HARNESSING ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE AGRICULTURE: A COMPREHENSIVE REVIEW OF AFRICAN APPLICATIONS IN SPATIAL ANALYSIS AND PRECISION AGRICULTURE


Obasi S.N., Tenebe V. A., Obasi C.C., Jokthan G.E., Adjei E.A., Keyagha E.R

DOI: 10.26480/bda.01.2024.01.13

ABSTRACT
Artificial Intelligence (AI) has emerged as a transformative tool in the agricultural sector, particularly in spatial analysis and precision farming. This study explores how AI is influencing precision agriculture and spatial analysis, with particular attention to the opportunities and problems that the African agricultural landscape presents. The paper examines the current progress of AI integration and emphasizes the transformative potential of technology in revolutionizing farming practices across all agro-ecological zones in Africa. The project explores adapting precision farming to enhance crop yields, soil health, and mitigate climate change concerns using AI technologies such as sensor-based monitoring and satellite imaging analysis. Examining the socio-economic effects of AI adoption in agriculture in the African context, light is cast on how this technology may promote both economic growth and sustainable development. This research contributes to the knowledge of AI’s revolutionary impact on agricultural practices in Africa by addressing important aspects of precision agriculture and spatial analysis, opening the door for creative, effective, and sustainable farming methods. Using AI to precisely monitor crops, evaluate soil health, and improve decision-making through weather forecasting are some of the main areas of focus. The study looks at the prospects, difficulties, and socioeconomic effects of using AI in agriculture in several agro-ecological zones of Africa. In addition, it offers suggestions for policymakers, lists best practices, and indicates future lines of inquiry to fully utilize AI in advancing resilient and sustainable agriculture across Africa.

KEYWORDS
Precision agriculture, soil health assessment, crop monitoring, sustainable agriculture