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The Cloud-to-Edge-to-IoT Continuum as an Enabler for Search and Rescue Operations

Author

Listed:
  • Leonardo Militano

    (School of Engineering, ZHAW Zurich University of Applied Sciences, 8400 Winterthur, Switzerland)

  • Adriana Arteaga

    (INRIA, Lille, 59650 Villeneuve d’Ascq, France)

  • Giovanni Toffetti

    (School of Engineering, ZHAW Zurich University of Applied Sciences, 8400 Winterthur, Switzerland)

  • Nathalie Mitton

    (INRIA, Lille, 59650 Villeneuve d’Ascq, France)

Abstract

When a natural or human disaster occurs, time is critical and often of vital importance. Data from the incident area containing the information to guide search and rescue (SAR) operations and improve intervention effectiveness should be collected as quickly as possible and with the highest accuracy possible. Nowadays, rescuers are assisted by different robots able to fly, climb or crawl, and with different sensors and wireless communication means. However, the heterogeneity of devices and data together with the strong low-delay requirements cause these technologies not yet to be used at their highest potential. Cloud and Edge technologies have shown the capability to offer support to the Internet of Things (IoT), complementing it with additional resources and functionalities. Nonetheless, building a continuum from the IoT to the edge and to the cloud is still an open challenge. SAR operations would benefit strongly from such a continuum. Distributed applications and advanced resource orchestration solutions over the continuum in combination with proper software stacks reaching out to the edge of the network may enhance the response time and effective intervention for SAR operation. The challenges for SAR operations, the technologies, and solutions for the cloud-to-edge-to-IoT continuum will be discussed in this paper.

Suggested Citation

  • Leonardo Militano & Adriana Arteaga & Giovanni Toffetti & Nathalie Mitton, 2023. "The Cloud-to-Edge-to-IoT Continuum as an Enabler for Search and Rescue Operations," Future Internet, MDPI, vol. 15(2), pages 1-18, January.
    • Handle: RePEc:gam:jftint:v:15:y:2023:i:2:p:55-:d:1051355
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