Internet-of-Things-Based CO<sub>2</sub> Monitoring and Forecasting System for Indoor Air Quality Management

Internet-of-Things-Based CO<sub>2</sub> Monitoring and Forecasting System for Indoor Air Quality Management

This study presents a low-cost and scalable CO<sub>2</sub> monitoring system that leverages NDIR sensors and a Long Short-Term Memory (LSTM) neural network to predict indoor CO<sub>2</sub> concentrations over both short- and long-term horizons. The proposed system aims to ant...

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Bibliographic Details
Main Authors: Marya J. Marquez-Zepeda, Ildeberto Santos-Ruiz, Esvan-Jesús Pérez-Pérez, Adrián Navarro-Díaz, Jorge-Alejandro Delgado-Aguiñaga
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Mathematical and Computational Applications
Subjects:
CO<sub>2</sub>
air quality
remote monitoring
forecasting
artificial neural network
Online Access:https://www.mdpi.com/2297-8747/30/2/36
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