Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/113781
Título: An Internet of Thing Architecture Based on Message Queuing Telemetry Transport Protocol and Node-RED: A Case Study for Monitoring Radon Gas
Autores/as: Medina-Perez, A
Sánchez Rodríguez, David Cruz 
Alonso González, Itziar Goretti 
Clasificación UNESCO: 3307 Tecnología electrónica
Palabras clave: IoT architecture
radon gas
MQTT
Node-RED
Fecha de publicación: 2021
Publicación seriada: SMART CITIES
Resumen: This work aims to monitor air quality in places where humans spend most of their time, such as workplaces and homes. Radon gas is a naturally occurring, colourless, odourless and tasteless gas that accumulates in enclosed spaces. It is a radioactive element produced by the decay of its natural parent elements, uranium and thorium, which is harmful to our respiratory system when inhaled. The Internet of Things (IoT) is the key to the problems of contemporary life; we are witnessing an emerging connected world, and these architectures have the potential by using sensors to take data from the physical world, transfer it over the network and store it for further decision making or action. The proposal of this work is based on a radon sensor connected to an IoT device, the Message Queuing Telemetry Transport protocol (MQTT), the Node-RED for managing data flows and a database management system on a web server. The information collected by the sensor is sent by the IoT device to be processed by Node-RED. The obtained data is stored in a database to be represented on a web server. Therefore, this work includes a case study where the technologies involved in the indoor radon gas monitoring system are presented. It is a way to perform radon gas measurements automatically. The final application would allow: displaying radon concentrations on a map with placemarks and updating the information in real-time. The database could record data from other radon sensors that any user wants to associate with this website.
URI: http://hdl.handle.net/10553/113781
ISSN: 2624-6511
DOI: 10.3390/smartcities4020041
Colección:Artículos
Adobe PDF (4,13 MB)
Vista completa

Citas SCOPUSTM   

14
actualizado el 17-nov-2024

Citas de WEB OF SCIENCETM
Citations

8
actualizado el 17-nov-2024

Visitas

69
actualizado el 07-sep-2024

Descargas

282
actualizado el 07-sep-2024

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.