Indoor Air Quality Analysis Using Recurrent Neural Networks: A Case Study of Environmental Variables

Carlos A. Reyes Pérez, Miguel E. Iglesias Martínez (), Jose Guerra-Carmenate, Humberto Michinel Álvarez, Eduardo Balvis, Fernando Giménez Palomares and Pedro Fernández de Córdoba
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Carlos A. Reyes Pérez: Grupo de Modelización Interdisciplinar, InterTech, Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, Camino de Vera, s/n, 46022 València, Spain
Miguel E. Iglesias Martínez: Grupo de Modelización Interdisciplinar, InterTech, Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, Camino de Vera, s/n, 46022 València, Spain
Jose Guerra-Carmenate: Grupo de Modelización Interdisciplinar, InterTech, Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, Camino de Vera, s/n, 46022 València, Spain
Humberto Michinel Álvarez: Grupo de Ingeniería Física, Escuela de Ingeniería Aeronáutica y del Espacio, Universidad de Vigo, Edif. Manuel Martínez Risco, Campus de As Lagoas, 32004 Ourense, Spain
Eduardo Balvis: Departamento de Ingeniería de Sistemas y Automática, Escuela Superior de Ingeniería Informática, Universidade de Vigo, Edificio Politécnico s/n, 32004 Ourense, Spain
Fernando Giménez Palomares: Grupo de Modelización Interdisciplinar, InterTech, Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, Camino de Vera, s/n, 46022 València, Spain
Pedro Fernández de Córdoba: Grupo de Modelización Interdisciplinar, InterTech, Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, Camino de Vera, s/n, 46022 València, Spain

Mathematics, 2023, vol. 11, issue 24, 1-17

Abstract: In the pursuit of energy efficiency and reduced environmental impact, adequate ventilation in enclosed spaces is essential. This study presents a hybrid neural network model designed for monitoring and prediction of environmental variables. The system comprises two phases: An IoT hardware–software platform for data acquisition and decision-making and a hybrid model combining short-term memory and convolutional recurrent structures. The results are promising and hold potential for integration into parallel processing AI architectures.

Keywords: neural network; air quality; environment (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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