Intelligent Dependable Environment Control For Sustainable Aquaculture

多年来，水文环境的变化给水产养殖和养鱼带来了新的问题和挑战。已经开发了应对这些挑战的技术和研究计划，但仍有很大的改进空间。到2050年，世界人口将达到97亿，全球对蛋白质的需求预计将增长40%。满足我们蛋白质需求的一种方法是可持续地维持野生鱼类和养殖鱼的储备。然而，随着已经过度开发的野生鱼类保护区面临压力，英国和世界各地的社区，包括联合国粮食及农业组织，呼吁采取更有效的方式来管理淡水和野生鱼类资源以及海洋的自然生物多样性。展望英国2030年主要物种的水产养殖生产目标，迫切需要考虑机器人和自主系统技术，以在不损害环境的情况下提高产量。目前池塘或海上水产养殖场的运营高度依赖体力劳动以及与过程和网箱结构的密切人类互动。现有设备和仪器的功能及其在英国水产养殖业中使用的灵活性有限，特别是在水下环境中。如果我们通过保持水质、降低压力水平、防止寄生虫爆发、确保有足够的食物--并开发这样做的技术--为鱼类提供最佳的环境条件，这将是有帮助的。该项目旨在开发一个可靠的、认知的、功能化的机器人辅助水产养殖平台，促进环境控制，并进行智能养鱼作业，如喂鱼、鱼类监测、海洋生物采集、水质监测和分析、网箱清洁等，无论水类型(淡水、海水)和水文环境(池塘、近海)如何。该项目旨在在合作伙伴之间建立一种新的、长期的、可持续的和战略的合作伙伴关系，并加强理论、技术和实践知识以及多学科技能，为培养英国可靠地设计和开发机器人辅助环境控制平台的能力做出重要贡献，以实现英国水产养殖生产的可持续增长，以实现英国2030年的目标。该伙伴关系将在机器人、可靠系统、复杂系统管理和控制、信通技术、人工智能和机器学习、数据表示和分析、渔业生物技术、混合建模和智能控制及其在可持续水产养殖中的应用等主题下，在联合研究、伙伴关系建设、知识转让和培训方面进行合作。

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.