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Solar panels are frequently used in wireless sensor nodes because they can theoretically provide quite a bit of harvested energy. However, they are not a reliable, consistent source of energy because of the Sun's cycles and the ever-changing weather conditions. Thus, in this paper the authors present a fast, efficient and reliable solar prediction algorithm, namely, Weather-Conditioned Moving Average (WCMA) that is capable of exploiting the solar energy more efficiently than state-of-the-art energy prediction algorithms (e.g. Exponential Weighted Moving Average EWMA).
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