Indoor Air Quality Analysis Using Recurrent Neural Networks: A Case Study of Environmental Variables-Reference-Cited by-同舟云学术

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

Published:2023-12-05 Issue:24 Volume:11 Page:4872
ISSN:2227-7390
Container-title:Mathematics
language:en
Short-container-title:Mathematics

Author:

Reyes Pérez Carlos A.¹,Iglesias Martínez Miguel E.¹²^ORCID,Guerra-Carmenate Jose¹^ORCID,Michinel Álvarez Humberto²,Balvis Eduardo³^ORCID,Giménez Palomares Fernando¹,Fernández de Córdoba Pedro¹^ORCID

Affiliation:

1. Grupo de Modelización Interdisciplinar, InterTech, Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, Camino de Vera, s/n, 46022 València, Spain

2. 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

3. Departamento de Ingeniería de Sistemas y Automática, Escuela Superior de Ingeniería Informática, Universidade de Vigo, Edificio Politécnico s/n, 32004 Ourense, Spain

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.

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Link

https://www.mdpi.com/2227-7390/11/24/4872/pdf

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