Application of Artificial Intelligence in Clean Cooking Energy Technologies for Enhancing Access to Carbon Credits in Tanzania
タンザニアにおける炭素クレジットへのアクセス向上のためのクリーンクッキングエネルギー技術への人工知能の応用 (AI 翻訳)
Samson Mwakapoma, Bertha Mwaituka, Ally Ngulugulu
🤖 gxceed AI 要約
日本語
本研究は、タンザニアのクリーンクッキング技術にAIを活用し、システム性能向上と炭素クレジット市場へのアクセス改善を検討する。リアルタイム監視、予知保全、行動分析、AIベースのMRVシステムにより、燃料効率向上、排出削減、炭素会計の正確性向上が期待される。課題はデジタルインフラ不足、高コスト、専門知識不足。
English
This study explores the use of AI in clean cooking technologies in Tanzania to improve system performance and access to carbon credits. Key AI functions include real-time monitoring, predictive maintenance, user behavior analysis, and AI-based MRV systems, enhancing fuel efficiency, emission reduction, and carbon accounting accuracy. Challenges include limited digital infrastructure, high cost, and lack of expertise.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
タンザニア事例だが、AIによる炭素クレジットのMRV精度向上はJCMなど日本の二国間クレジット制度にも示唆を与える。途上国での実装課題は日本企業の海外展開にも参考になる。
In the global GX context
This paper provides a developing-country perspective on using AI for clean cooking and carbon credit verification, relevant for global carbon markets and climate finance. The challenges and solutions identified can inform international cooperation and technology transfer.
👥 読者別の含意
🔬研究者:A review synthesizing AI applications in clean cooking and carbon credit systems, identifying key research gaps and practical challenges.
🏢実務担当者:Provides insights on deploying AI-based monitoring and MRV for clean cooking projects to improve carbon credit eligibility and transparency.
🏛政策担当者:Highlights the potential of AI to strengthen carbon credit programs in developing countries, with implications for national climate policies and international finance mechanisms.
📄 Abstract（原文）
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.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.62277/mjrd2026v7i20006first seen 2026-06-18 05:03:38
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