Abstract
The use of small-scale biodigesters is gaining traction in Kenya and Uganda as a clean renewable energy solution. In this paper, we explore how remote monitoring through Internet of Things (IoT) technologies can enhance the service quality of biogas digesters in low-resource settings and promote transparency in carbon accounting. Using data from 121 monitored digesters in Uganda and Kenya, we demonstrate how the analysis of real-time pressure and flow data, coupled with machine learning, can provide an understanding of usage patterns, provide behavioural insights, facilitate the early identification of issues requiring intervention, and give insights into relative digester performance. The tools presented offer a powerful means to study behavioural patterns and the adoption dynamics of biogas as a clean cooking fuel, aligning with national and global aims of broader clean cooking interventions.
Original language | English |
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Article number | 101668 |
Journal | Energy for Sustainable Development |
Volume | 86 |
Early online date | 31 Mar 2025 |
DOIs | |
Publication status | Published - Jun 2025 |
Keywords
- Remote monitoring
- Machine learning
- Biogas
- Clean cooking
- Sustainable development goals
- Sub-Saharan Africa