The live plankton analysis system (LPAS) is a great example of artificial intelligence technology that has been through a commercialisation pipeline successfully in the last 5 years. This talk will cover the commercialisation steps, learnings, and the application of LPAS in the field. Currently, the machine learning model is able to identify algal based taxonomic features and quantify. In the future, it is anticipated that an automated sampling system could be used as a part of the solution to allow regular sampling and counting of algal species.
The use of artificial intelligence reduces the need for skilled labour; improves data integrity and standardises algal identification. There is scope for modelling, combining data with other water quality metrics, and using fish-related data to provide more accurate operational trigger limits. Further investment into this technology may unlock opportunities for identification/monitoring of zooplankton and hydrozoan medusae.