Using artificial intelligence to combat hydro-meteorological hazards in Africa

Abstract

The rise of hydrometeorological hazards in Africa has caused developmental devastation to the region. This devastation has led to a desperate call for intervention which has involved the likes of artificial intelligence (AI) and other 4.0 technologies. Although AI is a sought-after solution to these hazards, its implementation brings with it many complexities. The likes of which lack research and documentation. Existing research has explored the general use of AI in Africa; however, it neglects stressing hazard specific applications and their ecosystemic complexity. This research aims to explore and present the complexities of AI for reducing hydrometeorological hazards in Africa. It evaluates qualitative data through using a systemic literature review and formulates a network graph using ATLAS.ti.24. The results indicate an inherent mismatch between systemic interactions and the potential output of the phenomenon. For instance, the prominent disparities between the abundance of AI projects and the actual disaster risk reduction results in Africa. Furthermore, the results indicate an increased difficulty in complete comprehension of the system with a persistent gap in fully grasping the impact of AI projects on African hydrometeorological hazards. Consequently, AI for reducing hydrometeorological hazards in Africa is considered a complex adaptive system in need of further research and investigation.