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Improved Fuzzy Rule Promotion-Based Localized Crop Knowledge Dissemination System for Farmers of Punjab (India) Using Mobile Phone Technology

机译:基于改进的基于模糊规则促进的旁遮普邦(印度)农民本地作物知识传播系统

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摘要

Indian economy includes the major contribution provided by agriculturally driven activities. There is need to provide the agricultural stakeholders an appropriate, reliable, local, fast, 'round-the-clock, and precise knowledge, possibly in their native language, in order that they can enhance their decision-making capacity to improve the agricultural productivity. This can be achieved by using mobile phones. Mobile phones are becoming part of the daily routine of farmers and can be used to disseminate this appropriate, multilingual, localized knowledge right at the location of use. In this article, an improved fuzzy rule promotion-based technique to infer advice to farmers has been presented. Using this technique, an Android-based mobile phone application named mAglDS has been developed. This application uses a Global Positioning System (GPS) for localized inference and local language selected by the user. The application was tested on the dataset of a disease diagnosis of a paddy crop. The chi-square (x2) test was used to match the result of the mAglDS system with the experts' inferences. It was found that the results of the system and experts match with an accuracy of 95.84% at a 5% level of significance. Twenty-two scientists, working at various locations within Punjab state in India, were contacted for validation of the system, with 15 relevant parameters. It was found that the proposed system is statistically valid. The real-time implementation of the system provides immense and timely help to the farmers in making appropriate decisions for their crop production.
机译:印度经济包括由农业驱动的活动提供的主要贡献。有必要向农业利益相关者提供适当的,可靠的,本地的,快速的,全天候的和精确的知识(可能以他们的母语),以便他们能够增强决策能力,以提高农业生产力。这可以通过使用手机来实现。移动电话已成为农民日常工作的一部分,可用于在使用地点传播这种适当的多语言本地化知识。在本文中,提出了一种改进的基于模糊规则促进的技术来向农民提供建议。使用这种技术,已经开发了基于Android的手机应用程序,名为mAglDS。此应用程序使用全球定位系统(GPS)来进行用户选择的本地化推断和本地语言。该应用程序已在水稻作物病害诊断数据集上进行了测试。卡方检验(x2)用于将mAglDS系统的结果与专家的推论相匹配。结果发现,系统和专家的结果在5%的显着性水平上具有95.84%的准确度。与印度旁遮普邦内不同地点工作的22位科学家进行了联系,以对系统进行验证,并带有15个相关参数。发现所提出的系统在统计上是有效的。该系统的实时实施为农民制定农作物生产的适当决策提供了巨大而及时的帮助。

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