Monitoring Algae and Zooplankton Growth using Computer Vision and Sensors

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This works aims to monitor algae and Zooplankton growth and be able to accurately determine the physiological status of the cultures autonomously in a Land-based Automated Recirculating Aquaculture (LARA) system. To fully harness the advantages of the LARA system, efficient running of the algae and zooplankton unit is a requirement. To satisfy this, the ability to monitor growth, produce quality growth conditions within each unit needs to be ensured. Development of a software tool to achieve this is needed. Collection of data, its analysis, and interpretation in different stages of both life cycles is essential. Insights from data analysis will be used to inform software development.

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Computer Vision, Data Analysis, Sensors, Aquaculture, Data Science
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