Wireless Communications and Mobile Computing

Unmanned Aerial Vehicle-Enabled Smart Farming: Technologies, Communications and Routing


Publishing date
01 Jan 2021
Status
Closed
Submission deadline
11 Sep 2020

1University of Western Macedonia, Kozani, Greece

2The University of Sheffield International Faculty - CITY College, Sheffield, UK

3University of Peloponnese, Tripolis, Greece

4Kingston University, London, UK

5Cranfield University, Cranfield, UK

This issue is now closed for submissions.
More articles will be published in the near future.

Unmanned Aerial Vehicle-Enabled Smart Farming: Technologies, Communications and Routing

This issue is now closed for submissions.
More articles will be published in the near future.

Description

The rapid evolution of unmanned aerial vehicles (UAVs) can provide useful solutions to several applications, including environmental monitoring, critical infrastructure surveillance, public protection, and smart farming (SF). Further, with the advent of the Internet of Things (IoT), SF has emerged as an integrated approach for effectively managing agricultural activities, leading to a significant reduction in costs along with a notable qualitative and quantitative improvement in agricultural production. SF is one of the most popular and important UAV applications, where UAVs can leverage their power in an efficient and effective way for near real-time image acquisition, high-resolution imagery and low operational costs. However, there are many issues to resolve before UAVs can effectively provide stable and reliable SF applications, such as establishing and maintaining efficient communications either among UAVs or ground stations and IoT nodes.

UAV-enabled SF is conducted and supported efficiently through cutting-edge communication technologies. For instance, air to air wireless communication can be used in cases where there is no infrastructure or when a UAV wants to forward data to a node that is outside its transmission range. On the other hand, air to ground wireless communication is realized when there is a ground station but not all UAVs can communicate with it because of a limited transmission range. The use of relay UAVs is proposed in such cases in order to communicate to ground stations. In addition, important routing issues are raised when multi-UAV systems are considered, as multi-UAV networks can collaboratively complete missions more efficiently and economically when compared to single UAV systems. However, the routing demands of UAV networks go beyond the needs of mobile ad hoc networks (MANETs) and vehicular ad hoc networks (VANETs), given that special routing protocols are required to adapt to their high mobility, dynamic topology, large-scale landscapes, and power constraints.

In recent years, drone swarms have gained the attention of both academia and industry as it is considered a very promising development direction for UAVs. Tasks that are difficult for a single UAV are more efficiently accomplished by numerous, autonomous, and low-cost UAVs which collaborate with each other to achieve a common goal, e.g. to scan a large-scale farming area. Nevertheless, drone swarms face many challenging computation-intensive tasks, such as path planning, pattern recognition, and path optimization.

This Special Issue aims to provide an in-depth, critical contribution to the evolving field of UAV-enabled SF, particularly in terms of cutting-edge communication and routing technologies. We therefore aim to bring together state-of-the-art research and review articles which offer new insights into the applications and benefits of emerging methods and technologies in the UAV-based SF sector.

Potential topics include but are not limited to the following:

  • UAV communications in SF
  • Ground-to-UAV communication in SF
  • Cellular-connected UAV applications for SF
  • Multi-UAV routing issues in large-scale precision agriculture
  • Big data analytics in optimizing the SF process using UAVs
  • MANET, VANET and flying ad hoc network (FANET) applications in SF
  • Swarm of drones in SF
  • Path planning, pattern recognition and path optimization for drone swarms in SF
  • Human-UAV interaction in SF
  • UAV-based edge and fog computing in SF
  • UAV capabilities optimization
  • Security and privacy issues of UAV communications in SF
Wireless Communications and Mobile Computing
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