Unnamed Aerial Vehicles Research Articles

Modeling the Effect of Cell Orientation on the Performance of an Air-Breathing Polymer Electrolyte Fuel Cell with a Columnar Cathode Plate

Air-breathing polymer electrolyte fuel cells (PEMFCs) are expected to play an important role in the development of sustainable portable and mobile devices, such as unnamed aerial vehicles, motorbikes or laptops. In this work, the performance of air-breathing PEMFCs with a columnar cathode plate design is examined by means of a 3D two-phase, non-isothermal model, and compared against experimental data. The results show that the performance is highly influenced by the cell orientation, namely horizontal (material plane perpendicular to gravity) versus vertical (material plane parallel to gravity). Oxygen transport in horizontal cells is mainly dominated by diffusion, leading to oxygen shortage toward the cell center and an inhomogeneous current density distribution. In contrast, oxygen transport in vertical cells is assisted by natural convection, enhancing oxygen transport throughout the cell and increasing the current density homogeneity. Water saturation is preferentially accumulated close to the cell center, being larger in horizontal cells due to the lower water removal rate of the cathode plate.

Modeling the Effect of Cell Orientation on the Performance of an Air-Breathing Polymer Electrolyte Fuel Cell with a Columnar Cathode Plate

Air-breathing polymer electrolyte fuel cells (PEMFCs) are expected to play an important role in the development of sustainable portable and mobile devices, such as unnamed aerial vehicles, motorbikes or laptops. In this work, the performance of air-breathing PEMFCs with a columnar cathode plate design is examined by means of a 3D two-phase, non-isothermal model, and compared against experimental data. The results show that the performance is highly influenced by the cell orientation, namely horizontal (material plane perpendicular to gravity) versus vertical (material plane parallel to gravity). Oxygen transport in horizontal cells is mainly dominated by diffusion, leading to oxygen shortage toward the cell center and an inhomogeneous current density distribution. In contrast, oxygen transport in vertical cells is assisted by natural convection, enhancing oxygen transport throughout the cell and increasing the current density homogeneity. Water saturation is preferentially accumulated close to the cell center, being larger in horizontal cells due to the lower water removal rate of the cathode plate.

Data-Driven Cooperative Multi-Task Assignment in Heterogeneous Multi-Agent Pursuit-Evade Game

In this paper, a task assignment method is proposed to deal with the multi-agent pursuit-evade game for heterogeneous unnamed aerial vehicles via reinforcement learning. The mathematical model based on the local position error dynamics is established to describe the interactions among the vehicles in the pursuit-evade game, subject to high nonlinearities and parameter uncertainties involved in the vehicle model. The execution costs and the corresponding optimal control policies of the agent pursuing each target are calculated, and the policy with minimum execution cost is determined as the objective of the multi-agent pursuit-evade game. Min-Max strategy is introduced to estimate and counteract the interaction effects in the mathematical model, and the reinforcement learning-based algorithm is proposed to obtain the optimal solution to the assignment problem based on the Hamilton–Jacobi–Bellman equation without the interaction effects. Simulation results are given to show the effectiveness of the proposed task assignment method.

UAV technology to support management decision-making in the industry

Purpose: The aim of this article is to define and approach the concept of UAV and its use in industry and decision support in business. Design/methodology/approach: The methodology of the article consisted of comprehensive analysis of the theoretical concept of UAV technology within the case study framework. Findings: Result of this analysis provides an evaluation of the state for implementation as support for decision-making and management of companies that will use this trend in the future. Practical implications: With the progress of science and technology, the individual components of this technology have gradually evolved and become more and more accessible. UAV technology represents great potential in the production processes of factories or smaller factories. Social implications: UAV (Unnamed Aerial Vehicles) technology has been evolving for decades. However, its civilian use and industrial use have only come in recent years. UAV technology represents great potential in manufacturing processes, support other technological trends, such as IoT, 5G, AI, Factory 4.0. Originality/value: The presented paper provide not only practical but also theoretical conclusion to management of production processes of factories or smaller factories. Keywords: management, decision making, UAV technology. Category of the paper: Research paper. Case study.

Long life structural health monitoring of selected bridges

The paper is focused on the structural health monitoring, current methodology of inspection in Slovakia for road and railway bridges. Consequently, the paper presents the advanced methods for monitoring and inspection of bridges using various types of robots and unnamed aerial vehicles. It describes two selected case studies, where all integrated system of structural health monitoring will be applied. Later, it defines the inspection and current condition of road arc bridge with stiffened beams and steel truss bridge.

Use of Unnamed Aerial Vehicles (UAVs) to monitor marine megafauna strandings in beach monitoring programs

Use of Unnamed Aerial Vehicles (UAVs) to monitor marine megafauna strandings in beach monitoring programs

UAVs for traffic monitoring: A sequential game-based computation offloading/sharing approach

Recently, UAVs or Unnamed Aerial Vehicles have been proposed as flexible aerial support to assist ground vehicles for different applications such as rescue and traffic surveillance missions. UAVs can collect different data information about the road/traffic state usually as aerial photography and videos. The processing of this kind of data consists usually on pattern recognition and video processing which are complex tasks that necessitate powerful computing and energy resources. Unfortunately, the moderate UAV's computational and energy capabilities restrict local data processing. Fortunately, UAVs can leverage the computation resources of the surrounding edge network entities to enhance their computational capabilities. In this paper, we aim to achieve efficient data processing for the data collected by UAVs in the context of UAVs-aided vehicular networks for traffic monitoring missions. For this purpose, we propose a new system model where UAVs can offload and/or share intensive computation tasks with other nearby network nodes. Then, we use the computation response time, the energy consumed for the computation, the cost of cellular communication and the computation cost as the main system metrics to make any computation offloading/sharing decisions that optimize the system performance. We then modele the offloading/sharing decision-making problem as a sequential game, where we provide complete proof of the existence of the Nash equilibrium and propose an algorithm to reach such an equilibrium. The simulation results showed that the proposed game-based model outperforms other approaches by delivering better performance in terms of overall system utility with a data processing efficiency that varies between 43% and 97% depending on the computation approach, and provides a more efficient computation time and energy average.

Unsupervised deep learning and semi-automatic data labeling in weed discrimination

In recent years, supervised Deep Neural Networks have achieved the state-of-the-art in image recognition and this success has spread in many areas. In agricultural field, several researches have been conducted using architectures such as Convolutional Neural Networks. Despite this success, these works are still highly dependent on very time–costly manual data labeling. In contrast to this scenario, Unsupervised Deep Learning has no dependency on data labeling and is targeted as the future of the area, but after a promising start has been obfuscated by the success of supervised networks. Meanwhile, the low-cost of acquisition of field crop imagery using Unnamed Aerial Vehicles could be largely boosted in real-world applications if these images could be annotated without the need for a human specialist. In this work, we tested two recent unsupervised deep clustering algorithms, Joint Unsupervised Learning of Deep Representations and Image Clusters (JULE) and Deep Clustering for Unsupervised Learning of Visual Features (DeepCluster), using two public weed datasets. The first dataset was captured in a soybean plantation in Brazil and discriminates weeds between grass and broadleaf. The second dataset consists of 17,509 labeled images of eight nationally significant weed species native to Australia. We evaluated the purely unsupervised clustering performance using the NMI and Unsupervised Clustering Accuracy metrics and analysed the effects of techniques like data augmentation and transfer learning to improve clustering quality in a broad discussion that can be useful for unsupervised deep clustering in general. We also propose the usage of semi-automatic data labeling which greatly reduces the cost of manual data labeling and can be easily replicated to different datasets. This approach achieved 97% accuracy in discrimination of grass and broadleaf while reducing the number of manual annotations by 100 times, using a custom set of training images, without images labeled using inaccurate clusters.

UFPR CampusMap: a laboratory for a Smart City developments

UFPR CampusMap: a laboratory for a Smart City developments

Flying Ad Hoc network (FANET) Communication between UAV's

In FANET network communication is one of the major concern, and also communication between multi-UAV frameworks. The communication is established between UAV's and base terminal through satellite or any other structure. This kind of communication create issue between UAV's, the long distance between UAV's can create blackouts in communication, because of these issues the ad hoc network can be used among the UAV's, this kind of communication network is called FANET. In this paper I will discuss the implementation of the network and how the network structure can provide reliable communication ad transfer of data between the unnamed aerial vehicles UAV's and the base terminals.

Joint Position and Travel Path Optimization for Energy Efficient Wireless Data Gathering Using Unmanned Aerial Vehicles

Unnamed aerial vehicles (UAVs) or drones have attracted growing interest in the last few years for multiple applications; thanks to their advantages in terms of mobility, easy movement, and flexible positioning. In UAV-based communications, mobility and higher line-of-sight probability represent opportunities for the flying UAVs while the limited battery capacity remains its major challenge. Thus, they can be employed for specific applications where their permanent presence is not mandatory. Data gathering from wireless sensor networks is one of these applications. This paper proposes an energy-efficient solution minimizing the UAV and/or sensors energy consumption while accomplishing a tour to collect data from the spatially distributed wireless sensors. The objective is to determine the positions of the UAV “stops” from which it can collect data from a subset of sensors located in the same neighborhood and find the path that the UAV should follow to complete its data gathering tour in an energy-efficient manner. A non-convex optimization problem is first formulated then, an efficient and low-complex technique is proposed to iteratively achieve a sub-optimal solution. The initial problem is decomposed into three sub-problems: The first sub-problem optimizes the positioning of the stops using linearization. The second one determines the sensors assignment to stops using clustering. Finally, the path among these stops is optimized using the travel salesman problem. Selected numerical results show the behavior of the UAV versus various system parameters and that the achieved energy is considerably reduced compared to the one of existing approaches.

Prototype Survey of Path Planning and Obstacle Avoidance in UAV Systems

In recent years, have seen rapidly growing interest with implementation and development of different type of networks of multiple unnamed aerial vehicles (UAV), as aerial sensor networks for inter co-operative monitoring, surveillance monitoring and rapid emergency response for communication. This is an emerging concept in real time communicative networks. Path detection, planning and obstacle avoidance is the aggressive representation for unnamed aerial vehicles in indoor environments. There are many techniques/approaches are introduced to evaluate above features for real time communicative environments. So in this paper, we discuss about those techniques implementation procedure and brief description regarding obstacle avoidance, multi-point interaction to track the location in wireless network communications. This paper analysis most successful path detection, planning and other reference based methods with successive description in real time scenario. Furthermore, a comprehensive with comparable result analysis of each path planning technique by considering their implementation in time complexity and other parameters in real time communicative networks.

The Use of Drones in Spain: Towards a Platform for Controlling UAVs in Urban Environments.

Rapid advances in technology make it necessary to prepare our society in every aspect. Some of the most significant technological developments of the last decade are the UAVs (Unnamed Aerial Vehicles) or drones. UAVs provide a wide range of new possibilities and have become a tool that we now use on a daily basis. However, if their use is not controlled, it could entail several risks, which make it necessary to legislate and monitor UAV flights to ensure, inter alia, the security and privacy of all citizens. As a result of this problem, several laws have been passed which seek to regulate their use; however, no proposals have been made with regards to the control of airspace from a technological point of view. This is exactly what we propose in this article: a platform with different modes designed to control UAVs and monitor their status. The features of the proposed platform provide multiple advantages that make the use of UAVs more secure, such as prohibiting UAVs’ access to restricted areas or avoiding collisions between vehicles. The platform has been successfully tested in Salamanca, Spain.