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    Green internet of things using UAVs in B5G networks: A review of applications and strategies

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    Green internet of things using UAVs in B5G networks A review of applications and strategies.pdf (4.438Mb)
    Date
    2021-06-01
    Author
    Alsamhi, S. H.
    Afghah, Fatemeh
    Sahal, Radhya
    Hawbani, Ammar
    Al-qaness, Mohammed A.A.
    Lee, B.
    Guizani, Mohsen
    ...show more authors ...show less authors
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    Abstract
    Recently, Unmanned Aerial Vehicles (UAVs) present a promising advanced technology that can enhance people life quality and smartness of cities dramatically and increase overall economic efficiency. UAVs have attained a significant interest in supporting many applications such as surveillance, agriculture, communication, transportation, pollution monitoring, disaster management, public safety, healthcare, and environmental preservation. Industry 4.0 applications are conceived of intelligent things that can automatically and collaboratively improve beyond 5G (B5G). Therefore, the Internet of Things (IoT) is required to ensure collaboration between the vast multitude of things efficiently anywhere in real-world applications that are monitored in real-time. However, many IoT devices consume a significant amount of energy when transmitting the collected data from surrounding environments. Due to a drone's capability to fly closer to IoT, UAV technology plays a vital role in greening IoT by transmitting collected data to achieve a sustainable, reliable, eco-friendly Industry 4.0. This survey presents an overview of the techniques and strategies proposed recently to achieve green IoT using UAVs infrastructure for a reliable and sustainable smart world. This survey is different from other attempts in terms of concept, focus, and discussion. Finally, various use cases, challenges, and opportunities regarding green IoT using UAVs are presented.
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85104067439&origin=inward
    DOI/handle
    http://dx.doi.org/10.1016/j.adhoc.2021.102505
    http://hdl.handle.net/10576/35714
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    • Computer Science & Engineering [‎2428‎ items ]

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