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Computer vision based robotic weed control system for precision agriculture

机译:基于计算机视觉的精准农业机器人除草控制系统

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India is primarily an agriculture-based country and its economy largely depends upon the agriculture. But, most of the crops grown by the farmer are affected by weeds. Weed identification and control remains one of the most challenging tasks in agriculture. The most widely used methods for weed control is manual spraying of herbicides. But, this method has several negative impacts. Since hand labor is costly, an automated weed control system may be economically feasible. Although there have been many efforts to develop a system to control in-row weeds autonomously, no system is currently available for real-time field use. Further, the Onion is slow-growing, shallow-rooted crop that can suffer severe yield loss from weed competition. In order to overcome the above mentioned problems, the proposed system aims to develop a computer vision based robotic weed control system (WCS) for real-time control of weeds in onion fields. This system will be able to identify weeds and selectively spray right amount of the herbicide. The proposed WCS is an inexpensive and portable wireless system of handheld equipments which can be controlled remotely through a user friendly web interface. It is designed to automate the control of weeds and thus reduces the difficulties of farmers in maintaining the field. The proposed system is based on a combination of image processing, machine learning and internet of things (IoT).
机译:印度主要是一个以农业为基础的国家,其经济在很大程度上取决于农业。但是,农民种植的大部分农作物都受到杂草的影响。杂草的识别和控制仍然是农业中最具挑战性的任务之一。控制杂草最广泛使用的方法是手动喷洒除草剂。但是,此方法有几个负面影响。由于手工劳动成本高昂,因此自动化的杂草控制系统在经济上可能是可行的。尽管已经进行了许多努力来开发一种自动控制行内杂草的系统,但是目前还没有用于实时田间使用的系统。此外,洋葱是生长缓慢,根深蒂固的作物,可能因杂草竞争而遭受严重的单产损失。为了克服上述问题,提出的系统旨在开发一种基于计算机视觉的机器人杂草控制系统(WCS),以实时控制洋葱田中的杂草。该系统将能够识别杂草并选择性喷洒适量的除草剂。提出的WCS是一种手持设备的廉价便携式无线系统,可以通过用户友好的Web界面进行远程控制。它旨在自动控制杂草,从而减少农民维护田间的困难。拟议的系统基于图像处理,机器学习和物联网(IoT)的组合。

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