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Sustainable Fish Farming: Development of an Integrated monitoring & control system to maximise production and reduce waste


   Environmental Science

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  Dr Gera Troisi, Dr K Banitas  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

AQUA-EYE is an autonomous monitoring platform of ambient conditions in fish farms, for remote alerting of sub-optimal conditions in real-time, to minimise waste and maximise production. The technology provides the critical diagnostic function for an online software tool which is already being developed with cloud data storage. The device will provide fish-farmers with real-time information to inform their decision-making when optimising conditions in their fish farms to maximise fish production. This will help minimise waste and loss of fish stocks. The project will involve design, fabrication for the device followed by marine field trials at fish farms located along the Mediterranean Sea Coast. The project is in collaboration with European Research Institutes and Industrial Partners.

Students with a background in engineering should apply with strengths in Arduino programming, sensors and electronics.

Please specify your lab, software and field skills in your CV and list modules taken and their marks. Detail any previous research projects (e.g. dissertations) including the skills used and the mark achieved.


Funding Notes

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%

How good is research at Brunel University London in Earth Systems and Environmental Sciences?


Research output data provided by the Research Excellence Framework (REF)

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