SeaLens: Autonomous marine robot for seaweed and shellfish aquaculture
SeaLens: Autonomous marine robot for seaweed and shellfish aquaculture
批准号:
10004453
负责人:
金额:
$3.66万
依托单位国家:
英国
项目类别:
Feasibility Studies
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --
中文摘要
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英文摘要
INDUSTRY CHALLENGE:Near-shore coastal waters have highly dynamic physical, chemical and biological environments which can be subject to dramatic changes due to extreme weather, tidal currents and human activities. Monitoring this environment provides crucial information for the effective set-up and management of aquaculture operations. For example, when identifying new aquaculture locations it is essential to first characterise the local marine environment in order to comply with water quality standards, to establish effective mooring designs and to provide a baseline of the environmental conditions.Typical monitoring programs rely on in-situ sampling, where data is temporally sparse and is often irregularly sampled (e.g. dependent on vessel access, weather and tides). On the other hand, semi-permanent monitoring instruments (e.g. on a buoy or mooring) that measure continuously over long periods of time are able to capture temporal variations. However, due to their high capital costs (\> £20k - 1M) few of them exist and the ones that do are almost exclusively used by large organisations (e.g. harbour authorities, research institutes or large-scale aquaculture businesses)SOLUTION: PEBL CIC is developing an affordable (total cost < £2,000) autonomous monitoring system for small and medium sized aquaculture organisations. The system is modular in design and integrates sensors for monitoring various water quality parameters, such as seawater temperature, salinity and pH as well as recording video and images. The data gathered from this system benefits marine aquaculture organisations by:- Minimising mortality of species due to disease, extreme weather and pollution through early-onset detection and response.- Optimising marine-farm siting and design based on understanding of the local environment.- Developing operational strategy through the prediction of biomass, health indicators and market value based on data-driven models. - Enabling the management of sustainability objectives by monitor long-term changes to the local marine environment and biodiversity.The feasibility study will design, build and deploy the system at 5 different aquaculture locations across the UK to test its robustness and the quality of data captured.
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