{"id":623,"date":"2019-03-26T11:36:10","date_gmt":"2019-03-26T10:36:10","guid":{"rendered":"http:\/\/futureeuaqua.eu\/?page_id=623"},"modified":"2021-02-28T18:08:33","modified_gmt":"2021-02-28T17:08:33","slug":"monitoring-technologies","status":"publish","type":"page","link":"https:\/\/futureeuaqua.eu\/index.php\/project\/work-plans\/monitoring-technologies\/","title":{"rendered":"MONITORING TECHNOLOGIES"},"content":{"rendered":"
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MONITORING TECHNOLOGIES <\/h2>

Internet of Things for healthy fish and environment<\/p>\n<\/div>

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The goal of WP5 is to exploit the potential of the Internet of Things<\/strong> (IoT) to address the challenges of a sustainable and resilient aquaculture system that ensures profitability, maintains healthy aquatic ecosystems and strengthens capacity for adaptation to climate change.<\/p>\n

For this purpose, we will develop and implement a real-time wireless communication system to simultaneously monitor the activity and physiology of fish and the main parameters of the environment where they are farmed.<\/p>\n<\/div><\/section>\n

We will monitor the impact of housing environments and innovative diets on fish health and welfare, during large-scale demonstration activities carried out in sustainable breeding and production systems parts, by collecting and integrating Key Performance Indicators<\/strong> (KPIs<\/strong>).<\/p>\n

The specific objectives of\u00a0<\/span>this monitoring are:<\/span>\u00a0<\/span><\/p>\n

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  1. I<\/span>ntegrat<\/span>ing<\/span>\u00a0remote monitoring and signals communication from sensors tracking the activity pattern and physiological status of fish, with co-located instruments \/ sensors that recor<\/span>d the environmental parameters.<\/span>\u00a0<\/span><\/li>\n
  2. C<\/span>ollect<\/span>ing<\/span>\u00a0the main KPIs during large-<\/span>scale demonstration activities.<\/span>\u00a0<\/span><\/li>\n
  3. I<\/span>ntegrat<\/span>ing<\/span>\u00a0several KPIs to make diagnosis, by using P<\/span>reference Modelling techniques.<\/span>\u00a0<\/span><\/li>\n
  4. Collecting<\/span>\u00a0records of KPIs (historical data series in one farm or data set from many farms) to identify patterns and make forecast by using Generalized Linear or Additive Models.\u00a0<\/span>\u00a0<\/span><\/li>\n<\/ol>\n<\/div><\/section>\n
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    \"\"Photo: Kefalonia Fisheries<\/small><\/a>

    Get to know: Kefalonia Fisheries S.A.<\/a><\/h3><\/span><\/header>
    We asked Ms. Evi Abatzidou to tell her story about Kefalonia\u2026<\/div><\/div>