Diseño de una arquitectura servidora para la gestión de soluciones basadas en Crowdsensing

Abstract

[EN] The monitoring of noise pollution has become an essential requirement for industrialized and developed countries around the world. The traditional way to measure noise pollution is through the use of professional sound level meters, which are expensive and large-sized. Currently, with the emergence of smart mobile devices that are endowed with multiple sensors, a new paradigm has emerged, called crowdsensing, which takes advantage of the ability to detect mobile crowds, becoming a popular field of research and applications. In this work we propose GRCSensing, an environmental monitoring system based on crowdsensing that is able to measure noise pollution. GRCSensing consists of a life cycle of four stages, that is, (i) task creation, (ii) task assignment, (iii) task execution, and (iv) visualization of acoustic contamination information of a specific area in real time. To this aim, the system has been developed with the following resources: a web server that hosts the web platform, and that allows the creation of tasks and visualization of noise pollution levels, as well as mobile devices with Android OS for the collection of environmental noise data. By combining all the aforementioned devices, the transmission and capture of environmental noise data becomes possible. This results in an information system that helps at studying noise pollution in a specific region in a simple and inexpensive way.

En este proyecto se propone el diseño de una arquitectura centrada en el lado del servidor que permita gestionar aplicaciones basadas en Crowdsensing. Concretamente, se diseñará la estructura de la base de datos y la interfaz gráfica que permita al gestor del sistema planificar tareas de Crowdsensing de manera rápida e intuitiva, así como procesar y visualizar los datos resultantes de dicho proyecto. Igualmente el proyecto tratará de solucionar de manera eficiente la distribución de las tareas creadas a los diferentes usuarios de la aplicación, así como la recolección de datos asociados a dichas tareas.