A Study of Identifying Fish Diseases and Analysing Water Quality using AI-enabled Mobile App to Increase Fish Production in Rural Villages through Global Cooperation

沿着435公里的海岸线和新兴的水产养殖部门，柬埔寨拥有大量高产的内陆捕捞渔业和海洋渔业。2018年，内陆和海洋生产加上水产养殖的产量为910,153吨，到2020年将增长近100万吨。通过与柬埔寨皇家政府管理的亚洲愿景研究所（AVI）的TECO 100村项目（VP）合作进行的这项可行性研究；诺丁汉大学和普西斯特拉大学、亨Samrin Thbongkhmum大学、MediprospectsAI提出了人工智能（AI）驱动的游戏化移动应用程序，不仅可以分析社区渔业的水质和鱼类疾病，还可以分析小规模渔业的水质和鱼类疾病——由于缺乏可靠的数据，经常在政策制定中被忽视，在发展社会平等、减少性别差异、可持续资源利用、粮食安全和营养，消除贫困。**实时诊断水质、鱼类病原体分类**和鉴定**处理**应重点关注**图像处理技术和比色试验**。移动应用程序将被游戏化，以确保终端用户积极参与和激励。该项目可在孟加拉国和乌干达等其他最不发达国家复制，因为我们努力通过建设社会和经济复原力以及长期可持续和包容性发展，为实现联合国2030年可持续发展目标做出贡献。该提案的新颖之处在于，它是有史以来第一个通过多类别分类技术嵌入可解释人工智能（XAI）的解决方案，通过定位系统等技术提供智能农业；物联网设备；以及柬埔寨农场的人工智能，特别是池塘和孵化场的鱼。我们的产品将提高鱼类产品的质量和数量，并优化人力劳动，因为村民可以很容易地进入偏远和资源有限的地区，以便及早发现各种疾病。可行性研究应确定相关的风险，同时广泛调查鱼类疾病和水质分析自动诊断能力的技术和操作可行性，以在资源有限的情况下产生社会经济影响，主要是在柬埔寨，很快将在世界其他最不发达国家。

Along its 435-kilometre coastline and emerging aquaculture sector, Cambodia has a substantial and enormously productive inland capture fishery as well as marine fishery. In 2018, inland and marine production combined with aquaculture saw the production of 910,153 tonnes, with growth of close to 1 million tonnes in 2020\.Through this **feasibility study**, in collaboration with TECO 100-Village Project (VP) of the Asia Vision Institute (AVI) - managed by the Royal Government of Cambodia; the University of Nottingham and the University of Puthisastra, University of Heng Samrin Thbongkhmum, MediprospectsAI presents artificial intelligence (AI) powered gamified mobile application to analyse water quality and diseases of fish not only in community fisheries but also small-scale fisheries - often overlooked in policymaking given a lack of reliable data, playing an important role to develop equality in society, reduce gender disparity, sustainable resource utilisation, food security and nutrition, and poverty eradication. **Real-time diagnosis of water quality, classification of fish pathogens** and identification of **treatments** shall focus on **image processing techniques and colourimetric tests**. The mobile application will be gamified to ensure the end-users are actively engaging and motivated.The project is **replicable** in other least developed countries (LDCs) such as Bangladesh and Uganda, as we strive to contribute to the achievements of the United Nations Sustainable Development Goals 2030 by building social and economic resilience and long-term sustainable and inclusive development.The proposal's novelty is the first-ever solution with an explainable AI (XAI) embedded through multi-class classification techniques to offer smart agriculture through technologies like location systems; IoT based devices; and AI on Cambodian farms, especially for fish in ponds and hatchery. Our product shall increase the quality and quantity of fish productions and optimise human labour as villagers will easily access remote and resource-limited areas for early detection of various diseases. The feasibility study shall identify risks associated while extensively investigating technical and operational feasibility of the power of automated diagnosis for fish diseases & water quality analysis to create a socio-economical impact despite limited resources, principally in Cambodia and soon in the remaining LDCs, around the world.