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A Forecasting Model for Monitoring Water Quality in Aquaculture and Fisheries IoT Systems

机译:水产养殖和渔业水质中水质的预测模型及其IOT系统

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Water quality monitoring is an important task when developing IoT systems, especially for aquaculture and fisheries. By monitoring the real-time indicators (e.g., temperature, salinity, pH, Dissolved Oxygen - DO, and Chemical Oxygen Demand - COD) and getting early warning we can manage the quality of the water, thus collecting both quality and quantity in fish raising. In this work, we propose an IoT system for monitoring water quality in aquaculture and fisheries, especially the model for forecasting the quality indicators. Experimental results on two data sets show that the proposed approach can be applied for the real system.
机译:水质监测是在开发IOT系统时的重要任务,特别是对于水产养殖和渔业。通过监测实时指示器(例如,温度,盐度,pH,溶解氧 - DO和化学需氧量 - COD)并获得预警我们可以管理水的质量,从而收集鱼类的质量和数量。在这项工作中,我们提出了一个用于监测水产养殖和渔业水质的物联网系统,特别是预测质量指标的模型。两个数据集的实验结果表明,所提出的方法可以应用于真实系统。

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