Leveraging Artificial Intelligence for Real-Time Carbon Emission Management and Climate Change Resilience Planning in Kenya (Proposals Track)
Alukwe Jones (Kabarak University); Theophilus Owiti (Kabarak University); Mercy Gachoka (Kabarak Univeristy); Peter Rogendo (Kabarak University)
Abstract
As climate change intensifies, reducing carbon emissions has emerged as a critical global objective. Countries like Kenya, which heavily depend on agriculture and pastoral systems, are disproportionately affected by changing climatic conditions. In 2020, Kenya’s Nationally Determined Contribution (NDC) set a target to reduce carbon emissions by 32% by 2030. However, traditional methods for tracking and managing carbon emissions are derailed by inconsistencies, such as data manipulation and lack of real-time monitoring. This project leverages blockchain technology to provide a transparent and reliable platform for tracking CO2 emissions. Additionally, remote sensing and machine learning models will be used to enhance data collection, monitoring, and predicting emissions. The study will be piloted in 16 sugar companies and 16 plastic companies, as they are among the highest carbon emitters in Kenya. The findings from this study will assist the government and industries in planning climate change resilience strategies and adaptation measures.