В работе поднимается проблема экологического мониторинга воздуха около промышленных предприятий. Разработана информационно-управляющая система, включающая: устройство для определения концентрации вредных веществ в воздухе и передачи данных, беспилотный летательный аппарат (БПЛА) для проведения мониторинга, программный модуль для обработки полученных данных. Оперативное определение состояния окружающей среды с помощью устройства экологического мониторинга совместимого с БПЛА позволит снизить риск ухудшения здоровья рабочих, а также позволит предупредить утечки опасных газов, в том числе взрывоопасных. / The paper raises the problem of environmental monitoring of air near industrial enterprises. An information and control system has been developed, including: a device for determining the concentration of harmful substances in the air and transmitting data, an unmanned aerial vehicle (UAV) for monitoring, a software module for processing the received data. Operational determination of the state of the environment using an environmental monitoring device compatible with the UAV will reduce the risk of deterioration of workers' health, and will also prevent leaks of dangerous gases, including explosive ones.

Obemannade luftfarkoster, även kallade drönare, är del av IoT-revolutionen och har uppmärksammats de senaste åren på grund av integritetsfrågor såväl som flygplats- och militär säkerhet. Då de kan flyga samt har implementerat en ökande mängd teknologi, särskilt kamera och annan övervakning, är de attraktiva måltavlor för hackers och penetrationstestare. Ett antal attacker har genomförts i närtid. I detta examensarbete utforskas och attackeras drönaren Parrot ANAFI genom att använda hotmodellering ur ett black box-perspektiv. Hotmodelleringen inkluderar hotidentifiering med STRIDE samt riskvärdering med DREAD. Inga stora svagheter i systemet hittades. Rapporten visar att tillverkaren har en stor säkerhetsmedvetenhet. Exempel på denna medvetenhet är att tidigare rapporterade svagheter har åtgärdats och programkoden har förvrängts. Metoderna och de funna resultaten kan användas för att vidare utforska svagheter i drönare och liknande IoT-enheter. / Unmanned aerial vehicles, commonly known as drones, are part of the IoT revolution and have gotten some attention in recent years due to privacy violation issues as well as airport and military security. Since they can fly and have an increasing amount of technology implemented, especially camera and other surveillance, they are attractive targets for hackers and penetration testers. A number of attacks have been carried out over the years. In this thesis the Parrot ANAFI drone is explored and attacked using threat modeling from a black box perspective. The threat modeling includes identifying threats with STRIDE and assessing risks with DREAD. Major vulnerabilities in the system were not found. This report shows that the manufacturer has a high security awareness. Examples of this awareness are that previously reported vulnerabilities have been mitigated and firmware code has been obfuscated. The methods used and results found could be used to further explore vulnerabilities in drones and similar IoT devices.

Within the archaeological record ‘mounds’ are often ubiquitous. They are common in many ancient cultures, and they vary in size, construction techniques and use. This research is focused upon optimizing the use of remote sensing for the non-invasive study of mounds both in the United States and the United Kingdom. This thesis presents three representative earthen mound sites and proposes a comprehensive and modular survey methodology to guide the planning and execution of a mound survey tailored to the unique requirements presented by the cultural resource at a particular location. In doing so, the research has provided optimized approaches to high resolution three-dimensional topographic models using a variety of digital methods. These models have been shown to accurately capture the variability of the modern ground surface, which is of vital importance to the management of the mounds. Furthermore, these models have proved vital for integrating geophysical methods into the holistic workspace, thereby providing a better archaeological understanding of the below ground remains. Every mound surveyed presented different challenges, and therefore had to be approached in a slightly different way. However, the general methodology was highly effective for both characterizing below-ground archaeological and natural anomalies, and for assessing the state of preservation of all mounds surveyed. As a result, a flowchart has been generated for non-invasive assessment of mounds in general. If followed, this will allow the production of a “snapshot” of the mound or mound group at a fixed point in time with the resolution necessary to produce useful and insightful interpretation. While this research focuses on the application of geophysical and topographic survey in the United Kingdom and United States to a mound or mound group, this methodology and the associated outcomes can be valuable more globally not only for archaeology, but also heritage management.

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<p> Significant portions of nitrogen (40–60%), phosphorus (80–90%) and potash (30–50%) applied in agricultural fields are not taken up by plants, causing serious issues for farmers and the environment. Fertilizer losses result in greater fertilizer input costs and the cost of fertilizer is projected to increase due to limited ore resources and increasing fossil fuel prices. Moreover, excess fertilizer application can contaminate water and air, resulting in human health problems. Leaching fertilizers also induce eutrophication, acid rain and global climate change. Therefore, developing crops with high nutrient uptake efficiency is important for economic and environmental sustainability of agriculture. Crop improvement depends on efficiency and accuracy of genotyping and phenotyping. Genotyping has improved in recent years and is generally efficient and accurate. In contrast, improvements in phenotyping lag far behind. Lack of high-throughput (efficient, accurate and inexpensive) phenotyping (HTP) methods limit the speed of genetic improvement. As a result, there is an increasing interest in development of HTP for predicting crop nutrient status. My research addresses whether hyperspectral data in the visible-near-infrared range (HS-VNIR) acquired by a handheld device or an unmanned aerial vehicle (UAV) can be used for predicting maize nutrient status. Proximal and remote sensing data coupled with ground reference measurements of hybrid maize nutrient status were collected in fertilizer strip trials conducted at Purdue Agricultural Centers located throughout Indiana. Statistical models were developed to predict nutrient status based on HS-VNIR with coefficients of determination of cross-validation [R² (CV)] used to evaluate the performance of the predictive models. Models with acceptable goodness-of-fit [R² (CV) > 0.30] were considered satisfactory. These studies demonstrated that models developed using handheld proximal sensing data performed adequately for predicting N, K, Mg, Ca, P, S, Mn, Zn and B. Similarly, models developed using UAV-based HS-VNIR could be used to predict N, K, Mg, Ca, P, S, Mn, Zn and B. Models that combine proximal and remote sensing data also performed well with predictions of N, K, Mg, Ca, P, S, Mn, Zn and B. In conclusion, handheld or UAV-based hyperspectral imaging can provide corn breeders with HTP data on the status of all macronutrients (N, K, Mg, Ca, P, S) and some micronutrients (Mn, Zn, B). Deployment of this technology may provide a valuable tool to support development of cultivars with improved nutrient uptake efficiencies.  </p>

The research on autonomous vehicles, and more specifically cooperation between autonomous vehicles, has become a prominent research field during the last cou- ple of decades. One example is the combination of an unmanned aerial vehicle (UAV) together with an unmanned ground vehicle (UGV). The benefits of this are that the two vehicles complement each other, where the UAV provides an aerial view and can reach areas where a ground vehicle can not. Furthermore, since the UAV has a limited range, the UGV can then serve as transport and recharge sta- tion for the UAV. This master thesis studies how model predictive control (MPC) can be used to land a UAV on a moving UGV.  A linear MPC is chosen, since previous work using this has shown promising results. The UAV is chosen to be controlled using commands in pitch, roll and climbing rate. The MPC is designed as a decoupled controller, with a separate horizontal and vertical controller. This allows for a spatial constraint to be im- plemented, which constrains the UAV from entering ground level before arriving above the UGV. It also constrains the UAV from potentially hitting protruding ob- jects on the UGV. The horizontal controller uses a simple planner, which guides the UAV to land on the UGV from behind.  The MPC is evaluated using a additive white Gaussian noise (AWGN) sen- sor error model with zero mean. The scenario used is that the UAV starts 50 m from the UGV, and the UGV starts driving in a given direction turning randomly. The MPC lands successfully in 100 % of the simulations for a wide range of tun- ings. The MPC maintains the same landing statistics with a delay in the sensor information of up to 500 ms. The AWGN could be increased while maintaining successful landings, however with significantly more retakes and longer landing times. Lower AWGN variance only slightly improves performance, suggesting that the MPC is quite robust towards high variance in the state estimation.  The MPC is also compared to a PID controller. The MPC has significantly shorter landing times. The PID has a more oscillatory control signal, however, the PID has a lower variance in landing positions, but a slightly less centered mean on the UGV. The overall results show that an MPC can be used to achieve a flexible controller that can be tuned and reformulated to fit the situation, and performs as good or better compared to a PID controller.  The hardware tests show promising results for the implementation of the MPC. The controller is not tuned and no system identification is done specifi- cally for the physical UAV, suggesting that the controller is robust for varying settings. Even though the UAV never lands on the UGV, the visual behavior and control signal plots suggest that it would be able to land. However, these tests are performed using global navigation satellite system state estimation on a sta- tionary UGV, therefore further tests need to be performed in more challenging scenarios.

A system of an unmanned aerial vehicle (UAV) collaborating with an unmanned ground vehicle (UGV) for use in for example surveillance, reconnaissance, transport and target acquisition is studied. The project investigates the problem of estimating the relative position, velocity and orientation between the UAV and the UGV required to autonomously land the UAV on the UGV during movement. The use of global navigation satellite system (GNSS) receivers are not considered since they are sensitive to interference and spoofing attacks.  The developed estimation system consists of an extended Kalman filter (EKF) using measurements from several sensors, including: a camera, barometers, inertial measurement units (IMUs) and impulse-radio ultra-wide bandwidth (IRUWB) transceivers. Primarily the use of near infrared (NIR) light emitting diodes (LEDs) attached to the UGV and a camera on the UAV is investigated. Several configurations of LED placements, and what errors to expect when measuring them with the camera, are evaluated. The performance is evaluated in both simulations and hardware sensor tests, but no live experiments that include any autonomous landing manoeuvre are conducted.  The results indicate that high estimation precision can be achieved, at close range the errors in position average below 2 cm and in orientation under 0.5 degrees. However, some problems arise from the detection and identification of the LEDs. Further, if measurements of the LEDs are completely missing, the estimation precision suffers due to error accumulation in the inertial navigation. These results indicate that autonomous landing is possible, since the amount of LED measurements and consequently also the estimation precision increases as the relative position decreases.

Ducted fan vehicles possess a superior ability to maximize payload capacity while minimizing vehicle size. Their ability to both hover and fly at high speed is a key advantage for information-gathering missions, particularly when close proximity to a target is essential. However, the ducted fan's aerodynamic characteristics pose difficulties for stable vehicle flight and therefore require complex control algorithms. In particular, they exhibit a large nose-up pitching moment during wind gusts and when transitioning from hover to forward flight. Understanding ducted fan aerodynamic behavior and how it can be altered through flow control techniques are the two prime objectives of this work. This dissertation provides a new paradigm for modeling the ducted fan's nonlinear behavior and new methods for changing the duct aerodynamics using active flow control. Steady and piezoelectric synthetic jet blowing are employed in the flow control concepts and are compared. The new aerodynamic model captures the nonlinear characteristics of the force, moment, and power data for a ducted fan, while representing these terms in a set of simple equations. The model attains excellent agreement with current and legacy experimental data using twelve non-dimensional constants. Synthetic jet actuators (SJA) have potential for use in flow control applications in UAVs with limited size, weight, and power budgets. Piezoelectric SJAs for a ducted fan vehicle were developed through two rounds of experimental designs. The final SJA design attained peak jet velocities in the range of 225 ft/sec (69 m/s) for a 0.03â x 0.80â rectangular slot. To reduce the magnitude of the nose-up pitching moment in cross-winds, two flow control concepts were explored: flow separation control at the duct lip, and flow turning at the duct trailing edge using a CoandÄ surface. Both concepts were experimentally proven to be successful. Synthetic jets and steady jets were capable of modifying the ducted fan flow to reduce pitching moment, but some cases required high values of steady blowing to create significant responses. Triggering leading edge separation on the duct lip was one application where synthetic jets showed comparable performance to steady jets operating at a blowing coefficient an order of magnitude higher. / Ph. D.