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Electronics
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IoT Assisted Unmanned Aerial Vehicle for the Cellular Networks
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IoT Assisted Unmanned Aerial Vehicle for the Cellular Networks

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 20608

Special Issue Editors

Dr. Celestine Iwendi

E-Mail Website
Guest Editor
School of Creative Technologies, University of Bolton, Bolton BL3 5AB, UK
Interests: artificial intelligence; machine learning; internet of things; blockchain; wireless sensor networks
Special Issues, Collections and Topics in MDPI journals
Dr. M. Poongodi

E-Mail Website
Guest Editor
College of Science and Engineering, Hamad Bin Khalifa University, Doha 5825, Qatar
Interests: network analysis using social networking; mobile computing; web services; 4G communication; cloud computing; information security through anomaly detection
Special Issues, Collections and Topics in MDPI journals
Dr. Senthilkumar Mohan

E-Mail Website
Guest Editor
Department of Software and Systems Engineering, School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamilnadu 632014, India
Interests: big data; deep learning; machine learning; IoT
Special Issues, Collections and Topics in MDPI journals
Dr. Mohit Mittal

E-Mail Website
Guest Editor
CRIStAL, Institut national de recherche en informatique et en automatique (INRIA), Nord Europe, 59650 Lille, France
Interests: computer vision; machine learning; deep learning; wireless sensor networks; IoT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Due to their wider service coverage over fixed sensor nodes, emerging unmanned aerial vehicles (UAVs) have been extensively utilized for sensing applications. Sensory data must be transferred in real time to the base station/server for real-time data processing due to the UAVs' limited computing capabilities; therefore, cellular networks are necessary to ease this process between UAVs, having been dubbed the "Internet of UAVs". A research item regarding an improved support for seamlessly integrating unmanned aerial vehicles into future cellular networks has been approved by the 3GPP. UAV communications include a variety of distinct features compared to terrestrial cellular networks, such as extremely dynamic network topologies and sparsely coupled communication channels, also having practical limitations, including the battery life, no-fly zones, and sensor requirements. As a consequence, ultra-reliable and real-time sensing applications require novel communication and signal processing approaches.

Topics of interest relating to the Internet of UAVs include, but are not limited to:

  • Protocols and network architecture;
  • Techniques for canceling and coordinating interference;
  • Techniques for cooperating and relaying;
  • Artificial intelligence-aided communications for the Internet of UAVs;
  • Internet of UAVs helped by a wireless power transfer;
  • Radio resource management;
  • Quality-of-service-aware trajectory optimization;
  • UAV communications;
  • Cellular networks;
  • Signal processing approaches.

Dr. Celestine Iwendi
Dr. M. Poongodi
Dr. SenthilKumar Mohan
Dr. Mohit Mittal
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. Electronics 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 2400 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

  • Protocols and network architecture
  • Internet of UAVs
  • Radio resource management
  • Quality-of-service-aware trajectory optimization
  • UAV communications
  • Cellular networks
  • Signal processing approaches

Published Papers (5 papers)

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Research

14 pages, 690 KiB  
Article
Use of Blockchain-Based Smart Contracts in Logistics and Supply Chains
by Mohammed Ali Alqarni, Mohammed Saeed Alkatheiri, Sajjad Hussain Chauhdary and Sajid Saleem
Electronics 2023, 12(6), 1340; https://doi.org/10.3390/electronics12061340 - 11 Mar 2023
Cited by 13 | Viewed by 8918
Abstract
Blockchain is a disrupting technology that has the capability to completely alter the design, activities, and product flows in logistics and supply chain networks. It provides assurance of openness, immutability, transparency, security, and neutrality for all supply chain agents and stakeholders. In this [...] Read more.
Blockchain is a disrupting technology that has the capability to completely alter the design, activities, and product flows in logistics and supply chain networks. It provides assurance of openness, immutability, transparency, security, and neutrality for all supply chain agents and stakeholders. In this paper, we explore the improvements and tradeoffs introduced by using blockchains in logistics management in terms of the sustainability of society, the environment, and economic dimensions of the supply chain. Blockchain technology makes it much more difficult to counterfeit products by providing indisputable and immutable proof of the provenance of the raw materials, products, and sale to the end consumer. This can potentially enhance the trust of the consumer in the product and financially benefit the manufacturer through the protection of their intellectual property rights. This paper explores the benefits, applications, and issues related to the usage of blockchain and smart contracts for logistics and supply-chain management. We focus on the implementation, deployment, audit, and operational aspects of smart contracts in the blockchain applied to terrestrial, maritime, and aerial logistics networks. The paper also discusses opportunities and challenges that arise due to the use of smart contracts in these sectors. Full article
(This article belongs to the Special Issue IoT Assisted Unmanned Aerial Vehicle for the Cellular Networks)
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19 pages, 2656 KiB  
Article
Forest Fire Identification in UAV Imagery Using X-MobileNet
by Anupama Namburu, Prabha Selvaraj, Senthilkumar Mohan, Sumathi Ragavanantham and Elsayed Tag Eldin
Electronics 2023, 12(3), 733; https://doi.org/10.3390/electronics12030733 - 01 Feb 2023
Cited by 17 | Viewed by 3693
Abstract
Forest fires are caused naturally by lightning, high atmospheric temperatures, and dryness. Forest fires have ramifications for both climatic conditions and anthropogenic ecosystems. According to various research studies, there has been a noticeable increase in the frequency of forest fires in India. Between [...] Read more.
Forest fires are caused naturally by lightning, high atmospheric temperatures, and dryness. Forest fires have ramifications for both climatic conditions and anthropogenic ecosystems. According to various research studies, there has been a noticeable increase in the frequency of forest fires in India. Between 1 January and 31 March 2022, the country had 136,604 fire points. They activated an alerting system that indicates the location of a forest fire detected using MODIS sensor data from NASA Aqua and Terra satellite images. However, the satellite passes the country only twice and sends the information to the state forest departments. The early detection of forest fires is crucial, as once they reach a certain level, it is hard to control them. Compared with the satellite monitoring and detection of fire incidents, video-based fire detection on the ground identifies the fire at a faster rate. Hence, an unmanned aerial vehicle equipped with a GPS and a high-resolution camera can acquire quality images referencing the fire location. Further, deep learning frameworks can be applied to efficiently classify forest fires. In this paper, a cheaper UAV with extended MobileNet deep learning capability is proposed to classify forest fires (97.26%) and share the detection of forest fires and the GPS location with the state forest departments for timely action. Full article
(This article belongs to the Special Issue IoT Assisted Unmanned Aerial Vehicle for the Cellular Networks)
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19 pages, 1274 KiB  
Article
Smart IoMT Framework for Supporting UAV Systems with AI
by Nathan Shankar, Musiri Kailasanathan Nallakaruppan, Vaishali Ravindranath, Mohan Senthilkumar and Bhuvanagiri Prahal Bhagavath
Electronics 2023, 12(1), 86; https://doi.org/10.3390/electronics12010086 - 26 Dec 2022
Cited by 6 | Viewed by 2532
Abstract
The health monitoring system is one of the most innovative technologies that has gained traction in the Internet of Medical Things (IoMT). It allows the connection of multiple sensors and actuators that can capture and monitor the data through the web page or [...] Read more.
The health monitoring system is one of the most innovative technologies that has gained traction in the Internet of Medical Things (IoMT). It allows the connection of multiple sensors and actuators that can capture and monitor the data through the web page or mobile application. IoMT technology not only provides communications but also will provide monitoring, recording, storage, and display. IoMT in healthcare is used for measuring the vital signs of the human body, which allows medical professionals to assess the well-being of a patient. The doctor may recommend lifestyle modifications, prescribe more tests, or diagnose a disorder according to the results. This paper illustrates the remote-control health monitoring system (HMS) with the integration of a UAV, which allows the doctor to access the data and analyze the patient data remotely. Thus, the proposed HMS-UAV system aims to measure the temperature, humidity, blood pressure, heart rate, and SpO2 and stores the data on the UAV. Several sensors were thus used namely DHT11, MAX30102, Myoware and K24C16, and the Raspberry Pi camera. Reduced hospital stays and avoidance of readmissions are benefits of remote patient monitoring with IoMT-based UAVs. Contrary to its advantages, IoMT has flaws in information processing since a huge volume of data are needed to be handled in a single environment. One major novel inclusion in this work is to measure multiple parameters and provide a comparative analysis for all of them. Furthermore, the functionality of video recorded and stored is included where the doctor can surveil the patient. Full article
(This article belongs to the Special Issue IoT Assisted Unmanned Aerial Vehicle for the Cellular Networks)
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17 pages, 1365 KiB  
Article
A Lightweight Authentication Scheme for a Network of Unmanned Aerial Vehicles (UAVs) by Using Physical Unclonable Functions
by Mohammed Saeed Alkatheiri, Sajid Saleem, Mohammed Ali Alqarni, Ahmad O. Aseeri, Sajjad Hussain Chauhdary and Yu Zhuang
Electronics 2022, 11(18), 2921; https://doi.org/10.3390/electronics11182921 - 15 Sep 2022
Cited by 6 | Viewed by 1672
Abstract
A network of agents constituted of multiple unmanned aerial vehicles (UAVs) is emerging as a promising technology with myriad applications in the military, public, and civil domains. UAVs’ power, memory, and size constraints, ultra-mobile nature, and non-trusted operational environments make them susceptible to [...] Read more.
A network of agents constituted of multiple unmanned aerial vehicles (UAVs) is emerging as a promising technology with myriad applications in the military, public, and civil domains. UAVs’ power, memory, and size constraints, ultra-mobile nature, and non-trusted operational environments make them susceptible to various attacks, including physical capturing and cloning attacks. A robust and resilient security protocol should be lightweight and resource-efficient in addition to providing protection against physical and tampering threats. This paper proposes an authentication protocol for a UAV-based multi-agent system robust against various threats and adversaries, including strong resistance against cloning and physical attacks. The proposed protocol is based on a physical unclonable function (PUF), a well-known hardware security primitive that is utilized for low-cost authentication and cryptographic key generation. The analysis of the proposed approach shows that it provides strong protection against various attacks, including tampering and cloning, and exhibits scalability and energy efficiency. Full article
(This article belongs to the Special Issue IoT Assisted Unmanned Aerial Vehicle for the Cellular Networks)
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17 pages, 12927 KiB  
Article
Analysis of Fault Classifiers to Detect the Faults and Node Failures in a Wireless Sensor Network
by S. Gnanavel, M. Sreekrishna, Vinodhini Mani, G. Kumaran, R. S. Amshavalli, Sadeen Alharbi, Mashael Maashi, Osamah Ibrahim Khalaf, Ghaida Muttashar Abdulsahib, Ans D. Alghamdi and Theyazn H. H. Aldhyani
Electronics 2022, 11(10), 1609; https://doi.org/10.3390/electronics11101609 - 18 May 2022
Cited by 11 | Viewed by 2390
Abstract
Technology evaluation in the electronics field leads to the great development of Wireless Sensor Networks (WSN) for a variety of applications. The sensor nodes are deployed in hazardous environments, and they are operated by isolated battery sources. Network connectivity is purely based on [...] Read more.
Technology evaluation in the electronics field leads to the great development of Wireless Sensor Networks (WSN) for a variety of applications. The sensor nodes are deployed in hazardous environments, and they are operated by isolated battery sources. Network connectivity is purely based on power availability, which impacts the network lifetime. Hence, power must be used wisely to prolong the network lifetime. The sensor nodes that fail due to power have to detect quickly to maintain the network. In a WSN, classifiers are used to detect the faults for checking the data generated by the sensor nodes. In this paper, six classifiers such as Support Vector Machine, Convolutional Neural Network, Multilayer Perceptron, Stochastic Gradient Descent, Random Forest and Probabilistic Neural Network have been taken for analysis. Six different faults (Offset fault, Gain fault, Stuck-at fault, Out of Bounds, Spike fault and Data loss) are injected in the data generated by the sensor nodes. The faulty data are checked by the classifiers. The simulation results show that the Random Forest detected more faults and it also outperformed all other classifiers in that category. Full article
(This article belongs to the Special Issue IoT Assisted Unmanned Aerial Vehicle for the Cellular Networks)
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