The rise of AI in aquaculture
Artificial intelligence (AI) has become increasingly relevant in aquaculture research and production in recent years – with both startups and established companies developing new AI-based applications for the industry.
AI technology has developed rapidly over the past two decades in many fields, often in ways that can easily be adapted to aquaculture production.
At the same time, sensor technology has advanced by leaps and bounds, as have connectivity options through the Cloud, 5G networks and the internet of things (IoT). As a result, AI is currently being evaluated and deployed in aquaculture for improving feeding efficiency, biomass estimation, growth tracking, early detection of diseases, environmental monitoring and control (especially in RAS) and reduction of labour costs. With modern sensor and processing technologies, many of the routine tasks of modern aquaculture can be performed with much less labor and improved animal welfare conditions.
Costs of components required to elaborate AI systems for fish farming are still relatively high, but cost trends and novel approaches may eventually extend accessibility to even the most resource-limited producers. Underwater cameras or similar sensors to obtain images that are passed on, via the Cloud, to a partner for processing and scoring. Subsequently, the data will be classified and analysed via a trained AI model. With modern connectivity options, turnaround time can be as little as a matter of minutes and several or more farms can be evaluated per day.
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