Application of Artificial Intelligence in Clean Cooking Energy Technologies for Enhancing Access to Carbon Credits in Tanzania

Abstract

This study explores how Artificial Intelligence (AI) can be used to 
improve clean cooking energy technologies in Tanzania, 
particularly in enhancing system performance and supporting 
access to carbon credit markets. The research is based on a 
critical review and comparison of existing studies and real-world 
applications of AI in technologies such as improved biomass 
stoves, biogas systems, and electric cooking devices. It focuses on 
key AI functions, including real-time monitoring, predictive 
maintenance, user behavior analysis, and digital systems for 
measurement, reporting, and verification (MRV). The results show 
that AI can make a practical difference in how these technologies 
operate. For example, real-time monitoring helps improve fuel 
efficiency and reduce emissions by optimizing how stoves are 
used. Predictive maintenance reduces breakdowns and extends 
the lifespan of equipment, while analysis of user behavior 
provides insights that can help reduce the common practice of 
using multiple fuels (fuel stacking). In addition, AI-based MRV 
systems improve the accuracy and transparency of carbon credit 
verification by automating data collection and identifying 
irregularities. Overall, the study finds that AI is not only a 
promising concept but a practical tool that can improve efficiency, 
reduce emissions, and strengthen carbon accounting systems. 
However, challenges such as limited digital infrastructure, high 
costs, and lack of technical expertise may slow down its large
scale adoption in Tanzania. This paper contributes by bringing 
together existing knowledge and presenting a clear, Tanzania
focused perspective on how AI can support the growth of clean 
cooking technologies and access to climate finance.