508 research outputs found
Supporting UAVs with Edge Computing: A Review of Opportunities and Challenges
Over the last years, Unmanned Aerial Vehicles (UAVs) have seen significant
advancements in sensor capabilities and computational abilities, allowing for
efficient autonomous navigation and visual tracking applications. However, the
demand for computationally complex tasks has increased faster than advances in
battery technology. This opens up possibilities for improvements using edge
computing. In edge computing, edge servers can achieve lower latency responses
compared to traditional cloud servers through strategic geographic deployments.
Furthermore, these servers can maintain superior computational performance
compared to UAVs, as they are not limited by battery constraints. Combining
these technologies by aiding UAVs with edge servers, research finds measurable
improvements in task completion speed, energy efficiency, and reliability
across multiple applications and industries. This systematic literature review
aims to analyze the current state of research and collect, select, and extract
the key areas where UAV activities can be supported and improved through edge
computing
Lost in the City? - A Scoping Review of 5G Enabled Location-Based Urban Scenarios
5G mobile network technologies and scenarios with the associated innovations receive growing interest among academics and practitioners. Current literature on 5G technologies discusses several scenarios and specific chances and challenges. However, 5G literature is fragmented and not systematically reviewed. We conducted a scoping review on 5G applications in urban scenarios. We reviewed 1,394 papers and identified 20 studies about urban logistics and emergency indoor localization. Our review accumulates current academic knowledge on these scenarios and identifies six further research directions in four research fields. It reveals several further research opportunities, e.g., regarding trust and privacy concerns. We review and discuss 5G literature for academics and practitioners, contribute towards more tailored 5G research and reflect on cost- efficient 5G applications in urban scenarios
An Innovative Cloud-based Supervision System for the Integration of RPAS in Urban Environments
This paper proposes the outline of a Cloud-based supervision system for Remotely Piloted Aircraft Systems (RPAS), which are operating in urban environments. The novelty of this proposed concept is dual: (i) a Cloud-based supervision system focusing on safety and robustness, (ii) the definition of technical requirements allowing the RPAS to fly over urban areas, as a possible evolution of drone use in future smart cities. A new concept for the regulatory issues is also proposed, compared with existing worldwide regulations. The Cloud framework is intended to be an automated system for path planning and control of RPAS flying under its coverage, and not limited to conventional remote control as if supervised by a human pilot. Future works will be based on the experimental validation of the proposed concept in an urban area of Turin (Italy)
UAV Based 5G Network: A Practical Survey Study
Unmanned aerial vehicles (UAVs) are anticipated to significantly contribute
to the development of new wireless networks that could handle high-speed
transmissions and enable wireless broadcasts. When compared to communications
that rely on permanent infrastructure, UAVs offer a number of advantages,
including flexible deployment, dependable line-of-sight (LoS) connection links,
and more design degrees of freedom because of controlled mobility. Unmanned
aerial vehicles (UAVs) combined with 5G networks and Internet of Things (IoT)
components have the potential to completely transform a variety of industries.
UAVs may transfer massive volumes of data in real-time by utilizing the low
latency and high-speed abilities of 5G networks, opening up a variety of
applications like remote sensing, precision farming, and disaster response.
This study of UAV communication with regard to 5G/B5G WLANs is presented in
this research. The three UAV-assisted MEC network scenarios also include the
specifics for the allocation of resources and optimization. We also concentrate
on the case where a UAV does task computation in addition to serving as a MEC
server to examine wind farm turbines. This paper covers the key implementation
difficulties of UAV-assisted MEC, such as optimum UAV deployment, wind models,
and coupled trajectory-computation performance optimization, in order to
promote widespread implementations of UAV-assisted MEC in practice. The primary
problem for 5G and beyond 5G (B5G) is delivering broadband access to various
device kinds. Prior to discussing associated research issues faced by the
developing integrated network design, we first provide a brief overview of the
background information as well as the networks that integrate space, aviation,
and land
DroneTrack: Cloud-Based Real-Time Object Tracking Using Unmanned Aerial Vehicles Over the Internet
Low-cost drones represent an emerging technology that opens the horizon for new smart Internet-of-Things (IoT) applications. Recent research efforts in cloud robotics are pushing for the integration of low-cost robots and drones with the cloud and the IoT. However, the performance of real-time cloud robotics systems remains a fundamental challenge that demands further investigation. In this paper, we present DroneTrack, a real-time object tracking system using a drone that follows a moving object over the Internet. The DroneTrack leverages the use of Dronemap planner (DP), a cloud-based system, for the control, communication, and management of drones over the Internet. The main contributions of this paper consist in: (1) the development and deployment of the DroneTrack, a real-time object tracking application through the DP cloud platform and (2) a comprehensive experimental study of the real-time performance of the tracking application. We note that the tracking does not imply computer vision techniques but it is rather based on the exchange of GPS locations through the cloud. Three scenarios are used for conducting various experiments with real and simulated drones. The experimental study demonstrates the effectiveness of the DroneTrack system, and a tracking accuracy of 3.5 meters in average is achieved with slow-speed moving targets.info:eu-repo/semantics/publishedVersio
- …