scholarly journals Offloading Data through Unmanned Aerial Vehicles: A Dependability Evaluation

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1916
Author(s):  
Carlos Brito ◽  
Leonardo Silva ◽  
Gustavo Callou ◽  
Tuan Anh Nguyen ◽  
Dugki Min ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Base Station ◽  
Stochastic Petri Nets ◽  
Cloud Data ◽  
Aerial Vehicles ◽  
Processing Power ◽  
Key Points ◽  
Dependability Evaluation ◽  
Iot Devices ◽  
Different Characteristics

Applications in the Internet of Things (IoT) context continuously generate large amounts of data. The data must be processed and monitored to allow rapid decision making. However, the wireless connection that links such devices to remote servers can lead to data loss. Thus, new forms of a connection must be explored to ensure the system’s availability and reliability as a whole. Unmanned aerial vehicles (UAVs) are becoming increasingly empowered in terms of processing power and autonomy. UAVs can be used as a bridge between IoT devices and remote servers, such as edge or cloud computing. UAVs can collect data from mobile devices and process them, if possible. If there is no processing power in the UAV, the data are sent and processed on servers at the edge or in the cloud. Data offloading throughout UAVs is a reality today, but one with many challenges, mainly due to unavailability constraints. This work proposes stochastic Petri net (SPN) models and reliability block diagrams (RBDs) to evaluate a distributed architecture, with UAVs focusing on the system’s availability and reliability. Among the various existing methodologies, stochastic Petri nets (SPN) provide models that represent complex systems with different characteristics. UAVs are used to route data from IoT devices to the edge or the cloud through a base station. The base station receives data from UAVs and retransmits them to the cloud. The data are processed in the cloud, and the responses are returned to the IoT devices. A sensitivity analysis through Design of Experiments (DoE) showed key points of improvement for the base model, which was enhanced. A numerical analysis indicated the components with the most significant impact on availability. For example, the cloud proved to be a very relevant component for the availability of the architecture. The final results could prove the effectiveness of improving the base model. The present work can help system architects develop distributed architectures with more optimized UAVs and low evaluation costs.

scholarly journals A Framework for Agricultural Pest and Disease Monitoring Based on Internet-of-Things and Unmanned Aerial Vehicles

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1487 ◽  
Author(s):  
Demin Gao ◽  
Quan Sun ◽  
Bin Hu ◽  
Shuo Zhang
Keyword(s):  
Internet Of Things ◽  
Unmanned Aerial Vehicles ◽  
Sensor Nodes ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Pests And Diseases ◽  
Aerial Vehicles ◽  
Sensing Technology ◽  
Weather Parameters ◽  
Iot Devices

With the development of information technology, Internet-of-Things (IoT) and low-altitude remote-sensing technology represented by Unmanned Aerial Vehicles (UAVs) are widely used in environmental monitoring fields. In agricultural modernization, IoT and UAV can monitor the incidence of crop diseases and pests from the ground micro and air macro perspectives, respectively. IoT technology can collect real-time weather parameters of the crop growth by means of numerous inexpensive sensor nodes. While depending on spectral camera technology, UAVs can capture the images of farmland, and these images can be utilize for analyzing the occurrence of pests and diseases of crops. In this work, we attempt to design an agriculture framework for providing profound insights into the specific relationship between the occurrence of pests/diseases and weather parameters. Firstly, considering that most farms are usually located in remote areas and far away from infrastructure, making it hard to deploy agricultural IoT devices due to limited energy supplement, a sun tracker device is designed to adjust the angle automatically between the solar panel and the sunlight for improving the energy-harvesting rate. Secondly, for resolving the problem of short flight time of UAV, a flight mode is introduced to ensure the maximum utilization of wind force and prolong the fight time. Thirdly, the images captured by UAV are transmitted to the cloud data center for analyzing the degree of damage of pests and diseases based on spectrum analysis technology. Finally, the agriculture framework is deployed in the Yangtze River Zone of China and the results demonstrate that wheat is susceptible to disease when the temperature is between 14 °C and 16 °C, and high rainfall decreases the spread of wheat powdery mildew.

scholarly journals A Dynamic Topology Construction Algorithm for Self-Organizing Wireless Sensor Networks

2021 ◽  
Author(s):  
Waltenegus Dargie
Keyword(s):  
Wireless Sensor Networks ◽  
Environmental Factors ◽  
Unmanned Aerial Vehicles ◽  
Base Station ◽  
Wireless Sensor ◽  
Topology Construction ◽  
Construction Algorithm ◽  
Aerial Vehicles ◽  
Dynamic Topology ◽  
Self Organizing

<div>Self-organizing protocols and algorithms require knowledge of the underlying topology of the network. The topology can be represented by a graph or an adjacency matrix. In most practical cases, establishing the topology prior to a deployment is not possible because the exact placement of nodes and the existence of a reliable link between any two individual nodes cannot guaranteed. Therefore, this task has to be carried out after deployment. If the network is stand-alone and certain aspects are fixed (such as the identity of the base station, the size of the network, etc.), the task is achievable. If, however, the network has to interact with other systems -- such as Unmanned Aerial Vehicles (UAVs) or mobile robots -- whose operation is affected by environmental factors, the task can be difficult to achieve. In this paper we propose a dynamic topology construction algorithm, assuming that the network is a part of a joint deployment and does not have a fixed based station.</div>

scholarly journals Control System Architecture for Automatic Recovery of Fixed-Wing Unmanned Aerial Vehicles in a Moving Arrest System

2021 ◽  
Vol 103 (4) ◽  
Author(s):  
Kristoffer Gryte ◽  
Martin L. Sollie ◽  
Tor Arne Johansen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Low Cost ◽  
Field Testing ◽  
Satellite System ◽  
Base Station ◽  
Research Literature ◽  
Aerial Vehicles ◽  
Global Navigation Satellite ◽  
The Right ◽  
Automatic Recovery

AbstractAutomatic recovery is an important step in enabling fully autonomous missions using fixed-wing unmanned aerial vehicles (UAVs) operating from ships or other moving platforms. However, automatic recovery in moving arrest systems is only briefly studied in the research literature, and is not yet an option when using low-cost, commercial off-the-shelf (COTS) autopilots. Acknowledging the reliability and low cost of COTS avionics, this paper adds recovery functionality as a modular extension based on non-intrusive additions to an autopilot with very general assumptions on its interface. This is achieved by line-of-sight guidance, which sends an augmented desired position to the autopilot, to ensure line-following along a virtual runway that guides the UAV into the arrest system. The translation and rotation of this line is determined by the pose of the arrest system, determined using two Global Navigation Satellite System (GNSS) receivers, where one is configured as a Real-Time Kinematic (RTK) base station. The relative position of the UAV and arrest system is also precisely estimated using RTK GNSS. Through extensive field testing, on two different fixed-wing UAVs, the system has shown its performance and reliability; 43 recovery attempts in a stationary net hit 0.01 ± 0.25m to the right and 0.07 ± 0.20m below the target in calm conditions. Further, 15 recoveries in a barge-mounted, ship-towed net hit 0.06 ± 0.53m to the right and 0.98 ± 0.27m below the target in winds up to 4 m/s. The remaining error is largely systematic, caused by communication delays, and could be reduced with more integral effect or through direct compensation.

scholarly journals Medium Access Control Protocols for the Internet of Things Based on Unmanned Aerial Vehicles: A Comparative Survey

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5586
Author(s):  
Shreya Khisa ◽  
Sangman Moh
Keyword(s):  
Internet Of Things ◽  
Access Control ◽  
Medium Access Control ◽  
Unmanned Aerial Vehicles ◽  
Mac Protocols ◽  
The Internet ◽  
Medium Access ◽  
Aerial Vehicles ◽  
Iot Devices ◽  
The Internet Of Things

The Internet of Things (IoT), which consists of a large number of small low-cost devices, has become a leading solution for smart cities, smart agriculture, smart buildings, smart grids, e-healthcare, etc. Integrating unmanned aerial vehicles (UAVs) with IoT can result in an airborne UAV-based IoT (UIoT) system and facilitate various value-added services from sky to ground. In addition to wireless sensors, various kinds of IoT devices are connected in UIoT, making the network more heterogeneous. In a UIoT system, for achieving high throughput in an energy-efficient manner, it is crucial to design an efficient medium access control (MAC) protocol because the MAC layer is responsible for coordinating access among the IoT devices in the shared wireless medium. Thus, various MAC protocols with different objectives have been reported for UIoT. However, to the best of the authors’ knowledge, no survey had been performed so far that dedicatedly covers MAC protocols for UIoT. Hence, in this study, state-of-the-art MAC protocols for UIoT are investigated. First, the communication architecture and important design considerations of MAC protocols for UIoT are examined. Subsequently, different MAC protocols for UIoT are classified, reviewed, and discussed with regard to the main ideas, innovative features, advantages, limitations, application domains, and potential future improvements. The reviewed MAC protocols are qualitatively compared with regard to various operational characteristics and system parameters. Additionally, important open research issues and challenges with recommended solutions are summarized and discussed.

Towards a Predictive Analysis of UAV-Based Flying Base Station Decisions

2020 ◽  
Vol 16 (2) ◽  
pp. 20-52 ◽  
Author(s):  
Hamid Garmani ◽  
Driss Ait Omar ◽  
Mohamed El Amrani ◽  
Mohamed Baslam ◽  
Mostafa Jourhmane
Keyword(s):  
Nash Equilibrium ◽  
Unmanned Aerial Vehicles ◽  
Base Station ◽  
Base Stations ◽  
Practical Significance ◽  
Game Model ◽  
Activity Scheduling ◽  
Area Of Interest ◽  
Aerial Vehicles ◽  
Fairness Concern

The use of unmanned aerial vehicles (UAVs) as a communication platform is of great practical significance in the wireless communications field. This paper studies the activity scheduling of unmanned aerial vehicles acting as aerial base stations in an area of interest for a specific period. Specifically, competition among multiple UAVs is explored, and a game model for the competition is developed. The Nash equilibrium of the game model is then analyzed. Based on the analysis, an algorithm for Nash equilibrium computation is proposed. Then, a game model with fairness concern is established, and its equilibrium price is also analyzed. In addition, numerical examples are conducted to determine the factors that affect the strategies (price, quality of service, and beaconing duration) of the UAV and to show how the expected profits of UAVs change with that fairness concern point. The authors believe that this research paper will shed light on the application of UAV as a flying base station.

Minimizing the number of wireless charging PAD for unmanned aerial vehicle–based wireless rechargeable sensor networks

2021 ◽  
Vol 17 (12) ◽  
pp. 155014772110559
Author(s):  
Yingjue Chen ◽  
Yingnan Gu ◽  
Panfeng Li ◽  
Feng Lin
Keyword(s):  
Sensor Networks ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Large Scale ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Charging ◽  
Aerial Vehicles ◽  
Wireless Rechargeable Sensor Networks ◽  
Aerial Vehicle

In wireless rechargeable sensor networks, most researchers address energy scarcity by introducing one or multiple ground mobile vehicles to recharge energy-hungry sensor nodes. The charging efficiency is limited by the moving speed of ground chargers and rough environments, especially in large-scale or challenging scenarios. To address the limitations, researchers consider replacing ground mobile chargers with lightweight unmanned aerial vehicles to support large-scale scenarios because of the unmanned aerial vehicle moving at a higher speed without geographical limitation. Moreover, multiple automatic landing wireless charging PADs are deployed to recharge unmanned aerial vehicles automatically. In this work, we investigate the problem of introducing the minimal number of PADs in unmanned aerial vehicle–based wireless rechargeable sensor networks. We propose a novel PAD deployment scheme named clustering-with-double-constraints and disks-shift-combining that can adapt to arbitrary locations of the base station, arbitrary geographic distributions of sensor nodes, and arbitrary sizes of network areas. In the proposed scheme, we first obtain an initial PAD deployment solution by clustering nodes in geographic locations. Then, we propose a center shift combining algorithm to optimize this solution by shifting the location of PADs and attempting to merge the adjacent PADs. The simulation results show that compared to existing algorithms, our scheme can charge the network with fewer PADs.

scholarly journals Hybrid Direction of Arrival Precoding for Multiple Unmanned Aerial Vehicles Aided Non-Orthogonal Multiple Access in 6G Networks

2022 ◽  
Vol 12 (2) ◽  
pp. 895
Author(s):  
Laura Pierucci
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Multiple Access ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Base Station ◽  
Flying Height ◽  
Maximization Problem ◽  
Aerial Vehicles ◽  
Sum Rate ◽  
Hybrid Beamforming

Unmanned aerial vehicles (UAV) have attracted increasing attention in acting as a relay for effectively improving the coverage and data rate of wireless systems, and according to this vision, they will be integrated in the future sixth generation (6G) cellular network. Non-orthogonal multiple access (NOMA) and mmWave band are planned to support ubiquitous connectivity towards a massive number of users in the 6G and Internet of Things (IOT) contexts. Unfortunately, the wireless terrestrial link between the end-users and the base station (BS) can suffer severe blockage conditions. Instead, UAV relaying can establish a line-of-sight (LoS) connection with high probability due to its flying height. The present paper focuses on a multi-UAV network which supports an uplink (UL) NOMA cellular system. In particular, by operating in the mmWave band, hybrid beamforming architecture is adopted. The MUltiple SIgnal Classification (MUSIC) spectral estimation method is considered at the hybrid beamforming to detect the different direction of arrival (DoA) of each UAV. We newly design the sum-rate maximization problem of the UAV-aided NOMA 6G network specifically for the uplink mmWave transmission. Numerical results point out the better behavior obtained by the use of UAV relays and the MUSIC DoA estimation in the Hybrid mmWave beamforming in terms of achievable sum-rate in comparison to UL NOMA connections without the help of a UAV network.

scholarly journals Motion-Encoded Electric Charged Particles Optimization for Moving Target Search Using Unmanned Aerial Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6568
Author(s):  
Mohammed A. Alanezi ◽  
Houssem R. E. H. Bouchekara ◽  
Mohammad S. Shahriar ◽  
Yusuf A. Sha’aban ◽  
Muhammad S. Javaid ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Unmanned Aerial Vehicles ◽  
Optimization Problem ◽  
Charged Particles ◽  
Moving Target ◽  
Moving Targets ◽  
Aerial Vehicles ◽  
Motion Paths ◽  
Moving Target Search ◽  
Different Characteristics

In this paper, a new optimization algorithm called motion-encoded electric charged particles optimization (ECPO-ME) is developed to find moving targets using unmanned aerial vehicles (UAV). The algorithm is based on the combination of the ECPO (i.e., the base algorithm) with the ME mechanism. This study is directly applicable to a real-world scenario, for instance the movement of a misplaced animal can be detected and subsequently its location can be transmitted to its caretaker. Using Bayesian theory, finding the location of a moving target is formulated as an optimization problem wherein the objective function is to maximize the probability of detecting the target. In the proposed ECPO-ME algorithm, the search trajectory is encoded as a series of UAV motion paths. These paths evolve in each iteration of the ECPO-ME algorithm. The performance of the algorithm is tested for six different scenarios with different characteristics. A statistical analysis is carried out to compare the results obtained from ECPO-ME with other well-known metaheuristics, widely used for benchmarking studies. The results found show that the ECPO-ME has great potential in finding moving targets, since it outperforms the base algorithm (i.e., ECPO) by as much as 2.16%, 5.26%, 7.17%, 14.72%, 0.79% and 3.38% for the investigated scenarios, respectively.

scholarly journals Optimization of Base Location and Patrol Routes for Unmanned Aerial Vehicles in Border Intelligence, Surveillance and Reconnaissance

2018 ◽  
Author(s):  
Yao Liu ◽  
Zhong Liu ◽  
Jianmai Shi ◽  
Guohua Wu ◽  
Chao Chen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Base Station ◽  
Base Stations ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Solution Approach ◽  
Location Routing ◽  
Aerial Vehicles

The location routing problem of unmanned aerial vehicles (UAV) in border patrol for intelligence, surveillance and reconnaissance is investigated, where the location of UAV base stations and the UAV flying routes for visiting the targets in border area are jointly optimized. The capacity of the base station and the endurance of the UAV are considered. A binary integer programming model is developed to formulate the problem, and two heuristic algorithms combined with local search strategies are designed for solving the problem. The experiment design for simulating the distribution of stations and targets in border is proposed for generating random test instances. Also, an example based on the Sino-Vietnamese border is presented to illustrate the problem and the solution approach. The performance of the two algorithms are analyzed and compared through randomly generated instances.

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