Implementation of IoT Framework with Data Analysis Using Deep Learning Methods for Occupancy Prediction in a Building
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- Martín Pensado-Mariño & Lara Febrero-Garrido & Pablo Eguía-Oller & Enrique Granada-Álvarez, 2021. "Feasibility of Different Weather Data Sources Applied to Building Indoor Temperature Estimation Using LSTM Neural Networks," Sustainability, MDPI, vol. 13(24), pages 1-15, December.
- Angelique Mukasine & Louis Sibomana & Kayalvizhi Jayavel & Kizito Nkurikiyeyezu & Eric Hitimana, 2023. "Correlation Analysis Model of Environment Parameters Using IoT Framework in a Biogas Energy Generation Context," Future Internet, MDPI, vol. 15(8), pages 1-14, August.
- Diego Lopez-Bernal & David Balderas & Pedro Ponce & Arturo Molina, 2021. "Education 4.0: Teaching the Basics of KNN, LDA and Simple Perceptron Algorithms for Binary Classification Problems," Future Internet, MDPI, vol. 13(8), pages 1-14, July.
- Zhang, Wuxia & Wu, Yupeng & Calautit, John Kaiser, 2022. "A review on occupancy prediction through machine learning for enhancing energy efficiency, air quality and thermal comfort in the built environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
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LSTM; deep learning; prediction analysis; Internet of Things;All these keywords.
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