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Details of Grant 

EPSRC Reference: EP/Y000773/1
Title: Intelligent Dependable Environment Control For Sustainable Aquaculture
Principal Investigator: Liu, Dr P
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Computer Science
Organisation: University of York
Scheme: Standard Research - NR1
Starts: 01 January 2024 Ends: 31 December 2025 Value (£): 162,134
EPSRC Research Topic Classifications:
Environmental biotechnology
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
24 May 2023 ECR International Collaboration Grants Panel 2 Announced
Summary on Grant Application Form
Over the years, changes in the hydrological environment have introduced new issues and challenges to aquaculture and fish farming. Technologies and research programs have been developed to manage these challenges but there is still significant space for improvement. With the world's population on course to reach 9.7 billion by 2050, the global demand for protein is expected to grow by 40%. One way to meet our protein needs is to sustainably maintain both wild fish reserves and farmed fish. However, with pressure on the already over-exploited wild fish reserves, communities in the UK and worldwide, including the UN's Food and Agriculture Organization, are calling for more efficient ways to manage both freshwater and wild fish stocks and the ocean's natural biodiversity. Looking beyond UK's 2030 aquacultural production targets for the main UK species requires urgent consideration of robotics and autonomous systems technologies to deliver increased production without compromising the environment.

The current operations for pond-based or sea-based aquaculture farms are highly dependent on manual labor and close human interactions with the process and cage structures. The functions of existing equipment and apparatus and their dexterity being used in UK's aquaculture industry are limited, particularly in underwater environments. It would help if we provide fish with optimal environmental conditions by maintaining water quality, reducing stress levels, protecting against parasitic outbreaks, and ensuring there is enough food-and developing the technology to do so. The project aims to develop a dependable, cognitive, functionalized robot-assisted aquacultural platform that facilitates environment control and undertakes smart fish-farming operations such as fish feeding, fish monitoring, marine organisms collecting, water quality monitoring and analysis, net/cage cleaning, etc., regardless of the water types (freshwater, seawater) and hydrological environment (ponds, offshore). The project aims to create a new, long-term, sustainable, and strategic partnership between partners and reinforce the theoretical, technical, and practical knowledge and multidisciplinary skills to make crucial contributions to foster UK's ability for reliable design and development of robot-assisted environment control platforms for sustainable growth in aquaculture production to meet UK's 2030 targets. The partnership will collaborate in joint research, partnership building, knowledge transfer and training under the topics of robotics, dependable systems, complex system management and control, ICT, AI and machine learning, data representation and analytics, fishery biotechnology, hybrid modelling and intelligent control and their applications in sustainable aquaculture.
Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.york.ac.uk