Article
Combining Unmanned Aerial Systems and Sensor Networks for Earth Observation
Author/s | Martínez de Dios, José Ramiro
San Bernabé Clemente, Alberto de Viguria, Antidio Torres González, Arturo Eugenio Ollero Baturone, Aníbal |
Department | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática |
Publication Date | 2017-04-01 |
Deposit Date | 2017-06-14 |
Published in |
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Abstract | The combination of remote sensing and sensor network technologies can provide
unprecedented earth observation capabilities, and has attracted high R&D interest in recent years.
However, the procedures and tools used for ... The combination of remote sensing and sensor network technologies can provide unprecedented earth observation capabilities, and has attracted high R&D interest in recent years. However, the procedures and tools used for deployment, geo-referenciation and collection of logged measurements in the case of traditional environmental monitoring stations are not suitable when dealing with hundreds or thousands of sensor nodes deployed in an environment of tenths of hectares. This paper presents a scheme based on Unmanned Aerial Systems that intends to give a step forward in the use of sensor networks for environment observation. The presented scheme includes methods, tools and technologies to solve sensor node deployment, localization and collection of measurements. The presented scheme is scalable—it is suitable for medium–large environments with a high number of sensor nodes—and highly autonomous—it is operated with very low human intervention. This paper presents the scheme including its main components, techniques and technologies, and describes its implementation and evaluation in field experiments |
Funding agencies | Ministerio de Economía y Competitividad (MINECO). España |
Project ID. | info:eu-repo/grantAgreement/MINECO/DPI2014-59383-C2-1-R |
Citation | Martínez de Dios, J.R., San Bernabé Clemente, A.d., Viguria, A., Torres González, A.E. y Ollero Baturone, A. (2017). Combining Unmanned Aerial Systems and Sensor Networks for Earth Observation. Remote sensing, 9 (4), 1-21. |
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