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Smart Agriculture: An Approach for Agriculture Management using Recent ICT

机译:智能农业:利用最近ICT的农业管理方法

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Agriculture forms the backbone of a country's economy. Indian GDP mainly depends on agriculture yield growth and their products from these agro-industry. As it largely depends on monsoons, which affects the yield to a huge extend, for which agriculture yield analysis and prediction is the toughest task for different agricultural departments across the country. Other agriculture factors which can affect yield are pests attack, deviation in temperature, soil moisture, nutrient deficiency, global warming etc. As a developing economy, this can severely affect the country's GDP, hence predicting the yield and advising certain important measures to counter the ill effects on the growth of crop are important for a stable and effective contribution to the economy of the country. It can be done by monitoring, analysing, controlling and implementing accurate amount parameters such as required amount of irrigation, in limit use of chemical fertilizers, manure, choosing crop type according to weather, soil type suitability for crop, crop rotation, moisture amount, temperature etc. In our paper, IoT sensors are used for gathering data, and analysis is done to prepare a predictive model. Our model gives comparative analysis from real data and in turn gives a predictive model which predicts from the remarks of different production data with their environmental condition. This model is tested for the effective prediction and the estimate of the agribusiness yield for the different product in Odisha state.
机译:农业形成一个国家经济的骨干。印度国内生产总值主要取决于农业产量增长及其来自这些农业行业的产品。由于它在很大程度上取决于季风,这影响了巨大延伸的产量,其中农业收益率分析和预测是全国各地不同农业部门的最艰难的任务。可能影响产量的其他农业因素是害虫攻击,温度偏差,土壤水分,营养缺陷,全球变暖等作为发展经济,这可能会严重影响国家的国内生产总值,从而预测产量并建议衡量某些重要措施对作物生长的影响对于对国家经济的稳定和有效贡献很重要。它可以通过监测,分析,控制和实施准确的量参数,例如所需的灌溉量,限制使用化肥,粪肥,根据天气选择作物类型,土壤型适合作物,作物旋转,水分量,温度等在我们的论文中,物联网传感器用于收集数据,并进行分析以准备预测模型。我们的模型提供了实际数据的比较分析,又提供了一种预测模型,其预测不同生产数据与环境条件的评论。该模型用于有效预测和Otisha状态不同产品的农业综合性产量的有效预测和估计。

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