The principal goal of precision fish farming (PFF) is to use data and new technologies such as sensors, cameras, and internet connections to optimise fish-aquaculture operations. PFF improves fish farming operations, making them data-driven, accurate, and repeatable, reducing the effects of subjective choices by farmers. Thus, the daily management of operators based on manual practices and experience is shifted to knowledge-based automated processes. Modern sensors and animal biomarkers can be used to monitor environmental conditions, fish behaviour, growth performance, and key health indicators in real time, generating large datasets at low cost. The use of artificial intelligence provides useful insights from big data. Machine learning and modelling algorithms predict future outcomes such as fish growth, food requirements, or disease risk. The Internet of Things set up networks between connected devices on the farm for communication. Smart management systems can automatically adjust instruments such as aerators or feeders in response to sensor inputs. This integration between sensors, internet connectivity, and the use of automated controls enables real-time precision management.
Edo D’Agaro (2025) studied this question.