Monitoreo de la contaminación del aire en Tucumán utilizando IoT sobre redes wifi
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2024-12-26
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Abstract
El Internet de las Cosas (IoT) es un concepto que se refiere a la interconexión digital de
objetos cotidianos a Internet. Es importante tener en cuenta que el IoT representa la
próxima evolución de Internet y supondrá un enorme salto en su capacidad para reunir,
analizar y distribuir datos que puedan convertirse en información y conocimiento.
El objetivo principal de este proyecto es desarrollar un sistema de medición de la
contaminación del aire mediante sensores IoT conectados a una plataforma para su
visualización. Para ello, se creará una red de sensores para el monitoreo de diferentes
variables ambientales en distintos puntos de interés de Tucumán, desarrollada por el
CIASUR. Esto permitirá identificar las condiciones ambientales en diversos lugares de
la provincia. Se utilizará un sistema ambiental constituido por varios sensores que
medirán variables indicadoras de contaminación o calidad atmosférica. Los dispositivos
desarrollados incluirán la toma de telemetría en tiempo real de la información
proporcionada por los sensores instalados y transmitirán estos datos a la plataforma IoT
implementada.
En esta plataforma, los datos serán procesados y visualizados de una forma amigable
para los usuarios del sistema. El manejo de este software específico por parte de los
investigadores garantiza el aprovechamiento de los datos generados para la
modelización de procesos climáticos y la predicción de comportamientos atmosféricos
The Internet of Things (IoT) is a concept that refers to the digital interconnection of everyday objects to the Internet. It is important to note that IoT represents the next evolution of the Internet and will mark a significant leap in its ability to collect, analyze, and distribute data that can be transformed into information and knowledge. The main objective of this project is to develop an air pollution measurement system using IoT sensors connected to a platform for visualization. To achieve this, a sensor network will be created to monitor various environmental variables at different points of interest in Tucumán, developed by CIASUR. This will allow the identification of environmental conditions in different areas of the province. The system will consist of multiple sensors that will measure variables indicating pollution levels or air quality. The developed devices will include real-time telemetry capture of the information provided by the installed sensors and will transmit this data to the implemented IoT platform. On this platform, the data will be processed and displayed in a user-friendly manner for the system's users. The management of this specific software by the researchers ensures the effective use of the generated data for climate process modeling and atmospheric behavior prediction.
The Internet of Things (IoT) is a concept that refers to the digital interconnection of everyday objects to the Internet. It is important to note that IoT represents the next evolution of the Internet and will mark a significant leap in its ability to collect, analyze, and distribute data that can be transformed into information and knowledge. The main objective of this project is to develop an air pollution measurement system using IoT sensors connected to a platform for visualization. To achieve this, a sensor network will be created to monitor various environmental variables at different points of interest in Tucumán, developed by CIASUR. This will allow the identification of environmental conditions in different areas of the province. The system will consist of multiple sensors that will measure variables indicating pollution levels or air quality. The developed devices will include real-time telemetry capture of the information provided by the installed sensors and will transmit this data to the implemented IoT platform. On this platform, the data will be processed and displayed in a user-friendly manner for the system's users. The management of this specific software by the researchers ensures the effective use of the generated data for climate process modeling and atmospheric behavior prediction.
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