Design and implementation of a low-cost CO2 monitoring and control system prototype to optimize ventilation levels in closed spaces

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High concentrations of CO2 levels are significantly present in closed environments that do not have proper ventilation. Such high concentrations generate negative health consequences such as dizziness, headaches and various respiratory problems. For this reason, the design and implementation of a lo...

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Detalles Bibliográficos
Autores: Cavallini Rodriguez, Ramces Andrei, Espinoza Valera, Jesus Alberto Francisco, Sotomayor Beltran, Carlos Alberto
Formato: artículo
Fecha de Publicación:2022
Institución:Universidad Tecnológica del Perú
Repositorio:UTP-Institucional
Lenguaje:español
OAI Identifier:oai:repositorio.utp.edu.pe:20.500.12867/5803
Enlace del recurso:https://hdl.handle.net/20.500.12867/5803
http://doi.org/10.14569/IJACSA.2022.0130363
Nivel de acceso:acceso abierto
Materia:CO2 Monitoring
Ventilation System
Internet of things
https://purl.org/pe-repo/ocde/ford#2.11.03
Descripción
Sumario:High concentrations of CO2 levels are significantly present in closed environments that do not have proper ventilation. Such high concentrations generate negative health consequences such as dizziness, headaches and various respiratory problems. For this reason, the design and implementation of a low-cost CO2 monitoring and control prototype is proposed to optimize ventilation levels in closed spaces. The parameters that the proposed device measures are concentration of carbon dioxide, humidity and temperature. A digital PID controller was implemented, with the use of C++ programming language and an exhaust fan to stabilize carbon dioxide levels within a closed space. The aforementioned parameters can be viewed in two ways: The first way is locally through a LCD screen and LED indicators, and the second one, remotely using the free Arduino IoT Cloud platform. The closed environment was emulated using a cardboard box and in the tests it was obtained that the prototype manages to keep the CO2 concentration levels below the established limit. However, this can be further improved by using more precise sensors for more accurate results. It is expected that this model can be successfully scaled to closed spaces such as classrooms and offices.
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