This dataset details the energy consumption of appliances in a low-energy building over 4.5 months. Data was collected at 10-minute intervals.
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PPG-DaLiA is a publicly available dataset for PPG-based heart rate estimation. This multimodal dataset features physiological and motion data, recorded from both a wrist- and a chest-worn device, of 15 subjects while performing a wide range of activities under close to real-life conditions. The included ECG data provides heart rate ground truth. The included PPG- and 3D-accelerometer data can be used for heart rate estimation, while compensating for motion artefacts.
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Predictions of energy consumption are crucial for energy retailers to minimize deviations from energy acquired in the day-ahead market and the actual consumption of their customers. The increasing spread of smartmeters means that retailers have access to hourly consumption values of all their contracted customers in realtime. Using machine learning algorithms, these hourly values can be used to calculate predictions for the future energy consumption of the customers. The present data set allows the training and validation of AI-based prediction models.
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The Mauna Loa Seeing Study was performed by the EOL/Integrated Surface Flux System team, capturing surface meteorology and flux products at the Mauna Loa Observatory in Hawaii.
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The USNA long-term scintillation study is a continuing effort to characterize and measure optical turbulence in the near-maritime boundary layer.
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