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Special Issue "UAV-Based Applications in the Internet of Things (IoT)"

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

Deadline for manuscript submissions: closed (30 September 2019).

Special Issue Editor

Prof. Dr. Enrico Natalizio
Website
Guest Editor
LORIA Laboratory, University of Lorraine, France
Interests: Networks of Intelligent Objects; UAV, Robot and Sensor Communications; Security and privacy in the Internet of Things
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAV) have drastically modified users, practitioners and researchers perspectives for many fields of application, such as disaster management, structural inspection, goods delivery and transportation, localization and mapping, pollution and radiation monitoring, search and rescue, farming, etc. The advancements introduced by UAVs are innumerable and have led the way for the full integration of UAVs, as intelligent objects, into the Internet of Things (IoT).

However, the integration of UAVs into the IoT poses several scientific and technical challenges. From a scientific standpoint, the use of controllable devices redefines classic robotic issues, such as trajectory planning, formation control, exploration and simultaneous localization and mapping, by introducing a new scientific dimension given by the communication and networking capabilities of UAVs. From the technical standpoint, the current networking paradigms for the IoT need to be revised in order to explicitly take into account the advanced sensing, actuation, storage, computing, reasoning capabilities of UAVs. The integration of UAVs into the IoT could be eased by leveraging the possibilities offered by network function virtualization (NFV) and software-defined networking (SDN), which are two of the main innovations of 5G systems.

The goal of this Special Issue is to report research ideas and solutions for exploiting synergies between UAVs and the IoT towards the development of innovative applications.

Prof. Enrico Natalizio
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 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

  • UAV networks
  • Internet of Things
  • Internet of Intelligent Things
  • 5G
  • Network Function Virtualization
  • Software-Defined Networking.

Published Papers (18 papers)

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Research

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Open AccessArticle
Information Distribution in Multi-Robot Systems: Utility-Based Evaluation Model
Sensors 2020, 20(3), 710; https://doi.org/10.3390/s20030710 - 28 Jan 2020
Cited by 1
Abstract
This work addresses the problem of information distribution in multi-robot systems, with an emphasis on multi-UAV (unmanned aerial vehicle) applications. We present an analytical model that helps evaluate and compare different information distribution schemes in a robotic mission. It serves as a unified [...] Read more.
This work addresses the problem of information distribution in multi-robot systems, with an emphasis on multi-UAV (unmanned aerial vehicle) applications. We present an analytical model that helps evaluate and compare different information distribution schemes in a robotic mission. It serves as a unified framework to represent the usefulness (utility) of each message exchanged by the robots. It can be used either on its own in order to assess the information distribution efficacy or as a building block of solutions aimed at optimizing information distribution. Moreover, we present multiple examples of instantiating the model for specific missions. They illustrate various approaches to defining the utility of different information types. Finally, we introduce a proof of concept showing the applicability of the model in a robotic system by implementing it in Robot Operating System 2 (ROS 2) and performing a simple simulated mission using a network emulator. We believe the introduced model can serve as a basis for further research on generic solutions for assessing or optimizing information distribution. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Transport-Layer Limitations for NFV Orchestration in Resource-Constrained Aerial Networks
Sensors 2019, 19(23), 5220; https://doi.org/10.3390/s19235220 - 28 Nov 2019
Abstract
In this paper, we identify the main challenges and problems related with the management and orchestration of Virtualized Network Functions (VNFs) over aerial networks built with Small Unmanned Aerial Vehicles (SUAVs). Our analysis starts from a reference scenario, where several SUAVs are deployed [...] Read more.
In this paper, we identify the main challenges and problems related with the management and orchestration of Virtualized Network Functions (VNFs) over aerial networks built with Small Unmanned Aerial Vehicles (SUAVs). Our analysis starts from a reference scenario, where several SUAVs are deployed over a delimited geographic area, and provide a mobile cloud environment that supports the deployment of functions and services using Network Functions Virtualization (NFV) technologies. After analyzing the main challenges to NFV orchestration in this reference scenario from a theoretical perspective, we undertake the study of one specific but relevant aspect following a practical perspective, i.e., the limitations of existing transport-layer solutions to support the dissemination of NFV management and orchestration information in the considered scenario. While in traditional cloud computing environments this traffic is delivered using TCP, our simulation results suggest that using this protocol over an aerial network of SUAVs presents certain limitations. Finally, based on the lessons learned from our practical analysis, the paper outlines different alternatives that could be followed to address these challenges. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Internet of Unmanned Aerial Vehicles—A Multilayer Low-Altitude Airspace Model for Distributed UAV Traffic Management
Sensors 2019, 19(21), 4779; https://doi.org/10.3390/s19214779 - 03 Nov 2019
Abstract
The rapid adoption of Internet of Things (IoT) has encouraged the integration of new connected devices such as Unmanned Aerial Vehicles (UAVs) to the ubiquitous network. UAVs promise a pragmatic solution to the limitations of existing terrestrial IoT infrastructure as well as bring [...] Read more.
The rapid adoption of Internet of Things (IoT) has encouraged the integration of new connected devices such as Unmanned Aerial Vehicles (UAVs) to the ubiquitous network. UAVs promise a pragmatic solution to the limitations of existing terrestrial IoT infrastructure as well as bring new means of delivering IoT services through a wide range of applications. Owning to their potential, UAVs are expected to soon dominate the low-altitude airspace over populated cities. This introduces new research challenges such as the safe management of UAVs operation under high traffic demands. This paper proposes a novel way of structuring the uncontrolled, low-altitude airspace, with the aim of addressing the complex problem of UAV traffic management at an abstract level. The work, hence, introduces a model of the airspace as a weighted multilayer network of nodes and airways and presents a set of experimental simulation results using three UAV traffic management heuristics. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
An Anti-Interference Scheme for UAV Data Links in Air–Ground Integrated Vehicular Networks
Sensors 2019, 19(21), 4742; https://doi.org/10.3390/s19214742 - 31 Oct 2019
Cited by 1
Abstract
As one of the main applications of the Internet of things (IoT), the vehicular ad-hoc network (VANET) is the core of the intelligent transportation system (ITS). Air–ground integrated vehicular networks (AGIVNs) assisted by unmanned aerial vehicles (UAVs) have the advantages of wide coverage [...] Read more.
As one of the main applications of the Internet of things (IoT), the vehicular ad-hoc network (VANET) is the core of the intelligent transportation system (ITS). Air–ground integrated vehicular networks (AGIVNs) assisted by unmanned aerial vehicles (UAVs) have the advantages of wide coverage and flexible configuration, which outperform the ground-based VANET in terms of communication quality. However, the complex electromagnetic interference (EMI) severely degrades the communication performance of UAV sensors. Therefore, it is meaningful and challenging to design an efficient anti-interference scheme for UAV data links in AGIVNs. In this paper, we propose an anti-interference scheme, named as Mary-MCM, for UAV data links in AGIVNs based on multi-ary (M-ary) spread spectrum and multi-carrier modulation (MCM). Specifically, the Mary-MCM disperses the interference power by expanding the signal spectrum, such that the anti-interference ability of AGIVNs is enhanced. Besides, by using MCM and multiple-input multiple-output (MIMO) technologies, the Mary-MCM improves the spectrum utilization effectively while ensuring system performance. The simulation results verify that the Mary-MCM achieves excellent anti-interference performance under different EMI combinations. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
An Innovative Technique for Identification of Missing Persons in Natural Disaster Based on Drone-Femtocell Systems
Sensors 2019, 19(20), 4547; https://doi.org/10.3390/s19204547 - 19 Oct 2019
Cited by 1
Abstract
The recent development of the IoT (Internet of Things), which has enabled new types of sensors that can be easily interconnected to the Internet, will also have a significant impact in the near future on the management of natural disasters (mainly earthquakes and [...] Read more.
The recent development of the IoT (Internet of Things), which has enabled new types of sensors that can be easily interconnected to the Internet, will also have a significant impact in the near future on the management of natural disasters (mainly earthquakes and floods) with the aim of improving effectiveness in research, identification, and recovery of missing persons, and therefore increasing the possibility of saving lives. In this paper, more specifically, an innovative technique is proposed for the search and identification of missing persons in natural disaster scenarios by employing a drone-femtocell system and devising an algorithm capable of locating any mobile terminal in a given monitoring area. In particular, through a series of power measurements based on the reference signal received power (RSRP), the algorithm allows for the classification of the terminal inside or outside the monitoring area and subsequently identify the position with an accuracy of about 1 m, even in the presence of obstacles that act in such a way as to make the propagation of the radio signal non-isotropic. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Energy-Efficient UAV-Enabled MEC System: Bits Allocation Optimization and Trajectory Design
Sensors 2019, 19(20), 4521; https://doi.org/10.3390/s19204521 - 17 Oct 2019
Abstract
The unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) system is attracting a lot of attentions for the potential of low latency and low transmission energy consumption, due to the advantages of high mobility and easy deployment. It has been widely applied [...] Read more.
The unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) system is attracting a lot of attentions for the potential of low latency and low transmission energy consumption, due to the advantages of high mobility and easy deployment. It has been widely applied to provide communication and computing services, especially in Internet of Things (IoT). However, there are still some challenges in the UAV-enabled MEC system. Firstly, the endurance of the UAV is limited and further impacts the performance of the system. Secondly, mobile devices are battery-powered and the batteries of some devices are hard to change. Therefore, in this paper, a UAV-enabled MEC system in which the UAV is empowered to have computing capability and provides tasks offloading service is studied. The total energy consumption of the UAV-enabled system, which includes the energy consumption of the UAV and the energy consumption of the ground users, is minimized under the constraints of the UAV’s energy budget, the number of each task’s bits, the causality of the data and the velocity of the UAV. The bits allocation of uploading data, computing data, downloading data and the trajectory of the UAV are jointly optimized with the goal of minimizing the total energy consumption. Moreover, a two-stage alternating algorithm is proposed to solve the non-convex formulated problem. Finally, the simulation results show the superiority of the proposed scheme compared with other benchmark schemes. Finally, the performance of the proposed scheme is demonstrated under different settings. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Risk-Aware Resource Management in Public Safety Networks
Sensors 2019, 19(18), 3853; https://doi.org/10.3390/s19183853 - 06 Sep 2019
Cited by 2
Abstract
Modern Public Safety Networks (PSNs) are assisted by Unmanned Aerial Vehicles (UAVs) to provide a resilient communication paradigm during catastrophic events. In this context, we propose a distributed user-centric risk-aware resource management framework in UAV-assisted PSNs supported by both a static UAV and [...] Read more.
Modern Public Safety Networks (PSNs) are assisted by Unmanned Aerial Vehicles (UAVs) to provide a resilient communication paradigm during catastrophic events. In this context, we propose a distributed user-centric risk-aware resource management framework in UAV-assisted PSNs supported by both a static UAV and a mobile UAV. The mobile UAV is entitled to a larger portion of the available spectrum due to its capability and flexibility to re-position itself, and therefore establish better communication channel conditions to the users, compared to the static UAV. However, the potential over-exploitation of the mobile UAV-based communication by the users may lead to the mobile UAV’s failure to serve the users due to the increased levels of interference, consequently introducing risk in the user decisions. To capture this uncertainty, we follow the principles of Prospect Theory and design a user’s prospect-theoretic utility function that reflects user’s risk-aware behavior regarding its transmission power investment to the static and/or mobile UAV-based communication option. A non-cooperative game among the users is formulated, where each user determines its power investment strategy to the two available communication choices in order to maximize its expected prospect-theoretic utility. The existence and uniqueness of a Pure Nash Equilibrium (PNE) is proven and the convergence of the users’ strategies to it is shown. An iterative distributed and low-complexity algorithm is introduced to determine the PNE. The performance of the proposed user-centric risk-aware resource management framework in terms of users’ achievable data rate and spectrum utilization, is achieved via modeling and simulation. Furthermore, its superiority and benefits are demonstrated, by comparing its performance against other existing approaches with regards to UAV selection and spectrum utilization. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Optimizing 802.15.4 Outdoor IoT Sensor Networks for Aerial Data Collection
Sensors 2019, 19(16), 3479; https://doi.org/10.3390/s19163479 - 09 Aug 2019
Cited by 3
Abstract
Rural IoT sensor networks, prevalent in environmental monitoring and precision agriculture, commonly operate over some variant of the IEEE 802.15.4 standard. Data collection from these networks is often challenging, as they may be deployed in remote regions where existing backhaul infrastructure is expensive [...] Read more.
Rural IoT sensor networks, prevalent in environmental monitoring and precision agriculture, commonly operate over some variant of the IEEE 802.15.4 standard. Data collection from these networks is often challenging, as they may be deployed in remote regions where existing backhaul infrastructure is expensive or absent. With the commercial and industrial success of Unmanned Aircraft Systems (UAS), there is understandable interest in using UASs for delay tolerant data collection from 802.15.4 IoT sensor networks. In this study, we investigate how to optimize 802.15.4 networks for aerial data collection, which, unlike other wireless standards, has not received rigorous evaluation for three-dimensional aerial communication. We analyze experimental measurements from an outdoor aerial testbed, examining how factors, such as antenna orientation, altitude, antenna placement, and obstruction, affect signal strength and packet reception rate. In our analysis, we model and predict the quality of service for aerial data collection, based on these network configuration variables, and contrast that with the Received Signal Strength Indication (RSSI)—a commonly used signal strength metric. We find that network configuration plays a significant role in network quality, which RSSI, a mediator variable, struggles to account for in the presence of high packet loss. We conclude with a discussion of strategies for optimizing sensor network configuration for aerial data collection, in light of our results. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
A QoE-Oriented Uplink Allocation for Multi-UAV Video Streaming
Sensors 2019, 19(15), 3394; https://doi.org/10.3390/s19153394 - 02 Aug 2019
Abstract
Video streaming has become a kind of main information carried by Unmanned Aerial Vehicles (UAVs). Unlike single transmission, when a cluster of UAVs execute the real-time video shooting and uploading mission, the insufficiency of wireless channel resources will lead to bandwidth competition among [...] Read more.
Video streaming has become a kind of main information carried by Unmanned Aerial Vehicles (UAVs). Unlike single transmission, when a cluster of UAVs execute the real-time video shooting and uploading mission, the insufficiency of wireless channel resources will lead to bandwidth competition among them and the competition will bring bad watching experience to the audience. Therefore, how to allocate uplink bandwidth reasonably in the cluster has become a crucial problem. In this paper, an intelligent and distributed allocation mechanism is designed for improving users’ video viewing satisfication. Each UAV in a cluster can independently adjust and select its video encoding rate so as to achieve flexible uplink allocation. This choice relies neither on the existence of the central node, nor on the large amount of information interaction between UAVs. Firstly, in order to distinguish video service from ordinary data, a utility function for the overall Quality of Experience (QoE) is proposed. Then, a potential game model is built around the problem. By a distributed self-learning algorithm with low complexity, all UAVs can iteratively update their own bandwidth strategy in a short time until equilibria, thus achieving the total quality optimization of all videos. Numeric simulation results indicate, after a few iterations, that the algorithm converges to a set of correlation equilibria. This mechanism not only solves the uplink allocation problem of video streaming in UAV cluster, but also guarantees the wireless resource providers in distinguishing and ensuring network service quality. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Performance Evaluation of Direct-Link Backhaul for UAV-Aided Emergency Networks
Sensors 2019, 19(15), 3342; https://doi.org/10.3390/s19153342 - 30 Jul 2019
Cited by 2
Abstract
Today’s wireless networks provide us reliable connectivity. However, if a disaster occurs, the whole network could be out of service and people cannot communicate. Using a fast deployable temporally network by mounting small cell base stations on unmanned aerial vehicles (UAVs) could solve [...] Read more.
Today’s wireless networks provide us reliable connectivity. However, if a disaster occurs, the whole network could be out of service and people cannot communicate. Using a fast deployable temporally network by mounting small cell base stations on unmanned aerial vehicles (UAVs) could solve the problem. Yet, this raises several challenges. We propose a capacity-deployment tool to design the backhaul network for UAV-aided networks and to evaluate the performance of the backhaul network in a realistic scenario in the city center of Ghent, Belgium. This tool assigns simultaneously resources to the ground users—access network—and to the backhaul network, taking into consideration backhaul capacity and power restrictions. We compare three types of backhaul scenarios using a 3.5 GHz link, 3.5 GHz with carrier aggregation (CA) and the 60 GHz band, considering three different types of drones. The results showed that an optimal UAV flight height (80 m) could satisfy both access and backhaul networks; however, full coverage was difficult to achieve. Finally, we discuss the influence of the flight height and the number of requesting users concerning the network performance and propose an optimal configuration and new mechanisms to improve the network capacity, based on realistic restrictions. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Enabling the Orchestration of IoT Slices through Edge and Cloud Microservice Platforms
Sensors 2019, 19(13), 2980; https://doi.org/10.3390/s19132980 - 05 Jul 2019
Cited by 3
Abstract
This article addresses one of the main challenges related to the practical deployment of Internet of Things (IoT) solutions: the coordinated operation of entities at different infrastructures to support the automated orchestration of end-to-end Internet of Things services. This idea is referred to [...] Read more.
This article addresses one of the main challenges related to the practical deployment of Internet of Things (IoT) solutions: the coordinated operation of entities at different infrastructures to support the automated orchestration of end-to-end Internet of Things services. This idea is referred to as “Internet of Things slicing” and is based on the network slicing concept already defined for the Fifth Generation (5G) of mobile networks. In this context, we present the architectural design of a slice orchestrator addressing the aforementioned challenge, based on well-known standard technologies and protocols. The proposed solution is able to integrate existing technologies, like cloud computing, with other more recent technologies like edge computing and network slicing. In addition, a functional prototype of the proposed orchestrator has been implemented, using open-source software and microservice platforms. As a first step to prove the practical feasibility of our solution, the implementation of the orchestrator considers cloud and edge domains. The validation results obtained from the prototype prove the feasibility of the solution from a functional perspective, verifying its capacity to deploy Internet of Things related functions even on resource constrained platforms. This approach enables new application models where these Internet of Things related functions can be onboarded on small unmanned aerial vehicles, offering a flexible and cost-effective solution to deploy these functions at the network edge. In addition, this proposal can also be used on commercial cloud platforms, like the Google Compute Engine, showing that it can take advantage of the benefits of edge and cloud computing respectively. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Energy-Effective Data Gathering for UAV-Aided Wireless Sensor Networks
Sensors 2019, 19(11), 2506; https://doi.org/10.3390/s19112506 - 31 May 2019
Cited by 7
Abstract
Unmanned aerial vehicles (UAVs) are capable of serving as a data collector for wireless sensor networks (WSNs). In this paper, we investigate an energy-effective data gathering approach in UAV-aided WSNs, where each sensor node (SN) dynamically chooses the transmission modes, i.e., (1) waiting, [...] Read more.
Unmanned aerial vehicles (UAVs) are capable of serving as a data collector for wireless sensor networks (WSNs). In this paper, we investigate an energy-effective data gathering approach in UAV-aided WSNs, where each sensor node (SN) dynamically chooses the transmission modes, i.e., (1) waiting, (2) conventional sink node transmission, (3) uploading to UAV, to transmit sensory data within a given time. By jointly considering the SN’s transmission policy and UAV trajectory optimization, we aim to minimize the transmission energy consumption of the SNs and ensure all sensory data completed collected within the given time. We take a two-step iterative approach and decouple the SN’s transmission design and UAV trajectory optimization process. First, we design the optimal SNs transmission mode policy with preplanned UAV trajectory. A dynamic programming (DP) algorithm is proposed to obtain the optimal transmission policy. Then, with the fixed transmission policy, we optimize the UAV’s trajectory from the preplanned trace with recursive random search (RRS) algorithm. Numerical results show that the proposed scheme achieves significant energy savings gain over the benchmark schemes. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
A Distributed Approach for Collision Avoidance between Multirotor UAVs Following Planned Missions
Sensors 2019, 19(10), 2404; https://doi.org/10.3390/s19102404 - 26 May 2019
Cited by 2
Abstract
As the number of potential applications for Unmanned Aerial Vehicles (UAVs) keeps rising steadily, the chances that these devices get close to each other during their flights also increases, causing concerns regarding potential collisions. This paper proposed the Mission Based Collision Avoidance Protocol [...] Read more.
As the number of potential applications for Unmanned Aerial Vehicles (UAVs) keeps rising steadily, the chances that these devices get close to each other during their flights also increases, causing concerns regarding potential collisions. This paper proposed the Mission Based Collision Avoidance Protocol (MBCAP), a novel UAV collision avoidance protocol applicable to all types of multicopters flying autonomously. It relies on wireless communications in order to detect nearby UAVs, and to negotiate the procedure to avoid any potential collision. Experimental and simulation results demonstrated the validity and effectiveness of the proposed solution, which typically introduces a small overhead in the range of 15 to 42 s for each risky situation successfully handled. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Joint Placement and Device Association of UAV Base Stations in IoT Networks
Sensors 2019, 19(9), 2157; https://doi.org/10.3390/s19092157 - 09 May 2019
Cited by 7
Abstract
Drone base stations (DBSs) have received significant research interest in recent years. They provide a flexible and cost-effective solution to improve the coverage, connectivity, quality of service (QoS), and energy efficiency of large-area Internet of Things (IoT) networks. However, as DBSs are costly [...] Read more.
Drone base stations (DBSs) have received significant research interest in recent years. They provide a flexible and cost-effective solution to improve the coverage, connectivity, quality of service (QoS), and energy efficiency of large-area Internet of Things (IoT) networks. However, as DBSs are costly and power-limited devices, they require an efficient scheme for their deployment in practical networks. This work proposes a realistic mathematical model for the joint optimization problem of DBS placement and IoT users’ assignment in a massive IoT network scenario. The optimization goal is to maximize the connectivity of IoT users by utilizing the minimum number of DBS, while satisfying practical network constraints. Such an optimization problem is NP-hard, and the optimal solution has a complexity exponential to the number of DBSs and IoT users in the network. Furthermore, this work also proposes a linearization scheme and a low-complexity heuristic to solve the problem in polynomial time. The simulations are performed for a number of network scenarios, and demonstrate that the proposed heuristic is numerically accurate and performs close to the optimal solution. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Resource Allocation in Unmanned Aerial Vehicle (UAV)-Assisted Wireless-Powered Internet of Things
Sensors 2019, 19(8), 1908; https://doi.org/10.3390/s19081908 - 22 Apr 2019
Cited by 3
Abstract
Most of the wireless nodes in the Internet of Things (IoT) environment face the limited energy problem and the way to provide a sustainable energy for these nodes has become an urgent challenge. In this paper, we present an unmanned aerial vehicle (UAV) [...] Read more.
Most of the wireless nodes in the Internet of Things (IoT) environment face the limited energy problem and the way to provide a sustainable energy for these nodes has become an urgent challenge. In this paper, we present an unmanned aerial vehicle (UAV) to power the wireless nodes in the IoT and an investigation on the optimal resource allocation approach based on dynamic game theory. This IoT system consists of one UAV as the power source and information receiver. The wireless nodes can be powered and collected by the UAV. In order to distinguish the wireless nodes, the wireless nodes are divided into two categories based on the energy consumption. The UAV tries to power these two categories of nodes using a different power level based on the proposed approach, where the wireless nodes control the resources for information transmission. Based on Bellman dynamic programming, the optimal allocated resources for power transfer and information transmission are obtained for both the UAV and wireless nodes, respectively. In order to show the effectiveness of the proposed model and approach, we present numerical simulations. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things
Sensors 2019, 19(7), 1600; https://doi.org/10.3390/s19071600 - 02 Apr 2019
Cited by 1
Abstract
Multi-agent hybrid social cognitive optimization (MAHSCO) based on the Internet of Things (IoT) is suggested to solve the problem of the generation of formations of unmanned vehicles. Through the analysis of the unmanned vehicle formation problem, formation principles, formation scale, unmanned vehicle formation [...] Read more.
Multi-agent hybrid social cognitive optimization (MAHSCO) based on the Internet of Things (IoT) is suggested to solve the problem of the generation of formations of unmanned vehicles. Through the analysis of the unmanned vehicle formation problem, formation principles, formation scale, unmanned vehicle formation safety distance, and formation evaluation indicators are taken into consideration. The application of the IoT enables the optimization of distributed computing. To ensure the reliability of the formation algorithm, the convergence of MAHSCO has been proved. Finally, computer simulation and actual unmanned aerial vehicle (UAV) formation generation flight generating four typical formations are carried out. The result of the actual UAV formation generation flight is consistent with the simulation experiment, and the algorithm performs well. The MAHSCO algorithm based on the IoT is proved to be able to generate formations that meet the mission requirements quickly and accurately. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Open AccessArticle
Minimum-Throughput Maximization for Multi-UAV-Enabled Wireless-Powered Communication Networks
Sensors 2019, 19(7), 1491; https://doi.org/10.3390/s19071491 - 27 Mar 2019
Cited by 7
Abstract
This paper considers a wireless-powered communication network (WPCN) system that uses multiple unmanned aerial vehicles (UAVs). Ground users (GUs) first harvest energy from a mobile wireless energy transfer (WET) UAV then use the energy to power their information transmission to a data gatherer [...] Read more.
This paper considers a wireless-powered communication network (WPCN) system that uses multiple unmanned aerial vehicles (UAVs). Ground users (GUs) first harvest energy from a mobile wireless energy transfer (WET) UAV then use the energy to power their information transmission to a data gatherer (DG) UAV. We aim to maximize the minimum throughput for all GUs by jointly optimizing UAV trajectories, and the resource allocation of ET UAV and GUs. Because of the non-convexity of the formulated problem, we propose an alternating optimization algorithm, applying successive convex optimization techniques to solve the problem; the UAV trajectories and resource allocation are alternately optimized in each iteration. Numerical results show the efficiency of the proposed algorithm in different scenarios. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Review

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Open AccessReview
Precision Agriculture Techniques and Practices: From Considerations to Applications
Sensors 2019, 19(17), 3796; https://doi.org/10.3390/s19173796 - 02 Sep 2019
Cited by 8
Abstract
Internet of Things (IoT)-based automation of agricultural events can change the agriculture sector from being static and manual to dynamic and smart, leading to enhanced production with reduced human efforts. Precision Agriculture (PA) along with Wireless Sensor Network (WSN) are the main drivers [...] Read more.
Internet of Things (IoT)-based automation of agricultural events can change the agriculture sector from being static and manual to dynamic and smart, leading to enhanced production with reduced human efforts. Precision Agriculture (PA) along with Wireless Sensor Network (WSN) are the main drivers of automation in the agriculture domain. PA uses specific sensors and software to ensure that the crops receive exactly what they need to optimize productivity and sustainability. PA includes retrieving real data about the conditions of soil, crops and weather from the sensors deployed in the fields. High-resolution images of crops are obtained from satellite or air-borne platforms (manned or unmanned), which are further processed to extract information used to provide future decisions. In this paper, a review of near and remote sensor networks in the agriculture domain is presented along with several considerations and challenges. This survey includes wireless communication technologies, sensors, and wireless nodes used to assess the environmental behaviour, the platforms used to obtain spectral images of crops, the common vegetation indices used to analyse spectral images and applications of WSN in agriculture. As a proof of concept, we present a case study showing how WSN-based PA system can be implemented. We propose an IoT-based smart solution for crop health monitoring, which is comprised of two modules. The first module is a wireless sensor network-based system to monitor real-time crop health status. The second module uses a low altitude remote sensing platform to obtain multi-spectral imagery, which is further processed to classify healthy and unhealthy crops. We also highlight the results obtained using a case study and list the challenges and future directions based on our work. Full article
(This article belongs to the Special Issue UAV-Based Applications in the Internet of Things (IoT))
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Figure 1

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