Implementation Of Unmanned Aerial Vehicle Research Articles

UAV-Embedded Sensors and Deep Learning for Pathology Identification in Building Façades: A Review

The use of geotechnologies in the field of diagnostic engineering has become ever more present in the identification of pathological manifestations in buildings. The implementation of Unmanned Aerial Vehicles (UAVs) and embedded sensors has stimulated the search for new data processing and validation methods, considering the magnitude of the data collected during fieldwork and the absence of specific methodologies for each type of sensor. Regarding data processing, the use of deep learning techniques has become widespread, especially for the automation of processes that involve a great amount of data. However, just as with the increasing use of embedded sensors, deep learning necessitates the development of studies, particularly those focusing on neural networks that better represent the data to be analyzed. It also requires the enhancement of practices to be used in fieldwork, especially regarding data processing. In this context, the objective of this study is to review the existing literature on the use of embedded technologies in UAVs and deep learning for the identification and characterization of pathological manifestations present in building façades in order to develop a robust knowledge base that is capable of contributing to new investigations in this field of research.

Evaluation of the barriers to and drivers of the incorporation of unmanned aerial vehicles into dam asset management

ABSTRACT Dam asset management entails the consistent evaluation of the state and usefulness of dams as tangible assets in terms of their expected lifespan, criticality, operational history, maintenance history, and long-term financing plan. This research aims to identify and evaluate the critical drivers and barriers associated with the use of unmanned aerial vehicles in dam asset management. This study uses rough decision-making trial and evaluation laboratory and interpretive structure modelling to analyze the interactions that take place between the barriers to and the drivers of unmanned aerial vehicles incorporation. To overcome the problem of vagueness, it develops rough set theory to determine the driving and dependence power of the drivers and the barriers, respectively. According to the findings, the most significant barrier to the incorporation of unmanned aerial vehicles into dam asset management is a lack of skilled operators, while the most significant driver of their incorporation is their cost-effectiveness. The findings of this study will be highly valuable to practitioners and government agencies working on the implementation of unmanned aerial vehicles in dam asset management, as they will enable them to correctly assess the different aspects of unmanned aerial vehicles incorporation.

A novel dual-pooling attention module for UAV vehicle re-identification

Vehicle re-identification (Re-ID) involves identifying the same vehicle captured by other cameras, given a vehicle image. It plays a crucial role in the development of safe cities and smart cities. With the rapid growth and implementation of unmanned aerial vehicles (UAVs) technology, vehicle Re-ID in UAV aerial photography scenes has garnered significant attention from researchers. However, due to the high altitude of UAVs, the shooting angle of vehicle images sometimes approximates vertical, resulting in fewer local features for Re-ID. Therefore, this paper proposes a novel dual-pooling attention (DpA) module, which achieves the extraction and enhancement of locally important information about vehicles from both channel and spatial dimensions by constructing two branches of channel-pooling attention (CpA) and spatial-pooling attention (SpA), and employing multiple pooling operations to enhance the attention to fine-grained information of vehicles. Specifically, the CpA module operates between the channels of the feature map and splices features by combining four pooling operations so that vehicle regions containing discriminative information are given greater attention. The SpA module uses the same pooling operations strategy to identify discriminative representations and merge vehicle features in image regions in a weighted manner. The feature information of both dimensions is finally fused and trained jointly using label smoothing cross-entropy loss and hard mining triplet loss, thus solving the problem of missing detail information due to the high height of UAV shots. The proposed method’s effectiveness is demonstrated through extensive experiments on the UAV-based vehicle datasets VeRi-UAV and VRU.

Современные направления в области разработки и создания пожарной техники (часть 1)

Purpose. Demonstrating achievements in the field of fire protection at the largest specialized exhibitions allows manufacturers of firefighting appliances to exchange experiences, as well as to report on the latest developments and their advantages. The article analyzes some samples of appliances presented at the international exhibition “China Fire – 2023” – one of the world largest fire-engineering exhibitions. The target of the study was firefighting appliances and equipment, the scope of the study was engineering innovations in firefighting appliances and equipment. Methods. When writing the article, methods of observation, analysis, and description were used. Findings. Considering the specifics and scale of the exhibition, it is impossible to fully cover all the presented samples of equipment and appliances, however, their selective analysis made it possible to determine the trends for the development of firefighting appliances. The first trend to be concerned is widespread implementation of unmanned aerial vehicles in fire extinguishing process. In addition, there has been an increase in capabilities of appliances developed for urban conditions, caused by emergencies associated with territories underflooding and flooding. Research application field. The results of the study are applicable in the further development of innovative equipment and appliances capable of effectively and safely extinguishing fires and eliminating accidents. Conclusions. Analysis of technical characteristics, design and other features of firefighting equipment and appliances provides an idea of existing innovations and tendencies in this area.

Implementation of Unmanned Aerial Vehicle (UAV) for Slope Mapping

This paper discusses the applications of unmanned aerial vehicle (UAV) for slope mapping and its important parameters including perimeter, area and volume of certain selected areas at Perumahan Taman Gambang Damai in Kuantan Pahang. This study also focused on determining the potential slope hazard based on slope angle. Modern UAV able to take high quality image which essential for the effectiveness and nature of normal mapping output such as Digital Elevation Model (DEM) and Digital Orthophoto. This photo captured by the UAV will later transfer to Agisoft to generate full map of study area. With the help of Global Mapper, the measurement (perimeter, area and volume) of selected study areas can be determined easily and considered as the main interest in this study. In addition, another outcome of this study is, this modern method of mapping helps researchers and engineers to study the possibility of slope hazard based on their respective slope angle (according to slope classes). In conclusion, modern technology of UAV proves to be very effective for mapping in geotechnical engineering. Slope mapping help researchers and engineers to obtain slope measurement within short period of time compare to previous traditional method.

Drones as elements of remote control of the state of geophysical objects

Control of the state of geophysical objects is one of the key components of their further safe operation. But some geophysical objects have areas that cannot be successfully inspected for various reasons. Such missed areas can be in critical condition and significantly affect the final results of the examination. It is possible to solve this issue by implementing methods and means of remote operational non-destructive control of the state of geophysical objects. One such solution is implementation of unmanned aerial vehicles, commonly known as drones. The goal of the work is to find out the possibility of using drones as an element of remote control of the state of geophysical systems in order to eliminate inaccessible areas during the inspection of both on-ground and underground objects and to establish the key parameters of drones for their implementation in the specified role. Drones and areas of their application were used as objects for this research. Two categories of remote control of the state of geophysical objects by drones were defined, followed by technical requirements for drones for each category.

Transport-Associated Vibrational Stress Triggers Drug-Reversible Apoptosis and Cardiac Allograft Failure in Mice.

Increasingly complex and long-range donor organ allocation routes coupled with implementation of unmanned aerial vehicles (UAVs) have prompted investigations of the conditions affecting organs once packaged for shipment. Our group has previously demonstrated that different modes of organ transport exert unique environmental stressors, in particular vibration. Using a mouse heart transplant model, we demonstrated that vibrational forces exert tangible, cellular effects in the form of cardiomyocyte apoptosis and cytoskeletal derangement. Functionally, these changes translated into accelerated allograft loss. Notably, administration of an apoptosis inhibitor, Z-VAD-FMK, helped to ameliorate the detrimental cellular and functional effects of mechanical vibration in a dose-dependent manner. These findings constitute one of the first reports of the negative impact of transit environment on transplant outcomes, a contributing mechanism underpinning this effect, and a potential agent to prophylax against this process. Given current limitations in measuring donor organ transit environments in situ, further study is required to better characterize the impact of transport environment and to potentially improve the care of donor organs during shipment. Clinical and Translational Impact Statement: We show that apoptosis inhibitor, Z-VAD-FMK, ameliorated transport-related vibrational stress in murine heart transplants, which presents a potential therapeutic or preservation solution additive for future use in transporting donor organs.

Critical success factors for implementation of Unmanned Aerial Vehicles (UAVs) in construction

Critical success factors for implementation of Unmanned Aerial Vehicles (UAVs) in construction

Estimating the performance of multi-rotor unmanned aerial vehicle structure-from-motion (UAVsfm) imagery in assessing homogeneous and heterogeneous forest structures: a comparison to airborne and terrestrial laser scanning

The implementation of Unmanned Aerial Vehicles (UAVs) and Structure-from-Motion (SfM) photogrammetry in assessing forest structures for forest inventory and biomass estimations has shown great promise in reducing costs and labour intensity while providing relative accuracy. Tree Height (TH) and Diameter at Breast Height (DBH) are two major variables in biomass assessment. UAV-based TH estimations depend on reliable Digital Terrain Models (DTMs), while UAV-based DBH estimations depend on reliable dense photogrammetric point cloud. The main aim of this study was to evaluate the performance of multi-rotor UAV photogrammetric point cloud in estimating homogeneous and heterogeneous forest structures, and their comparison to more accurate LiDAR data obtained from Aerial Laser Scanners (ALS), Terrestrial Laser Scanners (TLS), and more conventional means like manual field measurements. TH was assessed using UAVSfM and LiDAR point cloud derived DTMs, while DBH was assessed by comparing UAVSfM photogrammetric point cloud to LiDAR point cloud, as well as to manual measurements. The results obtained in the study indicated that there was a high correlation between UAVSfM TH and ALSLiDAR TH (R2 = 0.9258) for homogeneous forest structures, while a lower correlation between UAVSfM TH and TLSLiDAR TH (R2 = 0.8614) and UAVSfM TH and ALSLiDAR TH (R2 = 0.8850) was achieved for heterogeneous forest structures. A moderate correlation was obtained between UAVSfM DBH and field measurements (R2 = 0.5955) for homogenous forest structures, as well as between UAVSfM DBH and TLSLiDAR DBH (R2 = 0.5237), but a low correlation between UAVSfM DBH and UAVLiDAR DBH (R2 = 0.1114). The study demonstrated that UAV acquired imagery can be used to accurately estimate TH in both forest types, but has challenges estimating DBH. The research does not suggest that UAVSfM serves as a replacement for more high-cost and accurate LiDAR data, but rather as a cheaper adequate alternative in forestry management depending on accuracy requirements.

Effects of Flight and Smoothing Parameters on the Detection of Taxus and Olive Trees with UAV-Borne Imagery

Recent technical and jurisdictional advances, together with the availability of low-cost platforms, have facilitated the implementation of unmanned aerial vehicles (UAVs) in individual tree detection (ITD) applications. UAV-based photogrammetry or structure from motion is an example of such a low-cost technique, but requires detailed pre-flight planning in order to generate the desired 3D-products needed for ITD. In this study, we aimed to find the most optimal flight parameters (flight altitude and image overlap) and processing options (smoothing window size) for the detection of taxus trees in Belgium. Next, we tested the transferability of the developed marker-controlled segmentation algorithm by applying it to the delineation of olive trees in an orchard in Greece. We found that the processing parameters had a larger effect on the accuracy and precision of ITD than the flight parameters. In particular, a smoothing window of 3 × 3 pixels performed best (F-scores of 0.99) compared to no smoothing (F-scores between 0.88 and 0.90) or a window size of 5 (F-scores between 0.90 and 0.94). Furthermore, the results show that model transferability can still be a bottleneck as it does not capture management induced characteristics such as the typical crown shape of olive trees (F-scores between 0.55 and 0.61).

Performance analysis of a UAV-based IRS-assisted hybrid RF/FSO link with pointing and phase shift errors

Intelligent reflecting surface (IRS)-assisted wireless communication has recently become a promising technology to relax the line-of-sight requirement and also to provide a communication link in uncovered and remote areas. In this work, an alternate implementation of unmanned aerial vehicle (UAV)-based IRS-assisted hybrid free space optics/radio frequency wireless communications is presented. Phase shift errors occur due to the presence of reflecting elements in the IRS and affect the reflected beam. We consider the effect of phase shift error along with atmospheric turbulence, which is modeled as gamma-gamma distribution. Furthermore, a statistical model is considered for pointing errors due to the position and orientation fluctuation of the mounted IRS on the UAV. We derive closed-form expressions of the average symbol error rate and spectral efficiency of the considered system, under the combined effects of atmospheric turbulence, pointing error, and phase shift error. In addition, we present asymptotic analysis of the average symbol error rate of the system in a high SNR region and evaluate the diversity order and coding gain. The derived results are further validated using Monte Carlo simulation.

Assessing the factors affecting implementation of unmanned aerial vehicles in Indian humanitarian logistics: a g-DANP approach

PurposeThe purpose of this paper is to analyze the factors affecting the implementation of unmanned aerial vehicles (UAVs) in Indian humanitarian logistics. The factors listed are significant as they are hindering the incorporation of this new technology into the humanitarian supply chain, thus creating inefficiencies in the humanitarian logistics sector.Design/methodology/approachThis research is approached using a two-step process. In the first step, the particular barriers for UAV implementation are determined by a literature review and consultation with experts. Next, the proposed framework, a combination of grey-decision-making trial and evaluation laboratory (grey-DEMATEL) and analytic network process (ANP), i.e. g-DANP, is used to determine a hierarchical structure for the factors and sub-factors. The grey hypothesis provides sufficient analytical data to an otherwise lacking DEMATEL technique. Also, the use of ANP gives weightage to each factor, allowing us to categorize their importance further.FindingsThis study reveals that factors like expensive commercial solutions and high transport energy costs are significant factors of the “cause” group, whereas the uncertain cost for maintenance and repair and deficiency of high-level computing are crucial factors of the “effect” category. The mentioned factors, along with many others, are the main reasons for the delayed incorporation of UAVs in humanitarian logistics.Practical implicationsThe results of this study present insights for humanitarian supply chain managers, UAV producers and policymakers. Those in the humanitarian logistics sector can use the findings of this study to plan for various challenges faced as they try and implement UAVs in their supply chain.Originality/valueThis research is unique as it analyses the general factors hindering the implementation of UAVs in Indian humanitarian logistics. The study enriches existing literature by providing an analytic approach to determine the weightage of various interrelations between the identified factors affecting UAV incorporation in the humanitarian supply chain.

UAV-Enabled Subsurface Characterization Using Multichannel Analysis of Surface Waves

AbstractThe implementation of unmanned aerial vehicles (UAVs) in civil engineering has primarily focused on remote sensing using optical cameras, light detection and ranging (LiDAR), and communicat...

Primena hibridnog modela fuzzy AHP - VIKOR u izboru bespilotne letelice za potrebe taktičkih jedinica oružanih snaga

Unmanned aerial vehicles represent an indispensable segment in the range of weapons of both military and police units. The expansion in development of unmanned aerial vehicles for both commercial and military purposes has created a need for constant improvement of drones and anti-drone means. A wide range of possibilities opens up a wide range of uses for them. The paper presents the choice of an unmanned aerial vehicle as an important combat system for the needs of tactical units of the army and police. The complexity of the problem is conditioned by various tactical-technical and economic characteristics of unmanned aerial vehicles, it has conditioned the use of different methods of multicriteria decision making. A hybrid model of multicriteria decision making fuzzy AHP-VIKOR was used to select the unmanned aerial vehicle for the needs of tactical units. Criteria of importance for the selection of an unmanned aerial vehicle for the needs of tactical units have been defined on the basis of which the most optimal solution (unmanned aerial vehicle) has been selected. The criteria are defined on the basis of tactical-technical and economic characteristics of unmanned aerial vehicles. The calculation of the weight coefficients of the defined criteria was performed using the fuzzy AHP method, while the selection of the drone (the most favorable alternative) based on the defined criteria was performed using the VIKOR method. The obtained result represents the starting point for further research and implementation of unmanned aerial vehicles in tactical units of the army and police.

Kinematics and Plane Decomposition Algorithm for Non Linear Path Planning Navigation and Tracking of Unmanned Aerial Vehicles

Online planned course of the flight and obstacle avoidance are the major issues of exploitation faced in the real time implementation of Unmanned Aerial Vehicles (UAVs). The main application that are used in the UAV are path planning navigation and tracking. Our project uses two algorithms to derive the navigation control laws. The algorithms such as kinematics based algorithm and plane decomposition algorithm. The control laws rely on the two factors namely, proportionality and derivation factors. These factors guide the UAV in reaching the goal in a nonlinear path successfully. The surveillance mode and obstacle avoidance mode are taken as the important consideration in our project. In the surveillance mode UAV reaches the goal in the three dimensional space with the aid of navigation laws. In obstacle avoidance function, the obstacles are avoided in the course of its path of the flight and attains the destination with the navigation laws’ assistance. The kinematics rules leads to the successful application of tracking and navigation of UAV in nonlinear path planning.

Ananas comosus crown image thresholding and crop counting using a colour space transformation scheme

The implementation of unmanned aerial vehicle (UAV) technology having image processing capabilities provides an alternative way to observe pineapple crowns captured from aerial images. In the majority of pineapple plantations, an agricultural officer will physically count the crop yield prior to harvesting the Ananas Comosus, also known as pineapple. This process is particularly evident in large plantation areas to accurately identify pineapple numbers. To alleviate this issue, given it is both time-consuming and arduous, automating the process using image processing is suggested. In this study, the possibilities and comparisons between two techniques associated with an image thresholding scheme known as HSV and L*A*B* colour space schemes were implemented. This was followed by determining the threshold by applying an automatic counting (AC) method to count the crop yield. The results of the study found that by applying colour thresholding for segmentation, it improved the low contrast image due to different heights and illumination levels on the acquired colour image. The images that were acquired using a UAV revealed that the best distance for capturing the images was at the height of three (3) metres above ground level. The results also confirm that the HSV colour space provides a more efficient approach with an average error increment of 47.6% when compared to the L*A*B*colour space.

Implementation of Unmanned Aerial Vehicle for Cadastral Mapping

Unmanned Aerial Vehicle (UAV) as a photogrammetric platform provides a new domain for engineers and geospatial professionals with a revolutionary tool for collecting a reliable geodata to be implemented for cadastral mapping. The aim of this study was to find the potential of UAV for cadastral mapping using high resolution aerial images. The study included the utilize of eBee PLUS fixed wing UAV flying at 106m altitude over Arab-Kand village. At the GSD of 2.5cm/pixel spatial resolution the site was covered by UAV images of forward and lateral overlap of 60% and 70% respectively. Horizontal accuracy obtained from generated orthomosaic was 4.8cm. This gives a possibility to create a line map with scale of 1:100 or 1:50. This study proved that the UAV based orthomosaic can be used for cadastral mapping due to high accuracy, low cost, less time consuming, rapid data acquisition, and complying with international standards.

Overview of the Development of the Maritime Search and Rescue System in Croatia

According to the Convention for the Safety of Life at Sea and International Convention on Maritime Search and Rescue, saving human lives at sea is the duty of all signatory states. This paper analyzes and gives an overview of previous research activities in search and rescue system at sea and how the use of unmanned aerial vehicles (UAV) can improve search and rescue actions at sea. Research activities include development of the search system and placement of resources that are used in search and rescue actions (ships, planes etc.). Previous research is mainly related to minimizing response time when accidents at sea are detected in relation to search and rescue missions. Implementation of unmanned aerial vehicles into the search and rescue system enables improvement of these actions due to earlier detection and verification of accidents at sea and prevents unnecessary search and rescue units engagement in cases when an accident did not occur. The results of previous research point to the fact that future research should aim to explore the synthesis of unmanned aerial vehicles with the existing search and rescue system at sea in Croatia.

Media framing the reception of unmanned aerial vehicles in the United States of America

When the United States Congress mandated implementation of unmanned aerial vehicles (UAVs) into the domestic airspace in 2012, there was substantial opposition to the policy change. Critics expressed fears regarding their threat to privacy and safety, and legislatures considered numerous bills that would significantly limit or even ban domestic unmanned flight. UAV advocates used various methods to counter UAV's negative image.This study examines media stories regarding UAVs over a four-year period (2011–2014) and demonstrates that despite the backlash against expansion, media frames emphasizing benefit rather than risk dominated in the U.S. media. The economic opportunities presented by UAVs appeared in most media reports and over time reports increased of relatively noncontroversial applications, such as agriculture. Citizen advocacy or frames that emphasized the personal freedom to fly a UAV also increased. Industry and university officials, who usually support expansion, were the most frequent sponsors of media statements. The framing of media reports can influence public debate. Potential risks of a new technology can be amplified or minimized depending on how the media present the issue to the public.

Performance Analysis in Object Diameter Estimation based on Single and Multiple Non-Destructive and Discrete Infrared Sensors

In Simultaneous Localization and Mapping (SLAM) technique, recognizing and marking the landmarks in the environment is very important. Therefore, in a commercial farm, rows of trees, borderline of rows as well as the trees and other features are mostly used by the researchers in realizing the automation process in this field. In this paper, the detection of the tree based on its diameter is focused. There are few techniques available in determining the size of the tree trunk inclusive of the laser scanning method as well as image-based measurements. However, those techniques require heavy computations and equipments which become constraints in a lightweight unmanned aerial vehicle implementation. Therefore, in this paper, the detection of an object by using a single and multiple infrared sensors on a non-stationary automated vehicle platform is discussed. The experiments were executed on different size of objects in order to investigate the effectiveness of this proposed method. This work is initially tested on the ground, based in the lab environment by using an omni directional vehicle which later will be adapted on a small-scale unmanned aerial vehicle implementation for tree diameter estimation in the agriculture farm. In the current study, comparing multiple sensors with single sensor orientation showed that the average percentage of the pass rate in the pole recognition for the former is relatively more accurate than the latter with 93.2 percent and 74.2 percent, respectively.