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Drones, Volume 4, Issue 3 (September 2020) – 15 articles

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Open AccessArticle
Virtual Modelling and Testing of the Single and Contra-Rotating Co-Axial Propeller
Drones 2020, 4(3), 42; https://doi.org/10.3390/drones4030042 (registering DOI) - 12 Aug 2020
Abstract
Propellers are a vital component to achieve successful and reliable operation of drones. However, the drone developer faces many challenges while selecting a propeller and a common approach is to perform static thrust measurement. However, the selection of a propeller using a static [...] Read more.
Propellers are a vital component to achieve successful and reliable operation of drones. However, the drone developer faces many challenges while selecting a propeller and a common approach is to perform static thrust measurement. However, the selection of a propeller using a static thrust measurement system is time-consuming. To overcome a need for the static thrust system a virtual model has been developed for measuring both the static and dynamic thrust of a single and coaxial propeller. The virtual model is reliable enough to minimize the need for full-scale tests. The virtual model has been built using two open-source software Qblade and OpenFoam. Qblade is employed to obtain the lift and drag coefficients of the propeller's airfoil section. OpenFoam is utilized to perform the flow simulations of propellers and for obtaining the thrust and torque data of the propeller. The developed virtual model is validated with experimental data and the experimental data are obtained by developing a multi-force balance system for measuring thrusts and torques of a single and a pair of coaxial contra-rotating propellers. The data obtained from the propeller virtual model are compared with the measurement data. For a single propeller, the virtual model shows that the estimated forces are close to the experiment at lower rotational speeds. For coaxial propellers, there are some deviations at the rear propeller due to the turbulence and flow disturbance caused by the front propeller. However, the computed thrust data are still accurate enough to be used in selecting the propeller. The studies indicate that in the future, these virtual models will minimize a need for experimental testing. Full article
Open AccessFeature PaperReview
A Review on Drone-Based Data Solutions for Cereal Crops
Drones 2020, 4(3), 41; https://doi.org/10.3390/drones4030041 (registering DOI) - 12 Aug 2020
Abstract
Food security is a longstanding global issue over the last few centuries. Eradicating hunger and all forms of malnutrition by 2030 is still a key challenge. The COVID-19 pandemic has placed additional stress on food production, demand, and supply chain systems; majorly impacting [...] Read more.
Food security is a longstanding global issue over the last few centuries. Eradicating hunger and all forms of malnutrition by 2030 is still a key challenge. The COVID-19 pandemic has placed additional stress on food production, demand, and supply chain systems; majorly impacting cereal crop producer and importer countries. Short food supply chain based on the production from local farms is less susceptible to travel and export bans and works as a smooth system in the face of these stresses. Local drone-based data solutions can provide an opportunity to address these challenges. This review aims to present a deeper understanding of how the drone-based data solutions can help to combat food insecurity caused due to the pandemic, zoonotic diseases, and other food shocks by enhancing cereal crop productivity of small-scale farming systems in low-income countries. More specifically, the review covers sensing capabilities, promising algorithms, and methods, and added-value of novel machine learning algorithms for local-scale monitoring, biomass and yield estimation, and mapping of them. Finally, we present the opportunities for linking information from citizen science, internet of things (IoT) based on low-cost sensors and drone-based information to satellite data for upscaling crop yield estimation to a larger geographical extent within the Earth Observation umbrella. Full article
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Open AccessArticle
Unmanned Aircraft Systems (UAS) for Bridge Inspection Safety
Drones 2020, 4(3), 40; https://doi.org/10.3390/drones4030040 - 04 Aug 2020
Viewed by 218
Abstract
Unmanned aircraft systems (UAS) are an excellent tool to remove bridge inspection workers from potential harm. Previous research has documented that UAS for bridge inspection is a strategic priority of a state’s Department of Transportation (DOT), and this paper presents how they can [...] Read more.
Unmanned aircraft systems (UAS) are an excellent tool to remove bridge inspection workers from potential harm. Previous research has documented that UAS for bridge inspection is a strategic priority of a state’s Department of Transportation (DOT), and this paper presents how they can increase safety and presents one methodology to quantify the economic benefit. Although previous studies have documented the potential benefits of using UAS for bridge inspection, these studies have primarily focused on efficiency and capabilities. This paper investigates in greater detail the potential to use UAS to increase the safety of bridge inspection, and includes the results of a survey of bridge inspectors, as well as a benefit cost methodology that utilizes worker compensation rates to quantify the safety benefits of UAS; the methodology is demonstrated using a case study for a DOT. The results of this research present evidence that UAS can increase the safety of bridge inspection, and the benefit–cost methodology and analysis suggest that using UAS to increase safety will provide benefits that are greater than agency costs. Full article
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Open AccessArticle
Towards Bio-Inspiration, Development, and Manufacturing of a Flapping-Wing Micro Air Vehicle
Drones 2020, 4(3), 39; https://doi.org/10.3390/drones4030039 - 25 Jul 2020
Viewed by 269
Abstract
Throughout the last decade, there has been an increased demand for intricate flapping-wing drones with different capabilities than larger drones. The design of flapping-wing drones is focused on endurance and stability, as these are two of the main challenges of these systems. Researchers [...] Read more.
Throughout the last decade, there has been an increased demand for intricate flapping-wing drones with different capabilities than larger drones. The design of flapping-wing drones is focused on endurance and stability, as these are two of the main challenges of these systems. Researchers have recently been turning towards bioinspiration as a way to enhance aerodynamic performance. In this work, the propulsion system of a flapping-wing micro air vehicle is investigated to identify the limitations and drawbacks of specific designs. Each system has a tandem wing configuration inspired by a dragonfly, with wing shapes inspired by a bumblebee. For the design of this flapping-wing, a sizing process is carried out. A number of actuation mechanisms are considered, and two different mechanisms are designed and integrated into a flapping-wing system and compared to one another. The second system is tested using a thrust stand to investigate the impact of wing configurations on aerodynamic force production and the trend of force production from varying flapping frequency. Results present the optimal wing configuration of those tested and that an angle of attack of two degrees yields the greatest force production. A tethered flight test is conducted to examine the stability and aerodynamic capabilities of the drone, and challenges of flapping-wing systems and solutions that can lead to successful flight are presented. Key challenges to the successful design of these systems are weight management, force production, and stability and control. Full article
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Open AccessArticle
Investigating Methods for Integrating Unmanned Aerial Systems in Search and Rescue Operations
Drones 2020, 4(3), 38; https://doi.org/10.3390/drones4030038 - 24 Jul 2020
Viewed by 284
Abstract
Unmanned aerial systems (UAS) are increasingly being used in search and rescue (SAR) operations to assist in the discovery of missing persons. UAS are useful to first responders in SAR operations due to rapid deployment, high data volume, and high spatial resolution data [...] Read more.
Unmanned aerial systems (UAS) are increasingly being used in search and rescue (SAR) operations to assist in the discovery of missing persons. UAS are useful to first responders in SAR operations due to rapid deployment, high data volume, and high spatial resolution data collection capabilities. Relying on traditional manual interpretation methods to find a missing person in imagery data sets containing several hundred images is both challenging and time consuming. To better find small signs of missing persons in large UAS datasets, computer assisted interpretation methods have been developed. This article presents the results of an initial evaluation of a computer assisted interpretation method tested against manual methods in a simulated SAR operation. The evaluation performed focused on using resources available to first responders performing SAR operations, specifically: RGB data, volunteers, and a commercially available software program. Results from this field test were mixed, as the traditional group discovered more objects but required more time, in man hours, to discover the objects. Further field experiments, based on the capabilities of current first responder groups, should be conducted to determine to what extent computer assisted methods are useful in SAR operations. Full article
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Open AccessArticle
An Open Simulation Strategy for Rapid Control Design in Aerial and Maritime Drone Teams: A Comprehensive Tutorial
Drones 2020, 4(3), 37; https://doi.org/10.3390/drones4030037 - 23 Jul 2020
Viewed by 256
Abstract
The deployment of robot controllers into the real robotic platform is cumbersome and time consuming, especially when testing scenarios involve several robots or are sites not easily accessible. Besides this, most of the time, testing on the real platforms or real conditions provides [...] Read more.
The deployment of robot controllers into the real robotic platform is cumbersome and time consuming, especially when testing scenarios involve several robots or are sites not easily accessible. Besides this, most of the time, testing on the real platforms or real conditions provides little value in the early stages of controller design and prototype, phases where debugging and suitability of the controller are the main objectives. This paper proposes a simulation strategy for developing and testing controllers for Unmanned Aerial and Surface Vehicle coordination and interaction with the environment. The simulation strategy is based on V-REP and Matlab/Simulink which provide a large set of features, modularity and compatibility across platforms. Results show that this approach significantly reduces development and delivery times by providing an off-the-shelf simulation environment and a step-by-step implementation guidelines. The source code to deploy the simulations is available in an open-source repository. Full article
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Open AccessArticle
Measures of Canopy Structure from Low-Cost UAS for Monitoring Crop Nutrient Status
Drones 2020, 4(3), 36; https://doi.org/10.3390/drones4030036 - 22 Jul 2020
Viewed by 406
Abstract
Deriving crop information from remotely sensed data is an important strategy for precision agriculture. Small unmanned aerial systems (UAS) have emerged in recent years as a versatile remote sensing tool that can provide precisely-timed, fine-grained data for informing management responses to intra-field crop [...] Read more.
Deriving crop information from remotely sensed data is an important strategy for precision agriculture. Small unmanned aerial systems (UAS) have emerged in recent years as a versatile remote sensing tool that can provide precisely-timed, fine-grained data for informing management responses to intra-field crop variability (e.g., nutrient status and pest damage). UAS sensors with high spectral resolution used to compute informative vegetation indices, however, are practically limited by high cost and data dimensionality. This research extends spectral analysis for remote crop monitoring to investigate the relationship between crop health and 3D canopy structure using low-cost UAS equipped with consumer-grade RGB cameras. We used flue-cured tobacco as a case study due to its known sensitivity to fertility variation and nutrient-specific symptomology. Fertilizer treatments were applied to induce plant health variability in a 0.5 ha field of flue-cured tobacco. Multi-view stereo images from three UAS surveys collected during crop development were processed into orthoimages used to compute a visible band spectral index and photogrammetric point clouds using Structure from Motion (SfM). Plant structural metrics were then computed from detailed high resolution canopy surface models (0.05 m resolution) interpolated from the photogrammetric point clouds. The UAS surveys were complimented by nutrient status measurements obtained from plant tissues. The relationships between foliar nitrogen (N), phosphorus (P), potassium (K), and boron (B) concentrations and the UAS-derived metrics were assessed using multiple linear regression. Symptoms of N and K deficiencies were well captured and differentiated by the structural metrics. The strongest relationship observed was between canopy shape and N foliar concentration (adj. r2 = 0.59, increasing to adj. r2 = 0.81 when combined with the spectral index). B foliar concentration was consistently better predicted by canopy structure with a maximum adj. r2 = 0.41 observed at the latest growth stage surveyed. Overall, combining information about canopy structure and spectral reflectance increased model fit for all measured nutrients compared to spectral alone. These results suggest that an important relationship exists between relative canopy shape and crop health that can be leveraged to improve the usefulness of low cost UAS for precision agriculture. Full article
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Open AccessTechnical Note
Temperature Profiling of Waterbodies with a UAV-Integrated Sensor Subsystem
Drones 2020, 4(3), 35; https://doi.org/10.3390/drones4030035 - 21 Jul 2020
Viewed by 217
Abstract
Evaluation of thermal stratification and systematic monitoring of water temperature are required for lake management. Water temperature profiling requires temperature measurements through a water column to assess the level of thermal stratification which impacts oxygen content, microbial growth, and distribution of fish. The [...] Read more.
Evaluation of thermal stratification and systematic monitoring of water temperature are required for lake management. Water temperature profiling requires temperature measurements through a water column to assess the level of thermal stratification which impacts oxygen content, microbial growth, and distribution of fish. The objective of this research was to develop and assess the functions of a water temperature profiling system mounted on a multirotor unmanned aerial vehicle (UAV). The buoyancy apparatus mounted on the UAV allowed vertical takeoff and landing on the water surface for in situ measurements. The sensor node that was integrated with the UAV consisted of a microcontroller unit, a temperature sensor, and a pressure sensor. The system measured water temperature and depth from seven pre-selected locations in a lake using autonomous navigation with autopilot control. Measurements at 100 ms intervals were made while the UAV was descending at 2 m/s until it landed on water surface. Water temperature maps of three consecutive depths at each location were created from the measurements. The average surface water temperature at 0.3 m was 22.5 °C, while the average water temperature at 4 m depth was 21.5 °C. The UAV-based profiling system developed successfully performed autonomous water temperature measurements within a lake. Full article
(This article belongs to the collection Feature Papers of Drones)
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Open AccessReview
A Comprehensive Review of Applications of Drone Technology in the Mining Industry
Drones 2020, 4(3), 34; https://doi.org/10.3390/drones4030034 - 15 Jul 2020
Viewed by 487
Abstract
This paper aims to provide a comprehensive review of the current state of drone technology and its applications in the mining industry. The mining industry has shown increased interest in the use of drones for routine operations. These applications include 3D mapping of [...] Read more.
This paper aims to provide a comprehensive review of the current state of drone technology and its applications in the mining industry. The mining industry has shown increased interest in the use of drones for routine operations. These applications include 3D mapping of the mine environment, ore control, rock discontinuities mapping, postblast rock fragmentation measurements, and tailing stability monitoring, to name a few. The article offers a review of drone types, specifications, and applications of commercially available drones for mining applications. Finally, the research needs for the design and implementation of drones for underground mining applications are discussed. Full article
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Open AccessArticle
A Hybrid Voronoi Tessellation/Genetic Algorithm Approach for the Deployment of Drone-Based Nodes of a Self-Organizing Wireless Sensor Network (WSN) in Unknown and GPS Denied Environments
Drones 2020, 4(3), 33; https://doi.org/10.3390/drones4030033 - 14 Jul 2020
Viewed by 384
Abstract
Using autonomously operating mobile sensor nodes to form adaptive wireless sensor networks has great potential for monitoring applications in the real world. Especially in, e.g., disaster response scenarios—that is, when the environment is potentially unsafe and unknown—drones can offer fast access and provide [...] Read more.
Using autonomously operating mobile sensor nodes to form adaptive wireless sensor networks has great potential for monitoring applications in the real world. Especially in, e.g., disaster response scenarios—that is, when the environment is potentially unsafe and unknown—drones can offer fast access and provide crucial intelligence to rescue forces due the fact that they—unlike humans—are expendable and can operate in 3D space, often allowing them to ignore rubble and blocked passages. Among the practical issues faced are the optimizing of device–device communication, the deployment process and the limited power supply for the devices and the hardware they carry. To address these challenges a host of literature is available, proposing, e.g., the use of nature-inspired approaches. In this field, our own work (bio-inspired self-organizing network, BISON, which uses Voronoi tessellations) achieved promising results. In our previous approach the wireless sensors network (WSN) nodes were using knowledge about their coverage areas center of gravity, something which a drone would not automatically know. To address this, we augment BISON with a genetic algorithm (GA), which has the benefit of further improving network deployment time and overall coverage. Our evaluations show, unsurprisingly, an increase in energy cost. Two variations of our proposed GA-BISON deployment strategies are presented and compared, along with the impact of the GA. Counter-intuitively, performance and robustness increase in the presence of noise. Full article
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Open AccessArticle
On the Self-Calibration of Aerodynamic Coefficients in Vehicle Dynamic Model-Based Navigation
Drones 2020, 4(3), 32; https://doi.org/10.3390/drones4030032 - 12 Jul 2020
Viewed by 288
Abstract
The performance of vehicle dynamic model (VDM)-based navigation largely depends on the accurate determination of aerodynamic coefficients that are unknown a priori. Among different techniques, such as model simulations or experimental analysis in a wind tunnel, the method of self-calibration via state-space augmentation [...] Read more.
The performance of vehicle dynamic model (VDM)-based navigation largely depends on the accurate determination of aerodynamic coefficients that are unknown a priori. Among different techniques, such as model simulations or experimental analysis in a wind tunnel, the method of self-calibration via state-space augmentation benefiting Global Navigation Satellite System (GNSS) positioning represents an interesting and economical alternative. We study this technique under simulation with the goal of determining the impact of aircraft maneuvers on the precision and (de)-correlation of the aerodynamic coefficients among themselves and with respect to other error-states. A combination of different maneuvers indicates to be essential for obtaining satisfactory aerodynamic coefficients estimation and reduce their uncertainty. Full article
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Open AccessArticle
Inferring Visual Biases in UAV Videos from Eye Movements
Drones 2020, 4(3), 31; https://doi.org/10.3390/drones4030031 - 04 Jul 2020
Viewed by 389
Abstract
Unmanned Aerial Vehicle (UAV) imagery is gaining a lot of momentum lately. Indeed, gathered information from a bird-point-of-view is particularly relevant for numerous applications, from agriculture to surveillance services. We herewith study visual saliency to verify whether there are tangible differences between this [...] Read more.
Unmanned Aerial Vehicle (UAV) imagery is gaining a lot of momentum lately. Indeed, gathered information from a bird-point-of-view is particularly relevant for numerous applications, from agriculture to surveillance services. We herewith study visual saliency to verify whether there are tangible differences between this imagery and more conventional contents. We first describe typical and UAV contents based on their human saliency maps in a high-dimensional space, encompassing saliency map statistics, distribution characteristics, and other specifically designed features. Thanks to a large amount of eye tracking data collected on UAV, we stress the differences between typical and UAV videos, but more importantly within UAV sequences. We then designed a process to extract new visual attention biases in the UAV imagery, leading to the definition of a new dictionary of visual biases. We then conduct a benchmark on two different datasets, whose results confirm that the 20 defined biases are relevant as a low-complexity saliency prediction system. Full article
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Open AccessReview
The Application of Drones in Healthcare and Health-Related Services in North America: A Scoping Review
Drones 2020, 4(3), 30; https://doi.org/10.3390/drones4030030 - 04 Jul 2020
Viewed by 334
Abstract
Using drone aircraft to deliver healthcare and other health-related services is a relatively new application of this technology in North America. For health service providers, drones represent a feasible means to increase their efficiency and ability to provide services to individuals, especially those [...] Read more.
Using drone aircraft to deliver healthcare and other health-related services is a relatively new application of this technology in North America. For health service providers, drones represent a feasible means to increase their efficiency and ability to provide services to individuals, especially those in difficult to reach locations. This paper presents the results of a scoping review of the research literature to determine how drones are used for healthcare and health-related services in North America, and how such applications account for human operating and machine design factors. Data were collected from PubMed, CINAHL, Scopus, Web of Science, and IEEE Xplore using a block search protocol that combined 13 synonyms for “drone” and eight broad terms capturing healthcare and health-related services. Four-thousand-six-hundred-and-sixty-five documents were retrieved, and following a title, abstract, and full-text screening procedure completed by all authors, 29 documents were retained for analysis through an inductive coding process. Overall, findings indicate that drones may represent a financially feasible means to promote healthcare and health-related service accessibility for those in difficult-to-reach areas; however, further work is required to fully understand the costs to healthcare organizations and the communities they serve. Full article
(This article belongs to the Special Issue Drones for Medicine Delivery and Healthcare Logistics)
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Open AccessArticle
A Method for Selecting Strategic Deployment Opportunities for Unmanned Aircraft Systems (UAS) for Transportation Agencies
Drones 2020, 4(3), 29; https://doi.org/10.3390/drones4030029 - 02 Jul 2020
Viewed by 301
Abstract
Unmanned aircraft systems (UAS) are increasingly used for a variety of applications by state Departments of Transportation (DOT) and local transportation agencies due to technology advancements, lower costs, and regulatory changes that have simplified operations. There are numerous applications (e.g., bridge inspection, traffic [...] Read more.
Unmanned aircraft systems (UAS) are increasingly used for a variety of applications by state Departments of Transportation (DOT) and local transportation agencies due to technology advancements, lower costs, and regulatory changes that have simplified operations. There are numerous applications (e.g., bridge inspection, traffic management, incident response, construction and roadway mapping) and agencies find it challenging to prioritize which applications are most appropriate. Important factors to consider when prioritizing UAS applications include: (1) benefits, (2) ease of adoption, (3) stakeholder acceptance, and (4) technical feasibility. These factors can be evaluated utilizing various techniques such as the technology acceptance model, benefit analysis, and technology readiness level (TRL). This paper presents the methodology and results for the prioritization of UAS applications’ quality function deployment (QFD), which reflects both qualitative and quantitative components. The proposed framework can be used in the future as technologies mature, and the prioritization can be revised on a regular basis to identify future strategic implementation opportunities. Numerous transportation agencies have begun to use UAS, some have developed UAS operating policies and manuals, but there has been no documentation to support identification of the UAS applications that are most appropriate for deployment. This paper fills that gap and documents a method for identification of UAS applications for strategic deployment and illustrates the method with a case study. Full article
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Open AccessArticle
Correlating the Plant Height of Wheat with Above-Ground Biomass and Crop Yield Using Drone Imagery and Crop Surface Model, A Case Study from Nepal
Drones 2020, 4(3), 28; https://doi.org/10.3390/drones4030028 - 01 Jul 2020
Viewed by 621
Abstract
Food security is one of the burning issues in the 21st century, as a tremendous population growth over recent decades has increased demand for food production systems. However, agricultural production is constrained by the limited availability of arable land resources, whereas a significant [...] Read more.
Food security is one of the burning issues in the 21st century, as a tremendous population growth over recent decades has increased demand for food production systems. However, agricultural production is constrained by the limited availability of arable land resources, whereas a significant part of these is already degraded due to overexploitation. In order to get optimum output from the available land resources, it is of prime importance that crops are monitored, analyzed, and mapped at various stages of growth so that the areas having underdeveloped/unhealthy plants can be treated appropriately as and when required. This type of monitoring can be performed using ultra-high-resolution earth observation data like the images captured through unmanned aerial vehicles (UAVs)/drones. The objective of this research is to estimate and analyze the above-ground biomass (AGB) of the wheat crop using a consumer-grade red-green-blue (RGB) camera mounted on a drone. AGB and yield of wheat were estimated from linear regression models involving plant height obtained from crop surface models (CSMs) derived from the images captured by the drone-mounted camera. This study estimated plant height in an integrated setting of UAV-derived images with a Mid-Western Terai topographic setting (67 to 300 m amsl) of Nepal. Plant height estimated from the drone images had an error of 5% to 11.9% with respect to direct field measurement. While R2 of 0.66 was found for AGB, that of 0.73 and 0.70 were found for spike and grain weights respectively. This statistical quality assurance contributes to crop yield estimation, and hence to develop efficient food security strategies using earth observation and geo-information. Full article
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