AI-based Leaf Disease Identification Robot using IoT Approach

P. Nagaraj, T. Rajkumar, S. Rakesh, A.Kavya Siva Durga, M. Jyothi, Ch. Guru Sai Nithin
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Abstract

Every area of the global economy has seen great advancements thanks to artificial intelligence, and agronomy is no exception. Modern agricultural farming faces great challenges in the cultivation of healthy crops. The “Internet of Things” is a system made up of actuators, sensors, or both that either directly or indirectly connect devices to the Internet. The development of the Internet of Things (IoT) can be used in smart farming to improve the standard of agriculture. The foundation of the Indian economy, agriculture, contributes to the country's overall economic growth. Yet, because of the usage of antiquated farming technology and the fact that individuals from rural areas now go to urban areas for more lucrative businesses rather than concentrating on agriculture, the obtained productivity is quite low compared to global standards. This artificial intelligence assists in increasing crop productivity and identifies or keeps track of crop illnesses. based on artificial intelligence to identify crop or leaf diseases, a robot or equipment has been created. It distinguishes or categorizes the plant as either disease-affected or unaffected. Image segmentation is a technique used to isolate the specific disease's affected area. This system's classification of diseased leaves offers farmers a better course of action. Faster feature collection, feature extraction, and illness classification methods based on R-CNN identify the disease afflicted.
基于物联网方法的人工智能叶片病害识别机器人
由于人工智能,全球经济的各个领域都取得了巨大的进步,农学也不例外。现代农业在培育健康作物方面面临着巨大的挑战。“物联网”是一个由执行器、传感器或两者组成的系统,它直接或间接地将设备连接到互联网。物联网(IoT)的发展可以应用于智慧农业,提高农业水平。农业是印度经济的基础,对该国的整体经济增长做出了贡献。然而,由于使用过时的农业技术,以及农村地区的个人现在去城市地区从事更有利可图的业务,而不是专注于农业,与全球标准相比,获得的生产力相当低。这种人工智能有助于提高作物产量,并识别或跟踪作物病害。利用人工智能识别农作物或叶片病害的机器人或设备已经诞生。它将植物区分为受疾病影响的或未受疾病影响的。图像分割是一种用于分离特定疾病影响区域的技术。该系统对病叶的分类为农民提供了更好的行动方案。基于R-CNN的更快的特征收集、特征提取和疾病分类方法可以识别所困扰的疾病。
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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