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为降低南美白对虾养殖风险,提高其疾病诊断与防治水平,将多种传感器在线采集的对虾养殖生态环境数据、3G手机获取的疾病图片和疾病诊治经验等多种数据进行融合,采用基于案例推理和规则推理相集成的混合推理、粗糙集融合多分类支持向量机、图像处理等多种方法,研制了基于物联网的南美白对虾疾病远程智能诊断系统。在浙江、广东等省对虾养殖区域进行现场验证,试验结果表明:该系统不仅实现了远程监测对虾养殖生态环境数据、对虾疾病图像、诊治经验数据和诊治推理规则等知识管理功能,还能够在多种数据融合的基础上,实现对虾疾病远程智能诊断与防治、疾病预警等功能。
In order to reduce the risk of P. vannamei breeding and improve the diagnosis and control of its diseases, a variety of data such as ecological environment data of shrimp farming collected online by various sensors, disease pictures acquired by 3G mobile phones and experience of disease diagnosis and treatment were merged. Based on case-based reasoning And rule-based reasoning, hybrid inference, Rough set fusion multi-class support vector machine, image processing, and other methods to develop a remote intelligence diagnosis system based on Internet of things. The results showed that the system not only realized the knowledge management functions of remote monitoring of shrimp culture ecological environment data, shrimp disease images, diagnosis and treatment experience data and diagnosis and treatment inference rules, but also in the multi Based on data fusion, remote intelligent diagnosis and prevention of shrimp diseases, disease warning and other functions.