FANET: Smart city mobility off to a flying start with self‐organized drone‐based networks
Journal article
Siddiqi, M.H., Draz, U., Ali, A., Iqbal, M., Alruwaili, M., Alhwaiti, Y. and Alanazi, S. (2021). FANET: Smart city mobility off to a flying start with self‐organized drone‐based networks. IET COMMUNICATIONS. 16 (10), pp. 1209-1217. https://doi.org/10.1049/cmu2.12291
Authors | Siddiqi, M.H., Draz, U., Ali, A., Iqbal, M., Alruwaili, M., Alhwaiti, Y. and Alanazi, S. |
---|---|
Abstract | Due to recent advancements in smart city traffic and transport monitoring industry 4.0 applications. Flying Ad-Hoc Networks (FANETs) ability to cover geographically large areas, makes it a suitable technology to address the challenges faced during remote areas traffic monitoring. The implementation of drone based FANETs have several advantages in remote traffic monitoring, including free air-to-air drone assisted communication zone and smart surveillance and security. The drone-based FANETs can be deployed within minutes without requiring physical infrastructure, making it suitable for mission critical applications in several areas of interests. Here a drone-based FANETs application for smart city remote traffic monitoring is presented while addressing several challenges including coverage of larger geographical area and data communication links between FANETs nodes. A FANET-inspired enhanced ACO algorithm that easily coped with drone assisted technology of FANETs is proposed to cover the large areas. Simulation results are presented to compare the proposed technique against different network lifetime and number of received packets. The presented results show that the proposed technique perform better compared to other state-of-the-art techniques. |
Keywords | Electrical and Electronic Engineering; Computer Science Applications |
Year | 2021 |
Journal | IET COMMUNICATIONS |
Journal citation | 16 (10), pp. 1209-1217 |
Publisher | Institution of Engineering and Technology (IET) |
ISSN | 1751-8628 |
1751-8636 | |
Digital Object Identifier (DOI) | https://doi.org/10.1049/cmu2.12291 |
Publication dates | |
Online | 16 Oct 2021 |
Publication process dates | |
Accepted | 07 Sep 2021 |
Deposited | 29 Oct 2021 |
Publisher's version | File Access Level Open |
License | http://creativecommons.org/licenses/by/4.0/ |
https://openresearch.lsbu.ac.uk/item/8y8x4
Download files
266
total views291
total downloads2
views this month0
downloads this month