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A Crop Selection Framework using K Nearest Neighbour for IoT Semantic Interoperability Applications

机译:用于IOT语义互操作性应用的K最近邻居的庄稼选择框架

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In agrosystems, the soil plays a determining role through the multitude of ecosystem services that it provides. Agriculture exploits natural spaces and resources for useful production to humans. Soil is the primary source of nutrients for the plants. The roots absorb nutrient ions from soil and water. Additional nutrients must be mixed in the soil before the cultivation begins. Use of excess chemicals has adverse effects both on the crop and the environment. Optimal amount of nutrient requirement must be met for maximum yield. This paper presents a crop selection criteria based on K-nearest neighbour algorithm. The proposed method used farm inputs like soil type, climate, micronutrients, macronutrients, water source etc. to select the best crop suited for the farm. The algorithm also provides the amount of deficient nutrients required for the crop production. This methodology can be integrated into a semantic interoperability framework for Internet of Things (IoT) based applications. The proposed method accurately estimated the crop needs and the corresponding quantity of the nutrient necessary and sufficient to achieve a production objective defined by the yield.
机译:在农业系统中,土壤通过它提供的众多生态系统服务起到了确定作用。农业利用自然空间和资源来对人类的有用生产。土壤是植物营养素的主要来源。根部吸收土壤和水的营养离子。在培养开始之前,必须在土壤中混合额外的营养物。使用过量的化学品在作物和环境中具有不利影响。必须满足最佳产量的最佳营养需求。本文介绍了基于k最近邻算法的作物选择标准。所提出的方法使用土壤类型,气候,微量营养素,MACRONRICE,水源等的农场投入,为适合农场的最佳作物。该算法还提供了作物生产所需的缺乏营养素的量。该方法可以集成到基于Internet(IoT)的应用程序的语义互操作性框架中。所提出的方法精确地估计了作物需求和相应的营养量,必需的营养量和足以实现由产率定义的生产目标。

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