Automatic Plant Escalation Monitoring System Using IoT

P. Varalakshmi, B. Y. Sivashakthivadhani, B. L. Sakthiram
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引用次数: 2

Abstract

Agriculture plays a crucial role in the Indian economy. It not only provides food and raw material but also provides employment opportunities and also helps in monitoring gas exchange problems, rainfall percolation and microbial activity. Hence it is important to find a technique which will classify infectious plant from healthy plant, in order to cure the diseased plant at early stages and also improve the yield of the agriculture. An hardware model is built using the Raspberry Pi 3 to indicate to the farmer about the temperature, pressure and soil moisture level when it goes below or above a threshold values. A new classification technique is developed based on the convolutional neural network (CNN) to classify infectious plant from the healthy plant and its efficiency is compared with SVM,KNN classifier and random forest.
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使用物联网的自动工厂升级监控系统
农业在印度经济中起着至关重要的作用。它不仅提供食物和原料,还提供就业机会,还有助于监测气体交换问题、降雨渗透和微生物活动。因此,寻找一种将病株与健康株区分开来的技术,对病株的早期治疗和提高农业产量具有重要意义。使用树莓派3建立了一个硬件模型,当温度、压力和土壤湿度低于或高于阈值时,它会向农民指示。提出了一种基于卷积神经网络(CNN)对健康植株和感染植株进行分类的新方法,并与SVM、KNN分类器和随机森林进行了效率比较。
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