Real-time Visual Analytics for Aquaculture

鉴于人口增长、经济发展和自然资源枯竭等全球共同粮食来源面临的压力，水产养殖在提高营养粮食生产和加强粮食安全方面处于有利地位。虽然自20世纪90年代以来，全球野生捕捞的水产捕捞量基本持平，但水产养殖是一个持续增长的行业，补充了自然来源鱼类生产的停滞不前，从而使普通加拿大人能够负担得起这种高质量的蛋白质来源。然而，获得批准新的水产养殖场址的困难是加拿大的一个严重限制因素，重要的是已批准的场址必须优化以提高生产力。迄今为止，在工业环境中，优化往往是临时的，依赖于现场工人的直觉。行业参与者明确表示希望获得更多实时数据和分析数据的方法，以最大限度地提高产量和降低成本。这需要两方面的努力：开发具有成本效益和时间效益的硬件来收集数据，以及能够可视化和分析收集到的数据的软件。这项工作将集中在可视化分析的设计，实时水产养殖优化。这将涉及界面和可视化的设计，以更好地分析实时水产养殖数据，并发现未知的见解和关系。这反过来将导致产品改进，使农民能够围绕饲料和鱼类健康做出决策。

Given the global pressures on our common food sources including population growth, economic advancementand natural resource depletion, aquaculture is well placed to enhance nutritious food production and bolsterfood security. While the global aquatic harvest through wild capture has essentially flatlined since the 1990's,aquaculture is an industry that has grown continuously, supplementing the stagnation of naturally source fishproduction and thereby keeping this high-quality source of protein within financial reach of ordinaryCanadians. However, the difficulty of gaining approval for new sites for aquaculture is a severe limiting factorin Canada and it is important that those have been approved be optimized for productivity. Thus faroptimization has often been ad hoc in industrial settings and reliant on the intuition of workers in the field.There is a clearly stated desire from industry participants for more real-time data and means of analyzing thatdata to maximize production and minimize costs. This requires a two-fold effort: the development of cost andtime-effective hardware to gather the data and capable software to visualize and analyze the gathered data.This work will focus on the design of visual analytics for real-time aquaculture optimization. This will involvethe design of interfaces and visualizations to better analyze real-time aquaculture data and discover as yetunknown insights and relationships. This in turn will lead to product improvements that will enable farmerscan make decisions around both feeding and fish health.