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Adoption of Artificial Intelligence in Agriculture in the Developing Nations: A Review

Benard Maake


While most developing nations rely largely on rain-fed agriculture and use of traditional mechanisms to mitigate and control emergency crop pests and disease invasion and their effects, global warming has severely affected the agricultural productivity in these regions making them vulnerable to food insecurity. Inadequate extension services and hardly accessible information from agricultural agencies both at the local and national governments has made arable lands in these countries unproductive. In an attempt to address this problem, this paper argues that leveraging digital tools could support the farmers to improve the productivity of their farms amidst the aforementioned challenges. Emerging technologies such as artificial intelligence (AI) and machine learning (ML) enable development of applications that could provide the farmers with timely, accurate and relevant agricultural information needed to support decision-making processes. Thus, this paper sought to establish the role of AI in agriculture in mitigating the challenges faced by farmers in developing nations.

Keywords: Artificial Intelligence (AI), e-agriculture, Information Communication and Technology (ICT), Internet of Things (IoT), Smart Farming, Support Vector Machines (SVM), Unmanned Aerial Vehicles (UAV)