孙正义:可持续农业的人工智能自适应移动应用

Ruth Ogubuike, Ashfaq Adib, Rita Orji
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引用次数: 4

摘要

近年来,移动应用程序对我们的日常生活做出了重大的积极贡献。它们大大改善了保健、教育和农业等关键部门的做法。农业部门面临着满足不断增长的粮食需求的压力,同时需要应对农业资源(如水和土壤)缺乏和气候变化问题。此外,还需要研究如何吸引年轻人参与农业,以取代老年农民。这些问题需要开发新的、可持续的农业解决方案。这正是Masa应用试图满足的需求。本文介绍了一个可持续农业的人工智能自适应移动应用程序的设计和实现。该应用程序分为两个部分:市场部分创建了一个买家可以直接与农民联系的平台,资源中心部分利用人工智能的力量为农民提供指导。它还有学习资源,新进入农业部门的人可以在农业领域获得第一手的指导,其中包含他们冒险种植任何选择的产品所需的所有信息。这将有助于减轻新进入或冒险进入农业部门的人面临的一些挑战,从而鼓励更多的人进入农业,从而实现其可持续性。人机交互领域研究人员对应用程序的初步反馈表明,该应用程序有望缩小一般人在农业知识方面的差距,同时强调了一些可以考虑改进应用程序的限制和建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Masa: AI-Adaptive Mobile App for Sustainable Agriculture
Mobile applications have made significant positive contributions to our daily lives in recent years. They have greatly improved practices in critical sectors such as healthcare, education, and agriculture etc. The agricultural sector is under pressure to meet the ever-increasing food demand while needing to deal with lack of agricultural resources (such as water and soil) and climate change issues. There is also a need to figure out how to attract and involve young people in agriculture in order to replace aging farmers. These issues necessitate the development of new, sustainable agricultural solutions. This is the demand that Masa app is attempting to meet. This paper presents the design and implementation of an AI-adaptive mobile app for sustainable agriculture. The app is divided into two sections: the market section which creates a platform where buyers are able to connect with the farmers directly and the resource center section where the power of AI is used to give guidance to the farmers. It also has learning resources where new entrants into the Agric sector can have first-hand walk-through guides in the Agric field containing all the information they need to venture into farming any product of choice. This will help mitigate some of the challenges faced by people who are new or venturing into the agricultural sector thereby encouraging more people to enter agriculture hence its sustainability. Initial feedback on the application from researchers of human-computer interaction domain show the application's promise in closing the gap in farming knowledge among general people while highlighting some limitations and suggestion that can be considered for improving the application.
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