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Acoustic noise monitoring with Low Power Wide Area Networks

Authors: Alrharad, Amine;

Acoustic noise monitoring with Low Power Wide Area Networks

Abstract

[ES] Este trabajo fin de master tiene como objetivo diseñar e implementar un sistema para monitorizar la contaminación acústica utilizando redes de área amplia de baja potencia (LPWAN). Asimismo, vamos a diseñar, implementar y desplegar un indicador de ruido más preciso, adaptado a dispositivos con recursos limitados, como Arduino, para obtener una información más precisa en tiempo real sobre el ruido acústico, que nos ayudará a evaluar la presencia de componentes de baja frecuencia que permite una detección más ajustada a la realidad del grado de molestia que provoca el ruido percibido por las personas. Para ello, se diseñará y desplegará una topología de red con el objetivo de monitorizar la contaminación acústica. En este trabajo de fin de máster vamos a utilizar dos tecnologías: las redes SIGFOX y LoRaWAN, con el objetivo de enviar los indicadores de ruido a nuestro servidor web. Finalmente, vamos a adaptar a nuestros requerimientos el servidor web implementado por el grupo de investigación Ingeniería de Sistemas Telemáticos (TIC-220), para lograr almacenar los indicadores de ruido enviados por los nodos finales (SIGFOX y LoRaWAN) en una base de datos, procesar y visualizarlos para el usuario final. Además, vamos a configurar el servidor web del TIC-220 para que toda la comunicación entre el backend de SIGFOX, el servidor LoRaWAN (TTN) y el servidor web se realice a través del protocolo https en lugar de http.

[EN] This master thesis aims to design and deploy a system to monitor the noise pollution using Low Power Wide Area Networks (LPWANs). Likewise, we are going to design, implement and deploy a more accurate noise indicator, adapted to resource-constrained devices, such as Arduino, in order to obtain a more precise real-time information about acoustic noise, which will help us to evaluate the presence of low frequency components that allows a detection more adjusted to reality of the degree of annoyance caused by the noise perceived by people. For this purpose, a network topology will be designed and deployed aiming to monitor the noise pollution. In this master thesis, we are going to use two technologies: SIGFOX and LoRaWAN networks, with the goal of sending the noise indicators to our web server. Finally, we are going to adapt to our requirements the web server implemented by the Telematics Systems Engineering research group (TIC-220), in order to achieve storing the noise indicators sent by the end nodes (SIGFOX and LoRaWAN) in a database, processing and visualizing them to the end user. As well, we are going to configure the TIC-220’s web server so that all the communication among SIGFOX backend, LoRaWAN server (TTN) and the web server will be done through https protocol instead of http.

Keywords

3325.99, Other (Signal theory), Radiocomunicaciones, Radiocommunications, 3325.05, Otras (Teoría de la señal), Other (Internet of Things), Otras (Internet de las cosas)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green