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Photovoltaic Prototype for Low-Power Device Charging in School Environments

Submitted:

14 January 2026

Posted:

15 January 2026

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Abstract
In recent years, numerous initiatives have aimed to implement renewable energy sources in diverse contexts. This article presents the design and evaluation of a photovoltaic charging station prototype for low-power devices in educational settings. Its foremost innovation is achieved through the integration of IoT technologies for real-time monitoring and optimization, enabling data collection on energy generation, consumption, and environmental conditions, with potential for AI-based processing. The system adopts a modular and scalable design, allowing adaptation to different needs and conditions. The project demonstrates how renewable energy use can be optimized in non-commercial contexts according to environmental factors and energy demand. The system comprises four subsystems: solar energy capture via a photovoltaic panel, current regulation and control, environmental parameter monitoring, and real-time data transmission through advanced communication protocols. Results indicate that the prototype efficiently supports device charging and enables intelligent energy management through IoT integration. Remote access to operational data facilitates real-time decision-making and management optimization. The charging efficiency allows laptops to operate for a one-hour class in off-grid outdoor environments, with up to four hours of battery life under average radiation. Beyond technical outcomes, the project positively impacted student motivation and user engagement, fostering critical thinking, problem-solving, and environmental awareness. In conclusion, this proposal contributes to advancing the intersection of education, sustainability, and technological innovation. Its modular structure, real-time analysis capacity, and educational value make it an adaptable and replicable solution that contributes to a more efficient and sustainable energy model.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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