Artificial Intelligence (AI) is becoming a veritable tool in promoting environmental sustainability such as water management, energy, land use, remote sensing transportation, biodiversity conservation and disaster management. The integration of Artificial Intelligence and remote sensing tools in monitoring and predicting environmental issues such as landslides at a large–scale is an advantage over any stand-alone technique. Landslides on Mount Patti are common occurrences and there are caused by; slope instability, excess rainfall, deforestation and the presence of fractures at the fridges of the escarpment. The study seeks to design an integrated system of remote sensing, cloud computing, AI algorithm and early warning system used to monitor and predict landslides on mount Patti. The functionality of this system relies on real-time measuring of rainfall which is the most vital trigger of landslides on Patti escarpment. Rainfall data acquired by smart rain gauges are transmitted into a cloud framework hosting the data processing AI algorithm. The final output data are predictions of landslides; this would improve the early warning system for landslide hazards around Patti escarpment.
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