Noise Pollution Control using Internet of Things (IoT) solutions

Main Article Content

Fausto Salazar
Jorge Eduardo Castañeda Alban
Marco Revelo
CESAR LUZA

Abstract

At present, noise is one of the main environmental pollutants that even government agencies are paying attention to find solutions for its control. Noise pollution traditional methods are based on expensive electronic devices—limited to constant monitoring in real-time. In recent years, (IoT), the internet of things diverse strategies, has been proposed to tackle this issue by offering low-cost sensors, capturing and storing real-time data for better decision-making processes. This article presents the results from an exploratory literature revision regarding Noise Pollution solution proposals based on IoT. in 17 articles indexed in a high-impact database with four research questions about the proposed layers, cover for the control of environmental noise, technological elements, and current limitations and gaps in the problem of environmental noise, defining an OiT system of four layers to define the functionalities of monitoring and analysis of noise levels, the review process established stages such as the identification of critical terms, location of literature, evaluating and selecting literature, organizing and finally summarizing the literature review.

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How to Cite
Salazar, F., Castañeda, J., Revelo, . M., & Luza, C. (2023). Noise Pollution Control using Internet of Things (IoT) solutions. INNOVATION & DEVELOPMENT IN ENGINEERING AND APPLIED SCIENCES, 5(1), 13. https://doi.org/10.53358/ideas.v5i1.902
Section
Information and Electronic Engineering
Author Biographies

Jorge Eduardo Castañeda Alban, Universidad Nacional Mayor de San Marcos

Salazar FierroF., CastañedaJ., & Revelo-AldásM. (2022). Modelos predictivos para la estimación de adolescentes con tendencia al alcoholismo. AXIOMA, 1(26), 74-79. https://doi.org/10.26621/ra.v1i26.779

Marco Revelo, Universidad Nacional Mayor de San Marcos

Salazar FierroF., CastañedaJ., & Revelo-AldásM. (2022). Modelos predictivos para la estimación de adolescentes con tendencia al alcoholismo. AXIOMA, 1(26), 74-79. https://doi.org/10.26621/ra.v1i26.779

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