743 research outputs found
Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0
Within the context of Industry 4.0, mobile robot systems such as automated
guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major
areas challenging current communication and localization technologies. Due to
stringent requirements on latency and reliability, several of the existing
solutions are not capable of meeting the performance required by industrial
automation applications. Additionally, the disparity in types and applications
of unmanned vehicle (UV) calls for more flexible communication technologies in
order to address their specific requirements. In this paper, we propose several
use cases for UVs within the context of Industry 4.0 and consider their
respective requirements. We also identify wireless technologies that support
the deployment of UVs as envisioned in Industry 4.0 scenarios.Comment: 7 pages, 1 figure, 1 tabl
Connecting Disjoint Nodes Through a UAV-Based Wireless Network for Bridging Communication Using IEEE 802.11 Protocols
Cooperative aerial wireless networks composed of small unmanned aerial vehicles(UAVs) are easy and fast to deploy and provide on the fly communication facilities in situations where part of the communication infrastructure is destroyed and the survivors need to be rescued on emergency basis. In this article, we worked on such a cooperative aerial UAV-based wireless network to connect the two participating stations. The proposed method provides on the fly communication facilities to connect the two ground stations through a wireless access point (AP) mounted on a UAV using the IEEE 802.11a/b/g/n. We conducted our experiments both indoor and outdoor to investigate the performance of IEEE 802.11 protocol stack including a/b/g/n. We envisioned two different cases: line of sight (LoS) and non-line of sight (NLoS). In LoS, we consider three different scenarios with respect to UAV altitude and performed the experiments at different altitudes to measure the performance and applicability of the proposed system in catastrophic situations and healthcare applications. Similarly, for NLoS, we performed a single set of experiments in an indoor environment. Based on our observations from the experiments, 802.11n at 2.4 GHz outperforms the other IEEE protocols in terms of data rate followed by 802.11n at 5 GHz band. We also concluded that 802.11n is the more suitable protocol that can be practiced in disastrous situations such as rescue operations and healthcare applications
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Robust, Resilient Networked Communication in Challenged Environments
In challenged environments, digital communication infrastructure may be difficult or even impossible to access. This is especially true in rural and developing regions, as well as in any region during a time of political or environmental crisis. We advance the state of the art in wireless networking and security to design networks and applications that rapidly assess changing networking conditions to restore communication and provide local situational awareness. This dissertation examines new systems for responding to current and emerging needs for wireless networks. This work looks across the wireless ecosystem of widely deployed standards. We develop new tools to improve network assessment and to provide robust and reliable network communication. By incorporating new technological breakthroughs, such as the wide commercial success of Unmanned Aircraft Systems (UAS), we introduce novel methods and systems for existing wireless standards for these challenged networks. We assess how existing technologies and standards function in difficult environments: lacking end-end Internet connectivity, experiencing overload or other resource constraints, and operating in three dimensional space. Through this lens, we demonstrate how to optimize networks to serve marginalized communities outside of first world urban cities and make our networks resilient to natural and political crisis that threaten communication
UAV-Aided Interference Assessment for Private 5G NR Deployments: Challenges and Solutions
Industrial automation has created a high demand for private 5G networks, the
deployment of which calls for an efficient and reliable solution to ensure
strict compliance with the regulatory emission limits. While traditional
methods for measuring outdoor interference include collecting real-world data
by walking or driving, the use of unmanned aerial vehicles (UAVs) offers an
attractive alternative due to their flexible mobility and adaptive altitude. As
UAVs perform measurements quickly and semiautomatically, they can potentially
assist in near realtime adjustments of the network configuration and
fine-tuning its parameters, such as antenna settings and transmit power, as
well as help improve indoor connectivity while respecting outdoor emission
constraints. This article offers a firsthand tutorial on using aerial 5G
emission assessment for interference management in nonpublic networks (NPNs) by
reviewing the key challenges of UAV-mounted radio-scanner measurements.
Particularly, we (i) outline the challenges of practical assessment of the
outdoor interference originating from a local indoor 5G network while
discussing regulatory and other related constraints and (ii) address practical
methods and tools while summarizing the recent results of our measurement
campaign. The reported proof of concept confirms that UAV-based systems
represent a promising tool for capturing outdoor interference from private 5G
systems.Comment: 7 pages, 4 figure
A Review on IoT Deep Learning UAV Systems for Autonomous Obstacle Detection and Collision Avoidance
[Abstract] Advances in Unmanned Aerial Vehicles (UAVs), also known as drones, offer unprecedented opportunities to boost a wide array of large-scale Internet of Things (IoT) applications. Nevertheless, UAV platforms still face important limitations mainly related to autonomy and weight that impact their remote sensing capabilities when capturing and processing the data required for developing autonomous and robust real-time obstacle detection and avoidance systems. In this regard, Deep Learning (DL) techniques have arisen as a promising alternative for improving real-time obstacle detection and collision avoidance for highly autonomous UAVs. This article reviews the most recent developments on DL Unmanned Aerial Systems (UASs) and provides a detailed explanation on the main DL techniques. Moreover, the latest DL-UAV communication architectures are studied and their most common hardware is analyzed. Furthermore, this article enumerates the most relevant open challenges for current DL-UAV solutions, thus allowing future researchers to define a roadmap for devising the new generation affordable autonomous DL-UAV IoT solutions.Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED431C 2016-047Xunta de Galicia; , ED431G/01Centro Singular de Investigación de Galicia; PC18/01Agencia Estatal de Investigación de España; TEC2016-75067-C4-1-
A drone-based networked system and methods for combating coronavirus disease (COVID-19) pandemic.
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. It is similar to influenza viruses and raises concerns through alarming levels of spread and severity resulting in an ongoing pandemic worldwide. Within eight months (by August 2020), it infected 24.0 million persons worldwide and over 824 thousand have died. Drones or Unmanned Aerial Vehicles (UAVs) are very helpful in handling the COVID-19 pandemic. This work investigates the drone-based systems, COVID-19 pandemic situations, and proposes an architecture for handling pandemic situations in different scenarios using real-time and simulation-based scenarios. The proposed architecture uses wearable sensors to record the observations in Body Area Networks (BANs) in a push-pull data fetching mechanism. The proposed architecture is found to be useful in remote and highly congested pandemic areas where either the wireless or Internet connectivity is a major issue or chances of COVID-19 spreading are high. It collects and stores the substantial amount of data in a stipulated period and helps to take appropriate action as and when required. In real-time drone-based healthcare system implementation for COVID-19 operations, it is observed that a large area can be covered for sanitization, thermal image collection, and patient identification within a short period (2 KMs within 10 min approx.) through aerial route. In the simulation, the same statistics are observed with an addition of collision-resistant strategies working successfully for indoor and outdoor healthcare operations. Further, open challenges are identified and promising research directions are highlighted
A Survey on Cellular-connected UAVs: Design Challenges, Enabling 5G/B5G Innovations, and Experimental Advancements
As an emerging field of aerial robotics, Unmanned Aerial Vehicles (UAVs) have
gained significant research interest within the wireless networking research
community. As soon as national legislations allow UAVs to fly autonomously, we
will see swarms of UAV populating the sky of our smart cities to accomplish
different missions: parcel delivery, infrastructure monitoring, event filming,
surveillance, tracking, etc. The UAV ecosystem can benefit from existing 5G/B5G
cellular networks, which can be exploited in different ways to enhance UAV
communications. Because of the inherent characteristics of UAV pertaining to
flexible mobility in 3D space, autonomous operation and intelligent placement,
these smart devices cater to wide range of wireless applications and use cases.
This work aims at presenting an in-depth exploration of integration synergies
between 5G/B5G cellular systems and UAV technology, where the UAV is integrated
as a new aerial User Equipment (UE) to existing cellular networks. In this
integration, the UAVs perform the role of flying users within cellular
coverage, thus they are termed as cellular-connected UAVs (a.k.a. UAV-UE,
drone-UE, 5G-connected drone, or aerial user). The main focus of this work is
to present an extensive study of integration challenges along with key 5G/B5G
technological innovations and ongoing efforts in design prototyping and field
trials corroborating cellular-connected UAVs. This study highlights recent
progress updates with respect to 3GPP standardization and emphasizes
socio-economic concerns that must be accounted before successful adoption of
this promising technology. Various open problems paving the path to future
research opportunities are also discussed.Comment: 30 pages, 18 figures, 9 tables, 102 references, journal submissio
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