection of these measurements. Using a combination of a high-definition light camera and a laser line scanner, the device can record detailed 3D images of individual specimens on a conveyor belt. The images can then be processed using artificial intelligence to indicate the species, sex and various size measurements of each specimen that is scanned. Whilst this technology has been used in factory settings, applying it for use with live shellfish and potentially on a 10m length fishing vessel presents significant challenges. A team led by the University of St Andrews including Envisage Systems Ltd and SeaScope have worked together to develop the AS3ID. The original prototype was developed under the Scottish Inshore Fisheries Integrated Data System project. Seafood Innovation Funding has supported a significant advance in the design and operational capability of the system. Further field trials and data collection will take place over the next year to optimise the performance of the system and complete development of the artificial intelligence to automatically process the data.

STATUS: Completed

Project Lead

University of St Andrews