IoT-Based Solar Energy System for Portable Biomedical Devices in Remote Healthcare

Abstract

The increasing demand for portable medical devices in remote and resource-constrained regions has created a critical need for reliable and sustainable energy solutions. This paper presents an IoT-based solar energy system designed to efficiently power portable biomedical devices with enhanced monitoring and optimization capabilities. The proposed system integrates solar energy harvesting, energy storage, and IoT-enabled real-time monitoring to ensure continuous operation. A simulation-based analysis was conducted to evaluate system performance under varying conditions. The solar power generation profile demonstrated a peak output of approximately 800 W at midday, while maintaining an average daily output of around 450 W. The battery state-of-charge (SoC) analysis indicated stable operation within the range of 40% to 100%, ensuring uninterrupted device functionality. Furthermore, a lightweight machine learning regression model was implemented to predict energy consumption, achieving a prediction accuracy of approximately 92% with low error margins. The system efficiency improved from 58% (conventional system) to nearly 76% with IoT integration and further to 84% with machine learning-assisted optimization. The results confirm that the integration of solar energy, IoT, and machine learning significantly enhances energy management, reliability, and sustainability. The proposed system offers a low-cost and scalable solution for powering portable healthcare devices in off-grid and rural environments.