Digital Inclusion of the Farming Sector Using Drone Technology

Agriculture continues to be the primary source of income for most rural people in the developing economy. The world’s economy is also strongly reliant on agricultural products, which accounts for a large number of its exports. Despite its growing importance, agriculture is still lagging behind to meet the demands due to crop failure caused by bad weather conditions and unmanaged insect problems. As a result, the quality and quantity of agricultural products are occasionally affected to reduce the farm income. Crop failure could be predicted ahead of time and preventative measures could be taken through a combination of conventional farming practices with contemporary technologies such as agri-drones to address the difficulties plaguing the agricultural sectors. Drones are actually unmanned aerial vehicles that are used for imaging, soil and crop surveillance, and a variety of other purposes in agricultural sectors. Drone technology is now becoming an emerging technology for large-scale applications in agriculture. Although the technology is still in its infancy in developing nations, numerous research and businesses are working to make it easily accessible to the farming community to boost the agricultural productivity

Improved terrain type classification using UAV downwash dynamic texture effect

The ability to autonomously navigate in an unknown, dynamic environment, while at the same time classifying various terrain types, are significant challenges still faced by the computer vision research community. Addressing these problems is of great interest for the development of collaborative autonomous navigation robots. For example, an Unmanned Aerial Vehicle (UAV) can be used to determine a path, while an Unmanned Surface Vehicle (USV) follows that path to reach the target destination. For the UAV to be able to determine if a path is valid or not, it must be able to identify the type of terrain it is flying over. With the help of its rotor air flow (known as downwash e↵ect), it becomes possible to extract advanced texture features, used for terrain type classification. This dissertation presents a complete analysis on the extraction of static and dynamic texture features, proposing various algorithms and analyzing their pros and cons. A UAV equipped with a single RGB camera was used to capture images and a Multilayer Neural Network was used for the automatic classification of water and non-water-type terrains by means of the downwash e↵ect created by the UAV rotors. The terrain type classification results are then merged into a georeferenced dynamic map, where it is possible to distinguish between water and non-water areas in real time. To improve the algorithms’ processing time, several sequential processes were con verted into parallel processes and executed in the UAV onboard GPU with the CUDA framework achieving speedups up to 10x. A comparison between the processing time of these two processing modes, sequential in the CPU and parallel in the GPU, is also presented in this dissertation. All the algorithms were developed using open-source libraries, and were analyzed and validated both via simulation and real environments. To evaluate the robustness of the proposed algorithms, the studied terrains were tested with and without the presence of the downwash e↵ect. It was concluded that the classifier could be improved by per forming combinations between static and dynamic features, achieving an accuracy higher than 99% in the classification of water and non-water terrain.Dotar equipamentos moveis da funcionalidade de navegação autónoma em ambientes desconhecidos e dinâmicos, ao mesmo tempo que, classificam terrenos do tipo água e não água, são desafios que se colocam atualmente a investigadores na área da visão computacional. As soluções para estes problemas são de grande interesse para a navegação autónoma e a colaboração entre robôs. Por exemplo, um veículo aéreo não tripulado (UAV) pode ser usado para determinar o caminho que um veículo terrestre não tripulado (USV) deve percorrer para alcançar o destino pretendido. Para o UAV conseguir determinar se o caminho é válido ou não, tem de ser capaz de identificar qual o tipo de terreno que está a sobrevoar. Com a ajuda do fluxo de ar gerado pelos motores (conhecido como efeito downwash), é possível extrair características de textura avançadas, que serão usadas para a classificação do tipo de terreno. Esta dissertação apresenta uma análise completa sobre extração de texturas estáticas e dinâmicas, propondo diversos algoritmos e analisando os seus prós e contras. Um UAV equipado com uma única câmera RGB foi usado para capturar as imagens. Para classi ficar automaticamente terrenos do tipo água e não água foi usada uma rede neuronal multicamada e recorreu-se ao efeito de downwash criado pelos motores do UAV. Os re sultados da classificação do tipo de terreno são depois colocados num mapa dinâmico georreferenciado, onde é possível distinguir, em tempo real, terrenos do tipo água e não água. De forma a melhorar o tempo de processamento dos algoritmos desenvolvidos, vários processos sequenciais foram convertidos em processos paralelos e executados na GPU a bordo do UAV, com a ajuda da framework CUDA, tornando o algoritmo até 10x mais rápido. Também são apresentadas nesta dissertação comparações entre o tempo de processamento destes dois modos de processamento, sequencial na CPU e paralelo na GPU. Todos os algoritmos foram desenvolvidos através de bibliotecas open-source, e foram analisados e validados, tanto através de ambientes de simulação como em ambientes reais. Para avaliar a robustez dos algoritmos propostos, os terrenos estudados foram testados com e sem a presença do efeito downwash. Concluiu-se que o classificador pode ser melhorado realizando combinações entre as características de textura estáticas e dinâmicas, alcançando uma precisão superior a 99% na classificação de terrenos do tipo água e não água

An Unmanned Lighter-Than-Air Platform for Large Scale Land Monitoring

The concept and preliminary design of an unmanned lighter-than-air (LTA) platform instrumented with different remote sensing technologies is presented. The aim is to assess the feasibility of using a remotely controlled airship for the land monitoring of medium sized (up to 107 m2) urban or rural areas at relatively low altitudes (below 1000 m) and its potential convenience with respect to other standard remote and in-situ sensing systems. The proposal includes equipment for high-definition visual, thermal, and hyperspectral imaging as well as LiDAR scanning. The data collected from these different sources can be then combined to obtain geo-referenced products such as land use land cover (LULC), soil water content (SWC), land surface temperature (LSC), and leaf area index (LAI) maps, among others. The potential uses for diffuse structural health monitoring over built-up areas are discussed as well. Several mission typologies are considere

Applications of Drones in Atmospheric Chemistry

The emission of greenhouse gases (GHGs) has changed the composition of the atmosphere during the Anthropocene. A major technical and scientific challenge is quantifying the resulting fugitive trace gas fluxes under variable meteorological conditions. Accurately documenting the sources and magnitude of GHGs emission is an important undertaking for discriminating contributions of different processes to radiative forcing. Therefore, the adverse environmental and health effects of undetected gas leaks motivates new methods of detecting, characterizing, and quantifying plumes of fugitive trace gases. Currently, there is no mobile platform able to quantify trace gases at altitudes(UASs), or drones, can be deployed on-site in minutes and can support the payloads necessary to quantify trace gases. Thus, the research herein has contributed to the advancement of atmospheric, environmental, and analytical chemistry through the development, calibration, validation, and application of small unmanned aerial systems (sUAS). The quantification of atmospheric gases with sUAS is expanding the ability to safely perform environmental monitoring tasks and quickly evaluate the impact of technologies. The experimental findings have developed the sUAS as a platform for atmospheric measurements and demonstrated applications of meteorological and trace gas measurements. The research ultimately enabled novel studies that quantified and modeled the atmospheric transport of trace gases to better understand their impact on environmental and atmospheric chemistry

Experimental and numerical investigation on conjugate performance of fan and heat exchanger of helicopter oil cooling system

© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license. https://creativecommons.org/licenses/by/4.0/In this article, a combined experimental and numerical study has been performed to investigate the operating performance of axial fan and oil cooling system. A test rig was established, and six types of plate-fin heat exchangers (HEs) with offset strip and rectangular fins and three different flow lengths of 30 mm, 60 mm and 90 mm at air side were designed and manufactured. The performance of an axial fan with front guide vane was experimentally studied by two different adjusting modes: gradually increasing and decreasing air flow rate. The conjugate performances of the axial fan and different HEs were discussed in detail. Moreover, a three-dimensional (3D) model was developed to investigate the flow distribution of the system including fan and 30 mm offset strip fins HE at different flow rates. The results show that: (1) the total pressure performance curve of the axial fan under two adjusting modes could form a hysteresis region near the stall boundary. In the hysteresis region, the fan performance curves showed significant difference under both adjusting modes; (2) when the offset strip fins HE with large flow resistance is considered, the system could have two theoretical working points in the hysteresis region. For the case of HE with 90 mm offset strip fins, the flow rates of the system at two theoretical working points were 25.1 m³/min and 34.2 m³/min, and the heat transfer capacity of the HE were 23.1 kW and 27.5 kW, respectively. In the current experiment, it was found that the system operated at the point with smaller flow rate; (3) when the HE flow resistance exceeded a certain value, the boundary layer separation of the airflow could occur at the rotor blade. The separation had a small effect on the inlet airflow due to its turbulence kinetic energy was low and basically the same at each blade passage. Therefore, the system did not surge or stall at small flow rate.Peer reviewe

Multicopter flow fields and their influence on a spray released from multicopters.

Multicopters are remote-controlled vertical take-off and landing unpiloted aerial vehicles (UAVs). When used for releasing particulates (crop seeding, targeted fertiliser, and aerial spraying), they are a convenient tool for farms situated in rocky or mountainous terrain that does not allow for the use of helicopters or aeroplanes. Their small size and high manoeuvrability are also attractive for spraying near sensitive areas (e.g., riverbeds, lakes, native forest, residential areas). Understanding the behaviour of spray is crucial for targeted spray dispersal and for the protection of sensitive areas. This research studies multicopter wake and its influence on the performance of spraying liquid. The primary experimental technique used for the study of multicopter wake was stereo particle image velocimetry (SPIV), supplemented by constant temperature anemometry (CTA) with a three-axial probe. The study analysed the isolated rotor wakes of the APC 1047 (127 mm radius, 119.3 mm pitch), APC 1045 (127 mm radius, 114.3 mm pitch), APC 1040 (127 mm radius, 101.6 mm pitch) and DJI E7000 (420 mm radius, 230 mm pitch). The isolated wake vector field, normalized by rotor tip velocity, was found to remain similar for each rotor with changing rotational speed. Multicopters can be divided into two-rotor sections, allowing a simplified experimental setup using two rotors instead of four or more. APC 1045 counter-rotating coplanar rotor pairs were used for the analysis of multicopter rotors in hover, at rotor arc spacings of 02R, 0.36R and 0.55R (R=rotor radius). SPIV experimental analysis shows the rotor wakes tilting towards each other. The tilt angle decreases with increased tip spacing. Two counter rotating coplanar DJI E7000 rotors with 0.2R rotor tip spacing also demonstrated tilted wakes. The tilt may be explained by interaction between wakes creating a low-pressure zone between them. A region of upwash was detected with APC 1045 rotors at rotor arc distances of 0.2R, 0.36R and 0.55R. The upwash region was observed at every rotational position and phase difference for DJI E7000 rotors at an arc distance of 0.2R. Upward velocity magnitude is dependent on the angular position of the rotor, peaking when one of the rotor tips is at its closest approach to the neighbouring rotor’s arc. It is weakly dependent on rotational speed over the range of 1740- 2150 rpm. Upwash generation may be explained by interaction between the tip vortices and wakes of the two rotors. APC 1045 counter-rotating rotor pairs were analysed in the presence of lateral velocity. In streamwise configuration, the wake of the windward rotor tilts 20-25º more than that of the leeward rotor at lateral velocities of 6 m/s, 10 m/s and 14 m/s. The shading of the leeward wake by the windward wake is the cause of the difference in tilt angles. In the presence of lateral velocity with a streamwise rotor configuration, the roll-up vortex is attached to the windward side of the windward rotor disk and extends in the direction of the airflow relative to the multicopter. With a spanwise rotor configuration, the roll-up vortex is attached to the windward side of both rotors and extends in the direction of the airflow near the free side of the rotor disk. However, in the presence of another counter-rotating rotor, the upwash region does not have a downstream lateral component at lateral velocities between 2- 6 m/s. Based on SPIV analysis data used to track spray deposition near the rotors, it is recommended to avoid placing the spray nozzle immediately under the arc swept by the rotor tip (0.8R-1R), especially in the zone between rotors. This draws some spray upwards, decreasing spraying efficiency and potentially entering the multicopter’s electrical components. The recommended nozzle position is the zone of strongest downwash (0.5-0.7R). A fast-computing model for spray pattern prediction was developed in OpenFoam, using rotor disk simplification as a boundary condition inside the domain. The velocity field boundary condition was obtained from SPIV data. The rotor boundary condition used the turbulence kinetic energy data obtained via CTA. The atmospheric wind model was incorporated into the model and can be used on-demand. The effect of plant canopy was introduced with a porous medium model. Two DJI E7000 coplanar counter-rotating rotors were modelled in hovering flight. The modelled velocity field below the rotors was within one standard deviation of SPIV experimental results. The modelled velocity field between rotors was not within one standard deviation. The upward velocity region was not reproduced in the model. Two APC 1045 rotors were modelled at 2 m/s, 6 m/s, 10 m/s lateral velocity in streamwise and spanwise configurations. In streamwise configuration, the leeward rotor is shaded by the windward rotor, therefore the inclination angle of the leeward rotor is smaller than that of the windward rotor. The roll-up vortices are observed in the model. The location of the roll-up vortices is similar in the model and experiment in both spanwise and streamwise configurations. A DJI Agras MG-1 multicopter was modelled to allow comparison of swath patterns in the model and experimental results. Two roll-up vortices are present in the multicopter and extend in a streamwise direction. The model output was used for spray pattern prediction by applying Lagrangian particle tracking. An evaporation model was implemented in a particle tracking algorithm. The spray footprints of two nozzle positions were modelled in hovering flight and compared to experimental results, revealing that the model can be used for spray footprint evaluation. Differences between the model and the experiment may be explained by absence of tip vortices in the model. The swath pattern in the wake of a DJI Agras MG-1 multicopter in three different flights (true airspeed 3.627 m/s, ground speed 2.85 m/s, and crosswind speed 0.736 m/s; true airspeed 3.234 m/s, ground speed 2.9 m/s, and crosswind speed 2.164 m/s; true air speed 4.88 m/s, ground speed 4.88 m/s, and crosswind speed 0.04 m/s), is comparable in the model and experiment. The effective swath width (30% line separation) is within one standard deviation of the model. In all flight trials, the modelled swath was closest to the experimentally obtained swath when the surface roughness of the ground was equal to 0.5 m (bushes) and the rotational speed of all rotors was equal to 2475 rpm with 0.75R (0.2m) tall plant canopy (grass) introduced to the model. The model can be used to evaluate the swath pattern left on the ground by the multicopter. It showed acceptable validity for hovering flight and flight velocities of up to 2.8-5 m/s when flight parameters can be approximately estimated. The computational time of the model is 12 minutes

Experimental investigations on the aerodynamic and aeroacoustic characteristics of small UAS propellers

Unmanned aerial system (UAS) is a hot topic in both industry and academia fields. As a popular planform, the rotary-wing system gains more attentions. The small UAS propeller is the most important component in this system, which transfers electric energy into kinetic energy to accomplish fly missions. In the present work, several experimental studies have been performed to investigate the aerodynamic and aeroacoustic characteristics of small UAS propellers. First of all, by conducting force and flow filed measurements, the unsteady dynamic thrust and the wake structure of the propeller has been studied to explore the fundamental physics to help researchers and engineers to obtain a better understanding. Secondly, two kinds of bio-inspired the propellers have been designed and manufactured. Through a set of force, sound, and flow filed measurements, the aerodynamic and aeroacoustic performance of these propellers has been compared to the baseline propeller to evaluate the effects of aerodynamic efficiency and noise attenuation. It was found that the serrated trailing edge propeller could reduce the turbulent trailing edge noise up to 2 dB, and the maple seed inspired propeller could reduce the noise up to 4 dB with no effect on the aerodynamic performance. In addition, since the rotary-wing system consists more than one propeller, the rotor to rotor interaction on the aerodynamic and aeroacoustic performance also has been studied. By enlarging the separation distance between two propellers, the thrust fluctuation and noise generation could be restricted. Not only the design of the device itself has effect on the flying performance, the extreme weather also would affect it. Therefore, an icing research study on the small UAS propeller has been conducted to illustrate how does the ice formed on the propeller and how does the icing influence the aerodynamics performance and power consumption. During these experimental studies, the force measurements were achieved by a high sensitive force and moment transducer (JR3 load cell), which had a precision of ñ0.1N (ñ 0.25% of the full range). The sound measurements were conducted inside of the anechoic chamber located in the aerospace engineering department at Iowa State University. This chamber has a physical dimensions of 12ÃÂ12ÃÂ9 feet with a cut-off frequency of 100 Hz. The detailed flow structure downstream of the propeller was measured by a high-resolution digital PIV system. The PIV system was used to elucidate the streamwise flow structure downstream of the propeller. Both “free-run” and “phase-locked” PIV measurements were conducted to achieve the ensemble-average flow structure and detailed flow structure at certain phase angles

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Location, location, location: considerations when using lightweight drones in challenging environments

Lightweight drones have emerged recently as a remote sensing survey tool of choice for ecologists, conservation practitioners and environmental scientists. In published work, there are plentiful details on the parameters and settings used for successful data capture, but in contrast there is a dearth of information describing the operational complexity of drone deployment. Information about the practices of flying in the field, whilst currently lacking, would be useful for others embarking on new drone-based investigations. As a group of drone-piloting scientists, we have operated lightweight drones for research in over 25 projects, in over 10 countries, and in polar, desert, coastal and tropical ecosystems, with many hundreds of hours of flying experience between us. The purpose of this paper was to document the lesser-reported methodological pitfalls of drone deployments so that other scientists can understand the spectrum of considerations that need to be accounted for prior to, and during drone survey flights. Herein, we describe the most common challenges encountered, alongside mitigation and remediation actions that increase the chances of safe and successful data capture. Challenges are grouped into the following categories: (i) pre-flight planning, (ii) flight operations, (iii) weather, (iv) redundancy, (v) data quality, (vi) batteries. We also discuss the importance of scientists undertaking ethical assessment of their drone practices, to identify and mitigate potential conflicts associated with drone use in particular areas. By sharing our experience, our intention is that the paper will assist those embarking on new drone deployments, increasing the efficacy of acquiring high-quality data from this new proximal aerial viewpoint.This work was supported by the Natural Environment Research Council [NE/K570009815], [NE/K500902/1] (to AMC), [NE/M016323/1] (to IHM-S), [NE/570009815] (to JPD) and the UK Technology Strategy Board [TS/K00266X/1] (to KA). JS and KA were partly supported by the European Space Agency contract No. 4000117644/16/NL/FF/gp

Physics-Based Modeling for Control and Autonomous Operation of Unmanned Aerial Vehicles

UAS are widely employed in commercial and military applications, and their utilization is growing at a rapid pace. Effective predictive models for aeromechanics, body dynamics and control are critical in trajectory planning and optimization, autonomous operations, and decision-making. Aeromechanical and wind models that are currently used in the control and guidance of UAS are typically simplistic and often do not represent the essential physics to an adequate degree. Therefore, the performance and versatility of such vehicles may be limited in extreme flight conditions. At the other end of the spectrum, there exist high fidelity models that are computationally expensive, and thus not applicable in path planning, optimization, and onboard flight controllers. The major goal of this dissertation is to bridge the gap between physics-based models and onboard decision-making. Multi-disciplinary models of appropriate fidelity are developed and integrated into a comprehensive flight simulation software suite. These models are experimentally validated and utilized in trajectory planning, optimization, onboard control and autonomous flight. Studying the impact of models of different fidelity for the environment and the aerodynamics determines the impact of modeling uncertainty on system-level goals. A vortex-based model for lifting surfaces is developed, using which control surfaces and couplings therein can be efficiently represented. Using this model, the interaction of the propeller wake with a downstream wing is studied, and it is demonstrated these models are effective tools in predicting the propeller-induced span-wise loading. Such a model is beneficial for trajectory planning and optimization applications to improve flight stability and trajectory tracking. Next, a novel HBEM model is developed to predict rotor forces over a wide range of flight conditions. The HBEM model is self-contained and combines blade element theory, momentum theory and a linear inflow model to determine the {em unique} inflow that is {em consistent with all theories}. The model utilizes the blade geometry and the flight condition as inputs to determine the relationship between the forces/moments and the rotor RPM. A detailed set of wind tunnel experiments is conducted to validate the model across a very wide range of flight regimes. Further, a semi-empirical model for the RIPF is developed using experimental data. It is noted that these models can be executed in real-time which makes them useful for implementation in flight software. A custom quadrotor is built and equipped with an ultrasonic wind sensor and RPM sensors. The HBEM and RIPF models are embedded in quadrotor flight software, and it is illustrated these models are fully integrable and efficient enough to run on a typical onboard compute module. To evaluate the ability of these models to function in harsh environmental conditions, motion capture aided autonomous flight is realized in the presence of strong wind gusts generated by a large industrial fan. A feedforward controller is designed to incorporate physical insight into flight mechanics and to provide estimates of the state. Flight tests are conducted in and out of strong crosswind conditions to further show the impact of computationally efficient models that are capable of being executed onboard in real-time. It is shown that the wind sensing and physics-based models along with the feedforward controller improve trajectory tracking in extreme environmental conditions.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169719/1/davoudi_1.pd