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Energy management algorithm for solar-powered energy harvesting wireless sensor node for Internet of Things

机译:物联网太阳能能量收集无线传感器节点的能量管理算法

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摘要

The solar powered energy harvesting sensor node is a key technology for Internet of Things (IoT), but currently it offers only a small amount of energy storage and is capable of harvesting only a trivial amount of energy. Therefore, new technology for managing the energy associated with this sensor node is required. In particular, it is important to manage the transmission interval because the level of energy consumption during data transmission is the highest in the sensor node. If the proper transmission interval is calculated, the sensor node can be used semi-permanently. In this study, the authors propose an energy prediction algorithm that uses the light intensity of fluorescent lamps in an indoor environment. The proposed algorithm can be used to accurately estimate the amount of energy that will be harvested by a solar panel using a weighted average for light intensity. Then, the optimal transmission interval is calculated using the amount of predicted harvested energy and residual energy. The results from the authors' experimental testbeds show that their algorithm's performance is better than the existing approaches. The energy prediction error of their algorithm is approximately 0.5%.
机译:太阳能能量收集传感器节点是物联网(IoT)的一项关键技术,但目前它仅提供少量的能量存储,并且仅能收集少量的能量。因此,需要用于管理与此传感器节点关联的能量的新技术。尤其重要的是,管理传输间隔很重要,因为数据传输期间的能耗水平在传感器节点中最高。如果计算出正确的传输间隔,则传感器节点可以半永久使用。在这项研究中,作者提出了一种能量预测算法,该算法利用室内环境中荧光灯的光强度。所提出的算法可用于使用光强度的加权平均值来准确估计太阳能电池板将收集的能量。然后,使用预测的收获能量和剩余能量的数量来计算最佳传输间隔。作者实验实验的结果表明,其算法的性能优于现有方法。他们算法的能量预测误差约为0.5%。

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