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Link to original content: https://doi.org/10.1007/978-3-319-92639-1_36
A Distributed Drone-Oriented Architecture for In-Flight Object Detection | SpringerLink
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A Distributed Drone-Oriented Architecture for In-Flight Object Detection

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Hybrid Artificial Intelligent Systems (HAIS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10870))

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Abstract

Drones are increasingly being used to provide support to inspection tasks in many industrial sectors and civil applications. The procedure is usually completed off-line by the final user, once the flight mission terminated and the video streaming and conjoint data gathered by the drone were examined. The procedure can be improved with real-time operation and automated object detection features. With this purpose, this paper describes a cloud-based architecture which enables real-time video streaming and bundled object detection in a remote control center, taking advantage of the availability of high-speed cellular networks for communications. The architecture, which is ready to handle different types of drones, is instantiated for a specific use case, the inspection of a telecommunication tower. For this use case, the specific object detection strategy is detailed. Results show that the approach is viable and enables to redesign the traditional inspection procedures with drones, in a step forward between manual operation and full automation.

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Acknowledgements

This work was supported in part by Universidad Politécnica de Madrid Project RP1509550C02, and by the Spanish Ministry of Economy and Competitiveness under Grants TEC2014-57022-C2-1-R and TEC2014-55146-R.

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Correspondence to Diego Vaquero-Melchor .

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Vaquero-Melchor, D., Campaña, I., Bernardos, A.M., Bergesio, L., Besada, J.A. (2018). A Distributed Drone-Oriented Architecture for In-Flight Object Detection. In: de Cos Juez, F., et al. Hybrid Artificial Intelligent Systems. HAIS 2018. Lecture Notes in Computer Science(), vol 10870. Springer, Cham. https://doi.org/10.1007/978-3-319-92639-1_36

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  • DOI: https://doi.org/10.1007/978-3-319-92639-1_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92638-4

  • Online ISBN: 978-3-319-92639-1

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