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CEYLAGRO: Information Technological Approach for an Optimized and Centralized Agriculiture Platform

机译:CEYLAGRO:优化和集中的农业平台信息技术方法

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Sri Lankan Agriculture sector can be considered as a crucial component as it contributes 18% of country GDP. As native farmers still cling to inapplicable traditional theorems and practices to track customer's vegetable consumption trends, they failed to assure a “good price” for their harvest. Also, the plants are prone to many diseases and pests' attacks which causes loss of the harvest. Unreliable problem identification, poor knowledge on application of fertilizers and pesticides have caused the farmers to lose their profits. As a solution to mitigate these problems, this study has built a computerized system with a vegetable price prediction system and a plant disease, pest identification system. Taking Potato as an example, the parameters of the time series model were analyzed through experiment and has built the price predictor using ARIMA model. Also, with advanced Image processing and CNN techniques Plant disease, pest identifier has built. Desirable results of the entire system have been achieved with more than 94%-97% rate of accuracy. The ultimate goal of this study is to achieve the optimal growth of the sector by navigating the users for a quality and effective decision making by reliable market trends and problem identification.
机译:斯里兰卡农业部门可被视为关键的成分,因为它贡献了18%的国家GDP。由于原住民仍然坚持不适用的传统定理和实践来跟踪客户的蔬菜消费趋势,他们未能确保收获的“优惠”。此外,植物容易出现许多疾病和害虫的攻击,这导致收获损失。不可靠的问题识别,对肥料和农药的应用差的知识使农民失去了利润。作为减轻这些问题的解决方案,本研究已经建立了一种具有蔬菜价格预测系统和植物病虫害识别系统的计算机化系统。以土豆为例,通过实验分析时间序列模型的参数,并使用Arima模型建立了价格预测器。此外,通过先进的图像处理和CNN技术植物疾病,害虫标识符已经构建。整个系统的理想结果已经实现,精度超过94%-97%。本研究的最终目标是通过导航用户通过可靠的市场趋势和问题识别来实现通过导航质量和有效的决策来实现该部门的最佳增长。

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