Hovering Time Research Articles

Adaptive Clustering and Scheduling for UAV-Enabled Data Aggregation

Using unmanned aerial vehicles (UAVs) is an effective way to gather data from Internet of Things (IoT) devices. To reduce data gathering time and redundancy, thereby enabling the timely response of state-of-the-art systems, one can partition a network into clusters and perform aggregation within each cluster. Existing works solved the UAV trajectory planning problem, in which the energy consumption and/or flight time of the UAV is the minimization objective. The aggregation scheduling within each cluster was neglected, and they assumed that data must be ready when the UAV arrives at the cluster heads (CHs). This paper addresses the minimum time aggregation scheduling problem in duty-cycled networks with a single UAV. We propose an adaptive clustering method that takes into account the trajectory and speed of the UAV. The transmission schedule of IoT devices and the UAV departure times are jointly computed so that (1) the UAV flies continuously throughout the shortest path among the CHs to minimize the hovering time and energy consumption, and (2) data are aggregated at each CH right before the UAV arrival, to maximize the data freshness. Intensive simulation shows that the proposed scheme reduces up to 35% of the aggregation delay compared to other benchmarking methods.

Research on insect-like long endurance hovering double-wing FMAV prototype

PurposeEndurance time is an important factor limiting the progress of flapping-wing aircraft. In this study, this paper developed a prototype of a double-wing flapping-wing micro air vehicle (FMAV) that mimics insect-scale flapping wing for flight. Besides, novel methods for optimal selection of motor, wing length and battery to achieve prolonged endurance are proposed. The purpose of this study is increasing the flight time of double-wing FMAV by optimizing the flapping mechanism, wings, power sources, and energy sources.Design/methodology/approachThe 20.4 g FMAV prototype with wingspan of 21.5 cm used an incomplete gear flapping wing mechanism. The motor parameters related to the lift-to-power ratio of the prototype were first identified and analyzed, then theoretical analysis was conducted to analyze the impact of wing length and flapping frequency on the lift-to-power ratio, followed by practical testing to validate the theoretical findings. After that, analysis and testing examined the impact of battery energy density and efficiency on endurance. Finally, the prototype’s endurance duration was calculated and tested.FindingsThe incomplete gear facilitated 180° symmetric flapping. The motor torque constant showed a positive correlation with the prototype’s lift-to-power ratio. It was also found that the prototype achieved the best lift-to-power ratio when using 100 mm wings.Originality/valueA gear-driven flapping mechanism was designed, capable of smoothly achieving 180° symmetric flapping. Besides, factors affecting long-duration flight – motor, wings and battery – were identified and a theoretical flight duration analysis method was developed. The experimental result proves that the FMAV could achieve the longest hovering time of 705 s, outperforming other existing research on double-wing FMAV for improving endurance.

Sizing of Multicopter Air Taxis—Weight, Endurance, and Range

In the near future, urban air mobility (UAM) will let an old dream of human society come true: affordable and fast air transportation for almost everyone. Among the various existing designs, the multicopter configuration best combines the advantages of compactness, simplicity, and maturity. These aspects are important for actual use, particularly during the early stage of this market. This study elaborates on the design principles of UAM multicopters by examining existing models in terms of their configuration, weight, and range specifications. In particular, the weights of the different components are estimated based on empirical models, aerodynamic fundamentals for the analysis of UAM multicopters are derived from momentum theory, and the power and energy requirements for hovering and cruise flight are evaluated, thereby enabling estimation of the maximum hovering time and flight range. Finally, a sizing method is introduced and validated against an actual UAM design.

Multiobjective trajectory optimization algorithms for solving multi-UAV-assisted mobile edge computing problem

The Internet of Things (IoT) devices are not able to execute resource-intensive tasks due to their limited storage and computing power. Therefore, Mobile edge computing (MEC) technology has recently been utilized to provide computing and storage capabilities to those devices, enabling them to execute these tasks with less energy consumption and low latency. However, the edge servers in the MEC network are located at fixed positions, which makes them unable to be adjusted according to the requirements of end users. As a result, unmanned aerial vehicles (UAVs) have recently been used to carry the load of these edge servers, making them mobile and capable of meeting the desired requirements for IoT devices. However, the trajectories of the UAVs need to be accurately planned in order to minimize energy consumption for both the IoT devices during data transmission and the UAVs during hovering time and mobility between halting points (HPs). The trajectory planning problem is a complicated optimization problem because it involves several factors that need to be taken into consideration. This problem is considered a multiobjective optimization problem since it requires simultaneous optimization of both the energy consumption of UAVs and that of IoT devices. However, existing algorithms in the literature for this problem have been based on converting it into a single objective, which may give preference to some objectives over others. Therefore, in this study, several multiobjective trajectory planning algorithms (MTPAs) based on various metaheuristic algorithms with variable population size and the Pareto optimality theory are presented. These algorithms aim to optimize both objectives simultaneously. Additionally, a novel mechanism called the cyclic selection mechanism (CSM) is proposed to manage the population size accurately, optimizing the number of HPs and the maximum function evaluations. Furthermore, the HPs estimated by each MTPA are associated with multiple UAVs using the k-means clustering algorithm. Then, a low-complexity greedy mechanism is used to generate the order of HPs assigned to each UAV, determining its trajectory. Several experiments are conducted to assess the effectiveness of the MTPAs with variable population size and cyclic selection mechanisms. The experimental findings demonstrate that the MTPAs with the cyclic selection mechanism outperform all competing algorithms, achieving better outcomes.

Unmanned Aerial Vehicles (UAVs) in Landslide Investigation and Monitoring: A Review

Over the past decade, Unmanned Aerial Vehicles (UAVs) have emerged as essential tools for landslide studies, particularly in on-site investigations. This paper reviews UAV applications in landslide studies, with a focus on static geological characteristics, monitoring temporal and spatial dynamics, and responses post-events. We discuss the functions and limitations of various types of UAVs and sensors (RGB cameras, multi-spectral cameras, thermal IR cameras, SAR, LiDAR), outlining their roles and data processing methods in landslide applications. This review focuses on the UAVs’ roles in landslide geology surveys, emphasizing landslide mapping, modeling and characterization. For change monitoring, it provides an overview of the temporal and spatial evolution through UAV-based monitoring, shedding light on dynamic landslide processes. Moreover, this paper underscores UAVs’ crucial role in emergent response scenarios, detailing strategies and automated detection using machine learning algorithms. The discussion on challenges and opportunities highlights the need for ongoing UAV technology advancements, addressing regulatory hurdles, hover time limitations, 3D reconstruction accuracy and potential integration with technologies like UAV swarms.

Wireless sensing charging based on multi‐drone cooperation

AbstractIn recent years, wireless charging technology is widely used for sensor charging. Though carts equipped with wireless charging tools were able to reach sensor nodes and continuously recharge them, their applications are limited and could not be used in many territories such as rugged mountainous terrain and severely damaged disaster areas. With the significant cost reduction of UAVs due to the mature technology, using UAVs to replace charging carts for wireless sensor networks is a future trend. In this study, the problem of energy replenishment and path planning for large‐scale wireless sensor networks by multiple UAVs is considered. First, sensor nodes are distributed evenly by using an improved k‐means clustering algorithm, modelling the problem of the UAV traversal over a certain range of sensors as a travelling salesman problem. Then, a heuristic algorithm is proposed to solve the path planning of UAVs and the hovering time at each sensor. The simulations show the effect of different charging ratios r on the number of non‐functional nodes and the loss of the UAV. The experimental results show that the proposed algorithm is able to plan a sensible path for the UAV, which leads to a smaller UAV energy loss and a smaller number of non‐functional nodes.

Enhancement of chaotic mixing performance in laminar flow with reciprocating and rotating coupled agitator

In this study, a reciprocating and rotating coupled agitator was proposed to enhance the quality of the liquid–liquid mixing state in a laminar flow, and validated using experimental and numerical approaches. The effects of impeller amplitude (Ai), impeller reciprocating speed (vi), and impeller hovering time (ti) at a constant rotating speed on the mixing effect were studied. The results showed that the mixing effect of this agitator was much superior to that of a traditional rotating agitator under proper parameters. Under the impeller reciprocating motion, a large-scale vortex is generated under the impeller, which can significantly enhance the mixing effect. The mixing efficiency under the best mixing condition (Ai = 0.05 m, vi = 0.005 m/s, ti = 15 s) in the experiment is 4.71 times than that of the traditional agitator.

Solar Powered UAV-Mounted RIS Networks

To compensate for severe blockages and achieve flexible and pervasive network access, UAV-mounted RISs have recently attracted research interest. In this work, a solar-powered UAV-mounted RIS (SUR) system is investigated, where solar cells are utilized to provide supplementary propulsion power. To maximize the energy efficiency of the SUR system, the optimal joint active and passive beamforming, as well as the energy-constrained UAV trajectory, i.e., its velocity and placement, are derived in closed form. Furthermore, subject to the size, weight, and power limitations of the UAV, the number of reflecting elements, the flying and hovering time of the SUR system are also optimized. Finally, simulations are provided to demonstrate the effectiveness of the proposed SUR system.

Design and Experiment of Ecological Plant Protection UAV Based on Ozonated Water Spraying

With the development of pesticide substitution technology, ozonated water has been gradually applied in agricultural plant protection. This paper describes our development of an ecological plant protection unmanned aerial vehicle (UAV) that can produce and spray ozonated water while flying. Firstly, this paper carries out the design of the ozonated water system, including the selection of the ozone generator and the gas-liquid mixing method. Secondly, the conceptual design method of the ecological plant protection UAV is introduced, including total weight estimation, propulsion system selection, layout and structure design, battery modeling, center of gravity evaluation, and control system. Then, static analysis was computed in ANSYS Workbench on the UAV fuselage. Finally, the field test verified that the hovering time of the UAV could reach the design requirement of 10 min when it was fully loaded. The effective spraying width (with a height of 2 m and a speed of 3 m/s) is 5.25 m. The UAV was used to spray ozonated water with a concentration of 17 ppm continuously once a day; on day 7, the control effect could reach 76.4% and the reduction rate of the larvae population was 59.3%. Therefore, spraying ozonated water with a concentration of 17 ppm every day by using the ecological plant protection UAV can effectively control broccoli diamondback moth larvae and achieve the control effect of traditional pesticides (Chlorantraniliprole SC).

Energy Minimization in RIS-Assisted UAV-Enabled Wireless Power Transfer Systems

Unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) systems offer significant advantages in coverage and deployment flexibility, but suffer from endurance limitations due to the limited onboard energy. This paper proposes to improve the energy efficiency of UAV-enabled WPT systems with multiple ground sensors by utilizing reconfigurable intelligent surface (RIS). Specifically, the total energy consumption of the UAV is minimized, while meeting the energy requirement of each sensor. Firstly, we consider a fly-hover-broadcast (FHB) protocol, in which the UAV radiates radio frequency (RF) signals only at several hovering locations. The energy minimization problem is formulated to jointly optimize the UAV’s trajectory, hovering time and the RIS’s reflection coefficients. To solve this complex non-convex problem, we propose an efficient algorithm. Specifically, the successive convex approximation (SCA) framework is adopted to jointly optimize the UAV’s trajectory and hovering time, in which a minorization-maximization (MM) algorithm that maximizes the minimum charged energy of all sensors is provided to update the reflection coefficients. Then, we investigate the general scenario in which the RF signals are radiated during the flight, aiming to minimize the total energy consumption of the UAV by jointly optimizing the UAV’s trajectory, flight time and the RIS’s reflection coefficients. By applying the path discretization (PD) protocol, the optimization problem is formulated with a finite number of variables. A high-quality solution for this more challenging problem is obtained. Finally, our simulation results demonstrate the effectiveness of the proposed algorithm and the benefits of RIS in energy saving.

IoT-Aerial Base Station Task Offloading With Risk-Sensitive Reinforcement Learning for Smart Agriculture

Aerial base stations (ABSs) allow smart farms to offload processing responsibility of complex tasks from internet of things (IoT) devices to ABSs. IoT devices have limited energy and computing resources, thus it is required to provide an advanced solution for a system that requires the support of ABSs. This paper introduces a novel multi-actor-based risk-sensitive reinforcement learning approach for ABS task scheduling for smart agriculture. The problem is defined as task offloading with a strict condition on completing the IoT tasks before their deadlines. Moreover, the algorithm must also consider the limited energy capacity of the ABSs. The results show that our proposed approach outperforms several heuristics and the classic Q-Learning approach. Furthermore, we provide a mixed integer linear programming solution to determine a lower bound on the performance, and clarify the gap between our risk-sensitive solution and the optimal solution, as well. The comparison proves our extensive simulation results demonstrate that our method is a promising approach for providing a guaranteed task processing services for the IoT tasks in a smart farm, while increasing the hovering time of the ABSs in this farm.

Energy-Efficient UAV-Based IoT Communications With WiFi Suppression in 5 GHz ISM Bands

Unmanned Aerial Vehicle (UAV) based communication is a promising technology for offering wireless communication services. UAVs can typically be adopted as aerial base stations to collect data from ground Internet of Things (IoT) devices. However, the Ground-to-Air link of UAV-based IoT communications is prone to be interfered by surrounding WiFi devices in the Industrial, Scientific, Medical (ISM) band. This paper aims to enable reliable uplink communications for IoT devices in 5 GHz ISM bands, thereby reducing the hover time and energy consumption of the UAV. To this end, we first study and design suppression frames suitable for WiFi devices. Then a suppression method is proposed, which is shown to be effective for all the tested devices, based on emulation performance verification of the frames for multiple commercial off-the-shelf (COTS) WiFi devices. Moreover, by taking the energy consumption of the UAV and multiple transmission parameters of the suppression method into account, we formulate an optimization problem for the desired uplink, which is designed to minimize the energy consumption of the UAV, under the constraints of satisfying the link channel capacity. Given that the optimization problem is non-convex mixed-integer nonlinear programming, this paper proposes an efficient algorithm that takes advantage of the suppression performance of the utilized frames. Numerical simulations demonstrate the performance of the proposed algorithm in terms of the WiFi device density, UAV weight, channel capacity requirement and parameters of the suppression method. The communication quality of the desired Ground-to-Air link is shown to be significantly improved, while the consumed energy is demonstrated to be obviously reduced.

Endurance estimation in hovering flight based on battery power requested on quadcopter UAV

In this era, Unmanned Air Vehicle (UAV) application is growing. However, there are still weaknesses in using UAVs to carry out certain missions. One of the major problems is the energy and power required to use the UAV which impacts the endurance of a UAV can hover. This study focuses on calculating the endurance and finding which configuration will produce the optimal endurance. It starts by calculating the thrust of a propeller using blade element theory which ends in calculating endurance. Using four different types of propellers, an integral formulation was devised for a constant–power battery discharge process to predict the hovering time. The result shows that APC 1238 combined with battery 6S will produce the longest endurance. The methodology is applicable for a custom quadcopter UAV.

Experimental investigation to understand robust design with paper helicopter

Paper helicopter is an inexpensive model and the simplest one used to study the motion of a freely falling rotating body. The behavior of a fixed axis autorotating wing is studied in the present study. The auto rotation of paper helicopter is analyzed through experimental studies by varying the number of blades, aspect ratio and thickness of paper. The study is conducted by dropping the models from pre-defined height in a closed environment to reduce the gust related errors. The aspect ratio, number of blades and thickness are varied, and the optimized model is analyzed. It is found that reducing the number of blades and aspect ratio is preferable to have higher hovering time in airspace with less thickness of the propeller blades. From the study, it is found that 2-bladed propellers having aspect ratio of 0.25 with less thickness exhibits a better hovering time than other models considered.

Analytical Evaluation of Power-Amplifier-Based Charging Methodology and Energy Efficiency Optimization Framework for Aerial Base Stations

In this article, a radio-frequency (RF) power-amplifier (PA) system configuration for the on-board energy conversion is proposed for unmanned aerial vehicle base station’s (UAV-BS’s) battery charging. First, the PA system utilizes the internal RF source for energy conversion so that perpetual battery charging is possible without external power sources. Therefore, a continuous battery charging of the UAV-BS is possible while providing wireless network coverage by hovering over the target location. In addition, the proposed PA system offers a higher RF power control resolution than the existing PA works, which is desirable for precise power control of the UAV-BS. The objective of simultaneous RF power control and battery charging by the PA system is achieved by activating one Wilkinson power divider (WPD) with a specific power splitting ratio in the power divider bank. The simulations show that the dynamic activation of ten distinct unequal split WPDs of the proposed PA system improves the RF power control resolution by $157$ and $396{\,}\%$ compared to the existing PAs. Additionally, the simulations show that the PA’s power added efficiency fluctuation is reduced by $54$ and $82{\,}\%$ compared to the existing PAs. In addition, it will be shown that the proposed on-board battery charging increases the hovering time by $7.4{\,}\%$. Furthermore, an energy-efficiency optimization framework for UAV-BS’s is proposed considering real-world communication system’s hardware imperfections, and the proposed result suggests that UAV-BS’s flight time may decrease by $50{\,}\%$ depending upon the type of UAV-BS RF components.

Shooting Utility Maximization in UAV-Assisted Wireless Camera Sensor Networks.

Recently, wireless camera sensor networks (WCSNs) have entered an era of rapid development, and WCSNs assisted by unmanned aerial vehicles (UAVs) are capable of providing enhanced flexibility, robustness and efficiency when executing missions such as shooting targets. Existing research has mainly focused on back-end image processing to improve the quality of captured images, but it has neglected the question of attaining quality images on the front-end, which is significantly influenced by the location and hovering time of the UAV. Therefore, in this paper, we conceive a novel shooting utility model to quantify shooting quality, which is maximized by simultaneously considering the UAV’s trajectory planning, hovering time and shooting point selection. To expound further, we prove the submodularity of the utility function, whereby the original problem can be expressed as a submodular maximization problem with path constraints, and we propose a utility-cost ratio (UCR) algorithm to maximize shooting utility through two-level optimization. Then, by using the relaxation of the cost function, we analyze the gap between the proposed algorithm and the optimal algorithm (OPT) and prove that the UCR algorithm has a bi-criterion approximation ratio of . Simulation results show that the algorithm outperforms both the random algorithm (RAN) and the maximum shooting utility point selection algorithm (MSU) in terms of shooting utility and time utilization efficiency, improving shooting utility by 51% and 21% compared to the RAN and MSU algorithms, respectively, and achieving at least 88.2% of the OPT algorithm in terms of time utilization efficiency.

The use of a multistage gearbox in an electric drive on quadcopters

The purpose of the work is to develop a multistage gearbox for quadcopters with an additional mass of approximately 700 g, for example: a topographic camera, a small parcel, or, as in the case under consideration, anti-radiation protection and a sensor for measuring radiation levels. We will develop such an electric drive that will ensure the preservation of maximum speed and maximum speeds of climb and descent, as well as select a new battery to preserve such characteristics as maximum range and altitude, maximum flight time and maximum hover time. The article discusses the main stages of selecting the components of an electric drive, taking into account their mass in the required thrust, to ensure the functioning of an average quadcopter upgraded for the study of a radiation-contaminated area. An example of solving the problem of insufficient traction of electric drives is considered. Comparing the use of a multistage drive with the traditional use of an engine without a gearbox on quadcopters, it is worth noting that a multistage drive is more technologically expensive, as well as has a large mass, but at the same time it provides higher useful thrust than most engines used on modern quadcopters. Also, the advantage of the developed drive is the protection of the motor board from radiation by the housing and gearbox, which increases the service life of the quadcopter in the conditions under consideration.

Application of macrolayer dryout model for the critical current density of water electrolysis

Electrochemical hydrogen evolving system such as the water electrolysis has the upper operation limit called critical current density (CCD) when the hydrogen film was formed on the surface as the vapor film in the critical heat flux (CHF) condition. This paper tried to apply one of the well-accepted CHF models, macrolayer dryout model to elucidate CCD phenomenon, which is a novel attempt to predict the CCD using the CHF model based upon the hydrodynamic nature of the phenomena. Hydrogen bubble behaviors at around the CCD were observed and compared with those of the CHF. At high nucleate bubble regime, presence of the macrolayer in the hydrogen evolving system was confirmed. Above this layer, hydrogen bubble cluster is generated and detached from the surface. At the CCD point, the nucleate bubbles adjacent to the surface started to coalescence and subsequently formed a hydrogen film. Based on the photographic analyses, the thickness of the macrolayer and the hovering time of the hydrogen bubble cluster were estimated. Application of these parameters to the existing macrolayer dryout model predicts the CCD well within 4.37%. It is concluded that the hydrodynamics of the CCD and the CHF are quite analogous.

Performance analysis and optimal sizing of electric multirotors

This paper presents an analytical framework for addressing the hovering performance of a battery–powered multirotor. The estimation of power required for flight is investigated and an analytical model is proposed to describe the rotor figure of merit as a function of few relevant blade parameters, without the need for ad hoc experiments. The model is derived after a discussion about the aerodynamics of rotating blades. The formulation in terms of Reynolds number is supported by an experimental campaign, performed on a set of commercial–of–the–shelf propellers optimized for small–scale multirotor applications.By imposing the balance between required and available power, the hovering time is predicted by an integral formulation developed for a constant–power battery discharge process. The best endurance condition is obtained in terms of optimum battery capacity and flight time. The methodology, applicable to the design phase of novel multirotor configurations, is finally validated by flight tests.

Development of optimal scheduling strategy and approach control model of multicopter VTOL aircraft for urban air mobility (UAM) operation

Urban air mobility (UAM) is emerging as a new alternative to solve the traffic problem in the metropolitan area. Industries and government agencies are preparing for the future UAM system and operation. A new ATC (Air Traffic Control) strategy or aircraft separation method that reflects flight characteristics of multicopter VTOL (Vertical Take-off and Landing) aircraft is required. Particularly, approach control around the vertiport is one of the essential issues for the safe and efficient operation of UAM, and strict safety standards are required for service in populated urban areas. In this study, the concept of holding points where multicopter aircraft can hover is introduced, and three scheduling strategies for arriving aircraft are developed and evaluated by comparing the on-time performance (OTP) with hovering time and ground time. BQA (Branch Queuing Approach), SBA (Sequence-based Approach) and, SBAM (sequence-based approach with moving circles) models are proposed and compared. BQA model prioritizes airspace safety by limiting the aircraft’s travel path; SBA model allows the aircraft to move freely within the airspace and prioritizes aircraft’s arrival sequence; and finally, SBAM adds the moving circle concept to the SBA model. For each model, OTP and loss of separation (LOS) risk of the proposed models are found and they are compared by simulations. The simulation result shows that SBA and BQA have similar punctuality performance and BQA model with no LOS risk is the most efficient approach control model for multicopter VTOL aircraft of UAM.