Short Communication: Pollution-and-greenhouse gases measurement system
This paper presents the design, development and preliminary results of a sensor system that georeferences and measures atmospheric variables, polluting gases and particle pollution on ground level and lower troposphere using an unmanned aerial vehicle. The system can measure dioxide and monoxide of...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2018
- Institución:
- Universidad de Medellín
- Repositorio:
- Repositorio UDEM
- Idioma:
- eng
- OAI Identifier:
- oai:repository.udem.edu.co:11407/4895
- Acceso en línea:
- http://hdl.handle.net/11407/4895
- Palabra clave:
- Aircraft navigation
Atmospherically-variable sensing
Particulate matter sensing
Sensor systems
UAV environmental sensing
Air navigation
Antennas
Atmospheric humidity
Greenhouse gases
Troposphere
Unmanned aerial vehicles (UAV)
Aircraft navigation
Atmospherically-variable sensing
Environmental sensing
Particulate Matter
Sensor systems
Pollution
- Rights
- License
- http://purl.org/coar/access_right/c_16ec
Summary: | This paper presents the design, development and preliminary results of a sensor system that georeferences and measures atmospheric variables, polluting gases and particle pollution on ground level and lower troposphere using an unmanned aerial vehicle. The system can measure dioxide and monoxide of carbon, methane, ozone, different-diameter particle pollution, and variables such as temperature, humidity, among others. Data is registered and processed by a microcontroller system, is saved in a SD card and sent to a ground station using an Xtend radiofrequency system. Atmospheric and pollution data is published in real time on a website; reports could be generated. Some tests were performed in Envigado, Antioquia-Colombia, because the special geographic characteristics of this area increase the concentration of polluting gases in Medellín City troposphere. This equipment facilitates terrestrial and aerial measurements because is a compact and versatile device that allows optimizing predictive models of pollutant gases. © 2018 Elsevier Ltd |
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