Issue |
E3S Web Conf.
Volume 636, 2025
2025 10th International Conference on Sustainable and Renewable Energy Engineering (ICSREE 2025)
|
|
---|---|---|
Article Number | 01003 | |
Number of page(s) | 7 | |
Section | Energy Justice, Education, and Social Impact | |
DOI | https://doi.org/10.1051/e3sconf/202563601003 | |
Published online | 30 June 2025 |
Smart Solar-Powered LED System for Mitigating Energy Poverty-Induced Inequality in Education
Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa
* Corresponding author: omowunmil@uj.ac.za
Energy poverty in rural South Africa negatively impacts the quality of education and academic performance of the learners resident there. This study presents a smart solar-powered LED system integrated with a Dynamic Energy Management System to optimize energy allocation for lighting and study time. It was tested in rural South Africa, where 16.6 million households experience energy poverty. The system leverages machine learning based on weather conditions to predict battery charge times for optimized study time and academic performance. A portable smart LED cube was introduced to ten high school students in Xigalo village, Limpopo province, South Africa, which significantly increased their study time (optimized at 9.46 hours) and improved their academic performance from an average of 52.2% to 66.6%. By harnessing solar energy for lighting and cognitive benefits, this AI-driven solution demonstrates its potential to bridge educational inequalities caused by energy poverty in South Africa and other developing countries.
Key words: Energy poverty / educational inequality / dynamic energy management system / machine learning / Smart Solar-Powered LED System
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.