Smart Crop Protection System From Animals Using AI

K. Dharanipriya, S. Sathyageetha, K. Sowmia, J. Srinidhi
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Abstract

Animal assaults on crops are one of the main risks to crop production reduction. Crop raiding is one of the most acrimonious disputes as farmed land encroaches on formerly uninhabited areas. Pests, natural disasters, and animal damage pose severe risks to Indian farmers, lowering productivity. Farmers’ traditional tactics are ineffective, and it is not practical to hire guards to watch over crops and keep animals away. Since animal and human safety are equally important, it is crucial to safeguard the crops from harm brought on by creatures without causing any harm, as well as divert the animal. As a result, we employ deep learning to recognize animals that visit our farm utilizing the deep neural network idea, a branch of computer vision, in order to overcome the aforementioned issues and achieve our goal. In this project, we will periodically check in on the entire farm using a camera that will continuously record its surroundings. We are able to recognize when animals are entering with the use of a deep learning model, and then we use an SD card and speaker to play the right sounds to scare them away. The many convolutional neural network libraries and principles that were used to build the model are described in this research.
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使用人工智能的动物智能作物保护系统
动物袭击农作物是农作物减产的主要风险之一。农作物掠夺是最激烈的争端之一,因为耕地侵占了以前无人居住的地区。害虫、自然灾害和动物伤害给印度农民带来了严重的风险,降低了生产力。农民的传统策略是无效的,雇人看守庄稼和驱赶动物是不现实的。由于动物和人类的安全同样重要,因此保护农作物免受生物的伤害而不造成任何伤害,以及转移动物的注意力是至关重要的。因此,我们采用深度学习来识别访问我们农场的动物,利用深度神经网络思想,计算机视觉的一个分支,以克服上述问题并实现我们的目标。在这个项目中,我们将定期检查整个农场,使用一个相机,将持续记录其周围环境。通过使用深度学习模型,我们能够识别动物何时进入,然后我们使用SD卡和扬声器播放正确的声音来吓跑它们。本研究描述了用于构建模型的许多卷积神经网络库和原理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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