Multi-sensor automated water quality monitoring an.. (AQUALITY)
Multi-sensor automated water quality monitoring and control system for continuous use in recirculation aquaculture systems
(AQUALITY)
Start date: Dec 1, 2011,
End date: Nov 30, 2014
PROJECT
FINISHED
EU aquaculture currently produces around 1.3 million tonnes a year, with a value of some EUR 2.9 billion and employs about 65 000 people. This level represents 18 % of EU fish production but only 2 % of world aquaculture production. Catches of wild fish levelled off in the 1980s but between 1973 and 2003 world fish consumption doubled According to FAO estimates 47 % of all fish for human consumption now comes from aquaculture. Between 2000 and 2005, due to growth in Asia and South America, world aquaculture production increased by one third but in the EU it has remained level since 2000.In the EU there are rigorous quality standards to ensure that aquaculture products are fit for human consumption, production is sensitive to the environment and maintenance of wellbeing of the animals is good. High standards bring higher costs, and make it more difficult for our fish farmers to compete with imports from markets that do not adhere to the same standards. Further barriers are access to large quantities to clean unpolluted water, increased competition for the use of space and conservation requirements of the marine environment have to be respected. Recirculated Aquaculture Systems (RAS) use minimal water and allow the farms to be sited anywhere including urban spaces. The technology of RAS systems are not standardised and key components effectively custom built for each development and in addition there is a higher skill level requirement to maintain good husbandry. Expansion of this sector will depend on continued improvements to design and optimisation of both build and operating costs.The AQUAlity project intends to address this through the provision of a standardised open platform technology to lower the cost for fish farmers by developing a multi-sensor unit to measure water quality parameters coupled to an intelligent control system that is automatic and contains built-in knowledge of the farmed species to reduce the skill level required of the fish farmer.
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