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UAV-Based Technology for IoT
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UAV-Based Technology for IoT

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 26260

Special Issue Editors

Dr. Emmanouel T. Michailidis

E-Mail Website
Guest Editor
Adjunct Lecturer, Department of Electrical and Electronics Engineering, University of West Attica, Ancient Olive Grove Campus, 250 Thivon & P. Ralli Str, 12241 Egaleo, Greece
Interests: UAV-based communications; wireless and satellite communications; software-defined radio (SDR); Internet of Things (IoT); physical-layer security (PLS); machine learning (ML)
Special Issues, Collections and Topics in MDPI journals
Dr. Petros Bithas

E-Mail Website
Guest Editor
Department of Digital Industry Technologies, National and Kapodistrian University of Athens, 157 72 Athens, Greece
Interests: wireless communication systems; wireless channel modeling; performance analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As ubiquitous connectivity and long-range radio coverage are required in many emerging Internet of Things (IoT) applications in multidisciplinary fields, supplementing and extending the terrestrial and satellite communication infrastructure is of paramount importance. In this respect, unmanned aerial vehicles (UAVs) are a promising candidate technology for attaining highly reliable and effective connections between sensors and data collection points at high elevation angles and across urban, suburban, and rural terrains.

Nevertheless, there exist several scientific and technical challenges for enabling the successful and long-term operation of UAV-based IoT for both massive machine type communications (mMTC)-based and ultra-reliable/low-latency communications (URLLC)-based delay-sensitive scenarios. To meet the mMTC and URLLC presuppositions in highly dynamic and heterogeneous environments, where the UAVs act as autonomous communicating nodes or aerial relays, advanced sensor, antenna, communication, networking, and computing technologies should be proposed, revised, and developed.

This ambiguous landscape regarding UAVs and IoT has motivated the present Special Issue, whose aim is to introduce current research activities and prospective solutions towards the evolution of UAV-based IoT technologies. Therefore, potential authors are invited to submit original research articles or surveys, new developments, and substantial experimental works. Topics of interest include (but are not limited to) the following:

  • Sensor and actuator technologies
  • Navigation, detection, and localization systems
  • Network architectures and protocols
  • Channel modeling and measurement
  • Wireless communication technologies, e.g., mmWave, massive multiple input multiple output (MIMO), non-orthogonal multiple access (NOMA), free-space optical (FSO)
  • Interference and resource management
  • Energy harvesting and wireless power transmission
  • Trajectory optimization
  • Mobile edge computing (MEC)
  • Software-defined radio (SDR), software-defined networking (SDN), and network function virtualization (NFV)
  • Machine learning and deep learning methods
  • Safety, security, and privacy issues
  • Prototype results, testbeds, and new applications

Dr. Emmanouel T. Michailidis
Dr. Petros Bithas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • 5G
  • Internet of Things
  • UAV networks
  • ultra-reliable and low-latency communications (URLLC)
  • massive machine type communications (mMTC)
  • mobile-edge computing (MEC)
  • machine learning
  • network function virtualization (NFV)
  • software-defined networking (SDN)
  • sensors

Published Papers (5 papers)

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Research

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25 pages, 8771 KiB  
Article
Smart Cybersecurity Framework for IoT-Empowered Drones: Machine Learning Perspective
by Abdulaziz Aldaej, Tariq Ahamed Ahanger, Mohammed Atiquzzaman, Imdad Ullah and Muhammad Yousufudin
Sensors 2022, 22(7), 2630; https://0-doi-org.brum.beds.ac.uk/10.3390/s22072630 - 29 Mar 2022
Cited by 17 | Viewed by 6297
Abstract
Drone advancements have ushered in new trends and possibilities in a variety of sectors, particularly for small-sized drones. Drones provide navigational interlocation services, which are made possible by the Internet of Things (IoT). Drone networks, on the other hand, are subject to privacy [...] Read more.
Drone advancements have ushered in new trends and possibilities in a variety of sectors, particularly for small-sized drones. Drones provide navigational interlocation services, which are made possible by the Internet of Things (IoT). Drone networks, on the other hand, are subject to privacy and security risks due to design flaws. To achieve the desired performance, it is necessary to create a protected network. The goal of the current study is to look at recent privacy and security concerns influencing the network of drones (NoD). The current research emphasizes the importance of a security-empowered drone network to prevent interception and intrusion. A hybrid ML technique of logistic regression and random forest is used for the purpose of classification of data instances for maximal efficacy. By incorporating sophisticated artificial-intelligence-inspired techniques into the framework of a NoD, the proposed technique mitigates cybersecurity vulnerabilities while making the NoD protected and secure. For validation purposes, the suggested technique is tested against a challenging dataset, registering enhanced performance results in terms of temporal efficacy (34.56 s), statistical measures (precision (97.68%), accuracy (98.58%), recall (98.59%), F-measure (99.01%), reliability (94.69%), and stability (0.73). Full article
(This article belongs to the Special Issue UAV-Based Technology for IoT)
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20 pages, 25712 KiB  
Article
Weather Sensing in an Urban Environment with the Use of a UAV and WebRTC-Based Platform: A Pilot Study
by Agnieszka Chodorek, Robert Ryszard Chodorek and Alexander Yastrebov
Sensors 2021, 21(21), 7113; https://0-doi-org.brum.beds.ac.uk/10.3390/s21217113 - 26 Oct 2021
Cited by 8 | Viewed by 2563
Abstract
Thanks to IoT, Internet access, and low-cost sensors, it has become possible to increase the number of weather measuring points; hence, the density of the deployment of sources that provide weather data for the needs of large recipients, for example, weather web services [...] Read more.
Thanks to IoT, Internet access, and low-cost sensors, it has become possible to increase the number of weather measuring points; hence, the density of the deployment of sources that provide weather data for the needs of large recipients, for example, weather web services or smart city management systems, has also increased. This paper presents a flying weather station that carries out measurements of two weather factors that are typically included in weather stations (ambient temperature and relative humidity), an often included weather factor (atmospheric pressure), and a rarely included one (ultraviolet index). In our solution, the measurements are supplemented with a visual observation of present weather phenomena. The flying weather station is built on a UAV and WebRTC-based universal platform proposed in our previous paper. The complete, fully operational flying weather station was evaluated in field studies. Experiments were conducted during a 6-month period on days having noticeably different weather conditions. Results show that weather data coming from the flying weather station were equal (with a good approximation) to weather data obtained from the reference weather station. When compared to the weather stations described in the literature (both stationary weather stations and mobile ones), the proposed solution achieved better accuracy than the other weather stations based on low-cost sensors. Full article
(This article belongs to the Special Issue UAV-Based Technology for IoT)
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24 pages, 617 KiB  
Article
Energy Optimization in Dual-RIS UAV-Aided MEC-Enabled Internet of Vehicles
by Emmanouel T. Michailidis, Nikolaos I. Miridakis, Angelos Michalas, Emmanouil Skondras and Dimitrios J. Vergados
Sensors 2021, 21(13), 4392; https://0-doi-org.brum.beds.ac.uk/10.3390/s21134392 - 27 Jun 2021
Cited by 24 | Viewed by 4196
Abstract
Mobile edge computing (MEC) represents an enabling technology for prospective Internet of Vehicles (IoV) networks. However, the complex vehicular propagation environment may hinder computation offloading. To this end, this paper proposes a novel computation offloading framework for IoV and presents an unmanned aerial [...] Read more.
Mobile edge computing (MEC) represents an enabling technology for prospective Internet of Vehicles (IoV) networks. However, the complex vehicular propagation environment may hinder computation offloading. To this end, this paper proposes a novel computation offloading framework for IoV and presents an unmanned aerial vehicle (UAV)-aided network architecture. It is considered that the connected vehicles in a IoV ecosystem should fully offload latency-critical computation-intensive tasks to road side units (RSUs) that integrate MEC functionalities. In this regard, a UAV is deployed to serve as an aerial RSU (ARSU) and also operate as an aerial relay to offload part of the tasks to a ground RSU (GRSU). In order to further enhance the end-to-end communication during data offloading, the proposed architecture relies on reconfigurable intelligent surface (RIS) units consisting of arrays of reflecting elements. In particular, a dual-RIS configuration is presented, where each RIS unit serves its nearby network nodes. Since perfect phase estimation or high-precision configuration of the reflection phases is impractical in highly mobile IoV environments, data offloading via RIS units with phase errors is considered. As the efficient energy management of resource-constrained electric vehicles and battery-enabled RSUs is of outmost importance, this paper proposes an optimization approach that intends to minimize the weighted total energy consumption (WTEC) of the vehicles and ARSU subject to transmit power constraints, timeslot scheduling, and task allocation. Extensive numerical calculations are carried out to verify the efficacy of the optimized dual-RIS-assisted wireless transmission. Full article
(This article belongs to the Special Issue UAV-Based Technology for IoT)
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35 pages, 52257 KiB  
Article
UAV-Based and WebRTC-Based Open Universal Framework to Monitor Urban and Industrial Areas
by Agnieszka Chodorek, Robert Ryszard Chodorek and Paweł Sitek
Sensors 2021, 21(12), 4061; https://0-doi-org.brum.beds.ac.uk/10.3390/s21124061 - 12 Jun 2021
Cited by 15 | Viewed by 4418
Abstract
Nowadays, we are observing a rapid development of UAV-based monitoring systems, which are faced with more and more new tasks, such as high temporal resolution and high spatial resolution of measurements, or Artificial Intelligence on board. This paper presents the open universal framework [...] Read more.
Nowadays, we are observing a rapid development of UAV-based monitoring systems, which are faced with more and more new tasks, such as high temporal resolution and high spatial resolution of measurements, or Artificial Intelligence on board. This paper presents the open universal framework intended for fast prototyping or building a short series of specialized flying monitoring systems able to work in urban and industrial areas. The proposed framework combines mobility of UAV with IoT measurements and full-stack WebRTC communications. WebRTC offers simultaneous transmission of both a real-time video stream and the flow of data coming from sensors, and ensures a kind of protection of data flow, which leads to preserving its near-real-time character and enables contextual communication. Addition of the AI accelerator hardware makes this system AI-ready, i.e., the IoT communication hub, which is the air component of our system, is able to perform tasks of AI-supported computing. The exemplary prototype of this system was evaluated in terms of the ability to work with fast-response sensors, the ability to work with high temporal and high spatial resolutions, video information in poor visibility conditions and AI-readiness. Results show that prototypes based on the proposed framework are able to meet the challenges of monitoring systems in smart cities and industrial areas. Full article
(This article belongs to the Special Issue UAV-Based Technology for IoT)
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Review

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24 pages, 3214 KiB  
Review
Review of Intentional Electromagnetic Interference on UAV Sensor Modules and Experimental Study
by Sung-Geon Kim, Euibum Lee, Ic-Pyo Hong and Jong-Gwan Yook
Sensors 2022, 22(6), 2384; https://0-doi-org.brum.beds.ac.uk/10.3390/s22062384 - 20 Mar 2022
Cited by 23 | Viewed by 6753
Abstract
With the advancement of technology, Unmanned Aerial Vehicles (UAVs), also known as drones, are being used in numerous applications. However, the illegal use of UAVs, such as in terrorism and spycams, has also increased, which has led to active research on anti-drone methods. [...] Read more.
With the advancement of technology, Unmanned Aerial Vehicles (UAVs), also known as drones, are being used in numerous applications. However, the illegal use of UAVs, such as in terrorism and spycams, has also increased, which has led to active research on anti-drone methods. Various anti-drone methods have been proposed over time; however, the most representative method is to apply intentional electromagnetic interference to drones, especially to their sensor modules. In this paper, we review various studies on the effect of intentional electromagnetic interference (IEMI) on the sensor modules. Various studies on IEMI sources are reviewed and classified on the basis of the power level, information needed, and frequency. To demonstrate the application of drone-sensor modules, major sensor modules used in drones are briefly introduced, and the setup and results of the IEMI experiment performed on them are described. Finally, we discuss the effectiveness and limitations of the proposed methods and present perspectives for further research necessary for the actual application of anti-drone technology. Full article
(This article belongs to the Special Issue UAV-Based Technology for IoT)
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