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Monitoring System to Strive against Fall Armyworm in Crops Case Study: Maize in Rwanda

机译:监测系统争取作物中的秋季陆虫案例研究:卢旺达玉米

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The food security has received much attention due the hunger that usually affects some countries in Africa. Pests are very dangerous to crops and reduce the harvest of affected crop and can cause risk if no technical methods are applied to strive against them. Fall armyworm (FAW) is one the pest that has attacked the priority stable crop of Rwanda (maize) since last year 2017. This reduced the expected harvest from this crop. The presence of this pest costs the government to use drones and other special forces to strive for it, but pest will remain a problem if there is no regular, automatic way to detect the pest and strive for it at the early days of attacking the crop. This paper introduces a design of a prototype of an automated system that will be able to detect the presence of a fall armyworm in the field. The system will use the new technology of Internet of Things (IoT) where sensors are used to identify the pest location. Once the presence of the pest is detected in the farm, the system will be able to give the information of the affected crop and notify the farmer through his/her mobile phone who will immediately react accordingly. Through the authorization from the farmer, the system will be able to pump pesticides to kill both larvae and eggs of fall armyworm on the affected crop. This automated system will save the farmer's time, as it will monitor the crops while the farmer is occupied with other activities. Lastly the system will help to increase the production of maize in Rwanda since the crop will be safe from the pest.
机译:粮食安全受到了很多关注,因为通常影响非洲的一些国家。害虫对庄稼非常危险,减少受影响作物的收获,如果没有应用技术方法争取他们,可能会导致风险。秋季武器(一汽)是自去年2017年以来袭击了卢旺达(玉米)优先稳定作物的害虫。这减少了这笔作物的预期收获。这种害虫的存在成本为政府使用无人机和其他特种力量来争取它,但如果没有常规,自动的方式在攻击作物的早期争夺这种害虫并争取它,害虫将仍然是一个问题。本文介绍了一种自动化系统的原型的设计,该原型能够检测到该领域的秋季武器的存在。系统将使用内容的新技术(物联网),其中传感器用于识别害虫位置。一旦在农场发现了害虫的存在,系统将能够提供受影响的作物的信息,并通知农民通过他/她的手机,谁将立即反应。通过农民的授权,该系统将能够泵用杀虫剂杀死受影响的作物的幼虫和秋季植物的鸡蛋。这种自动化系统将挽救农民的时间,因为它将在农民占用其他活动时监控作物。最后,系统将有助于增加卢旺达玉米生产,因为作物从害虫中是安全的。

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