在撒哈拉以南非洲开发基于物联网云的智能农业平台,并实施智能灌溉作为测试案例

S. Okoh, E. N. Onwuka, Bala Alhaji Salihu, S. Zubairu, P. Dibal, E. Nwankwo
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摘要

联合国经济和社会事务部预测,到2050年,世界人口将增加20亿,其中超过50%来自撒哈拉以南非洲(SSA)。考虑到该区域的贫困和粮食不安全程度,迫切需要可持续地增加农产品。然而,该地区的耕作方式主要是传统的。传统农业的特点是劳动力成本高,产量低,农业投入不足/供过于求。所有这些因素使得农业对许多人没有吸引力。宽带、物联网(IoT)、云计算和大数据分析等数字技术的使用有望提高农业投资的回报,甚至可能使农业对年轻人产生吸引力。然而,智能农业的初始成本可能很高。因此,开发一个专用的基于云的物联网平台势在必行。然后农民们就可以在这个平台上订阅并管理他们的农场。应该指出的是,SSA的大多数农民都是小农,他们贫穷,没有受过教育,生活在农村地区,但生产了大约80%的粮食。他们主要使用不支持互联网的2G手机。任何为这一群体服务的功能物联网平台的设计都必须考虑到这些特性。本文介绍了该平台的开发过程,并在玉米作物智能灌溉试验台上进行了试验。除了智能系统提供的便利之外,与传统的灌溉方式相比,它记录了超过36%的灌溉节水。
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Development of IoT Cloud-based Platform for Smart Farming in the Sub-saharan Africa with Implementation of Smart-irrigation as Test-Case
UN Department of Economics and Social Affairs predicted that the world population will increase by 2 billion in 2050 with over 50% from the Sub-Saharan Africa (SSA). Considering the level of poverty and food insecurity in the region, there is an urgent need for a sustainable increase in agricultural produce. However, farming approach in the region is primarily traditional. Traditional farming is characterized by high labor costs, low production, and under/oversupply of farm inputs. All these factors make farming unappealing to many. The use of digital technologies such as broadband, Internet of Things (IoT), Cloud computing, and Big Data Analytics promise improved returns on agricultural investments and could make farming appealing even to the youth. However, initial cost of smart farming could be high. Therefore, development of a dedicated IoT cloud-based platform is imperative. Then farmers could subscribe and have their farms managed on the platform. It should be noted that majority of farmers in SSA are smallholders who are poor, uneducated, and live in rural areas but produce about 80% of the food. They majorly use 2G phones, which are not internet enabled. These peculiarities must be factored into the design of any functional IoT platform that would serve this group. This paper presents the development of such a platform, which was tested with smart irrigation of maize crops in a testbed. Besides the convenience provided by the smart system, it recorded irrigation water saving of over 36% compared to the control method which demonstrates how irrigation is done traditionally.
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