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Analyzing UAV-Based Remote Sensing and WSN Support for Data Fusion

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Proceedings of the International Conference on Information Technology & Systems (ICITS 2018) (ICITS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 721))

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Abstract

Recent developments in remote sensing are significantly contributing to exploration and data acquisition through improved efficiency and risk reduction. Unmanned Aerial Vehicles (UAV) are involved in a wide range of remote sensing applications, as they are rapid, efficient and flexible acquisition systems. They represent a valid alternative or a complementary solution to satellite or airborne sensors. Wireless Sensor Networks (WSN), on the other hand, have proliferated significantly in recent years thanks to their timely, cheap and extremely rich data acquisition capacity with respect to other acquisition systems. This paper analyzes current state of the art in UAV-based remote sensing and WSN support for the generation of integrated data. An architecture is proposed for the combination of these technologies and the data acquisition, communication, fusion, and presentation processes are analyzed along with the proposal of future challenges.

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Acknowledgments

These results were supported by UPM’s ‘Programa Propio’, and within the framework of the educational innovation project IE1617.1200, funded by UPM in its 2016–2017 call. Also by the Ministry of Economy and Competitiveness through SEMOLA project (TEC2015-68284-R) and the Autonomous Region of Madrid through MOSI-AGIL-CM project (grant P2013/ICE-3019, co-funded by EU Structural Funds FSE and FEDER). Borja Bordel has received funding from the Ministry of Education through the FPU program (grant number FPU15/03977).

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Correspondence to Ramón Alcarria .

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Alcarria, R., Bordel, B., Manso, M.Á., Iturrioz, T., Pérez, M. (2018). Analyzing UAV-Based Remote Sensing and WSN Support for Data Fusion. In: Rocha, Á., Guarda, T. (eds) Proceedings of the International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-319-73450-7_71

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  • DOI: https://doi.org/10.1007/978-3-319-73450-7_71

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