Title: Maximization of Agricultural Productivity through Machine Learning and the Internet of Things
Authors: Erick NGINDU BEYA
Volume: 9
Issue: 9
Pages: 17-27
Publication Date: 2025/09/28
Abstract:
This article project explores the potential of Artificial Intelligence (AI) to transform the agricultural sector in developing countries. Faced with persistent challenges such as low yields, post-harvest losses, inefficient resource management, and the impacts of climate change, agriculture in these regions struggles to achieve optimal productivity and efficiency. The study proposes an in-depth analysis of various AI applications including machine learning, computer vision, and agricultural IoT to optimize decision-making, improve crop and livestock management, and enhance the resilience of farming systems. We will consider the design of a methodological framework for integrating AI solutions adapted to local contexts, taking into account infrastructure, data accessibility, and farmers' capabilities. The objective is to demonstrate how AI can not only significantly increase yields and reduce waste, but also foster more sustainable and profitable agriculture, thereby contributing to food security and sustainable economic development.