Citas bibligráficas
Echevarria, P., Aguilar, S. (2023). Sistema de monitoreo de contaminación sonora basado en IoT y participación ciudadana como estrategia de inclusión social en un gobierno local [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/669126
Echevarria, P., Aguilar, S. Sistema de monitoreo de contaminación sonora basado en IoT y participación ciudadana como estrategia de inclusión social en un gobierno local [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2023. http://hdl.handle.net/10757/669126
@misc{renati/407820,
title = "Sistema de monitoreo de contaminación sonora basado en IoT y participación ciudadana como estrategia de inclusión social en un gobierno local",
author = "Aguilar Melgarejo, Stephanie Geraldine",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2023"
}
Noise pollution is one of the biggest problems affecting large cities due to the constant increase in the agglomeration of people and services in increasingly narrow spaces and/or the expansion of urban areas as a whole, to which is added the non-observance of environmental awareness guidelines of its citizens. However, these deficiencies are a common factor in Latin American countries, in Peru there are policies to combat noise pollution that, however, constitute weak tools to control and monitor pollution rates. The main technological objective of this project is to propose a real-time noise monitoring system to determine noise pollution levels through the use of noise sensors (on a wireless network infrastructure and the use of technologies such as IoT, Big Data, Cloud Computing and Cybersecurity) and citizen participation (crowdsourcing), which will benefit the city population, allowing the identification of critical points and attention to environmental incidents for the city of Metropolitan Lima. Likewise, the social objective is aimed at mitigating the greater impact on some sectors where certain pathologies (e.g.) associated with people diagnosed with autism spectrum disorder (ASD) occur, making life in the metropolis more inclusive. The solution consists of collecting data from a network of sensors arranged in critical areas of the city; this noise pollution monitoring system should allow the processing and analysis of the data, together with mobile crowdsourcing, which will make it possible to structure noise maps in real time. In turn, this real-time noise monitoring system contributes to the transformation process for the construction of an intelligent, autonomous and sustainable city, as it has the potential to be extrapolated to the entire city territory, that is, towards the achievement of a Smart City.
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