Development of an accurate automated fish weight and distribution camera for fish farms

养鱼场浪费饲料（占生产成本的60%，《Mowi手册2022》）的原因是过度喂养优势鱼，而对较小的鱼喂食不足（这导致压力、更高的疾病发病率和寄生虫，如海虱）。养殖户试图通过人工随机抽样（每个栏30-40条鱼，在12个笼点）来纠正这种情况，以提供低/平均/高鱼重的指示。苏格兰每年大约有400个养殖场，通常每个养殖场有12个网箱，每立方吨海水可容纳15-17.5公斤鱼（水鱼比为1.5/98.5）。放养密度受到严格管制，因此准确的生物量数据对遵守规定至关重要。通常，养殖场会将较小的鱼分级到一个新的围栏中，以使所有鱼达到所需的收获重量。然而，不准确的数据（由于抽样）导致许多鱼的收获超过或低于要求的重量。超市不会对生产不足或过剩的产品进行补偿。浪费的“消耗”饲料（每吨1300英镑）使农民损失了很大一部分收入（每公斤超过所需重量的成本为4.43英镑，而购买一条鱼的平均成本为40英镑（Kontali 2019））。Vaki的Biomass Daily frame、Akva的Vikas或一些新的人工智能相机（Aquabyte、Optoscale）等工具都试图实现重量估计过程的自动化；但是，整个研究领域的有限可见性导致了误导性的分布数据。虽然农民有更好的工具来跟踪围栏内的平均生长情况，以确保合规，但在准确评估何时对鱼进行分级以防止饲料浪费方面，他们几乎没有什么帮助。Ace的创新技术利用嵌入在360度布局中的多个立体摄像头，提供云测绘和人工智能重量估计的第一个“深度”点，能够跟踪笼中所有部分的鱼，提供高保真的分布精度，以及一个清晰的门户网站，为养鱼提供信息和节省资金。

Fish farms waste feed (60% of production costs, 'Mowi Handbook 2022) by over feeding dominant fish, and underfeeding smaller fish (which leads to stress, higher incidence of disease and parasites, such as sea lice). Farmers attempt to rectify this through manual random sampling (30-40 fish per pen, on 12 cage sites) to provide indications of low/average/high fish weights. There are around 400 live sites in Scotland each year with typically 12 cages per site containing 15-17.5kg of fish per cubic tonnes of seawater (1.5/98.5 water to fish ratio). Stocking density is heavily regulated so accurate biomass data is critical for compliance. Typically a farm will grade out smaller fish into a new pen to bring all fish up to the required harvest weight. However, inaccurate data (due to sampling) leads to many fish being harvested above or below the required weight. Supermarkets do not compensate for under or over production. Wasted 'consumed' feed (at £1300 per tonne) costs farmers a significant proportion of their income (every kilo over the required weight costs £4.43, when the average cost of a fish is bought for £40 (Kontali 2019)). Tools such as Vaki's Biomass Daily frame, Akva's Vikas, or several new AI cameras (Aquabyte, Optoscale) have attempted to automate the weight estimation process; but limited visibility throughout the pen leads to misleading distribution data. While farmers have better tools to track average growth in the pen ensuring compliance, they have little help when accurately assessing when to grade fish to prevent feed waste. Ace's innovation utilises multiple stereo cameras embedded in a 360 arrangement to provide the first 'depth' point of cloud mapping and AI weight estimation, capable of tracking fish in all parts of the cage providing high fidelity distribution accuracy, and a clear portal for informing fish husbandry and saving money.