@inproceedings{483f119144764e4ba854bd37fde995c5,
title = "Demo Abstract: Energy-Efficient Aerial Data Aggregation in IoT Networks with WuR",
abstract = "Unmanned aerial vehicles (UAVs) are promoted as efficient enablers for aerial data collection in massive Internet of Things (IoT) networks. In this paper, we develop a UAV-assisted energy-efficient system using the wake-up radio (WuR) technology for on-demand data collection in IoT networks. By leveraging the WuR technology, the IoT devices always operate in low-power sleep mode and only enter the active state to sense and send data when prompted by an external wake-up call (WuC) from the UAV. The developed solution is expected to reduce the energy consumption of IoT devices in hard-to-reach places, thus maintaining a more sustainable operation of the overall network.",
keywords = "Aerial Communication, Internet of Things (IoT), Unmanned Aerial Vehicle (UAV), Wake Up Radio (WuR)",
author = "Mohammed, {Anas S.} and Omar Khalifa and Ali Alhejab and Abdelrahman, {Abdelrahman S.} and Ahmed Al-Radhwan and Hesham Elsawy and Nour Kouzayha and Noha Al-Harthi and Jaafar Elmirghani and Mansoor Hanif and Al-Naffouri, {Tareq Y.}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2023 ; Conference date: 04-07-2023 Through 07-07-2023",
year = "2023",
doi = "10.1109/BlackSeaCom58138.2023.10299765",
language = "English (US)",
series = "2023 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "147--149",
booktitle = "2023 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2023",
address = "United States",
}
