No / Technology application to agricultural productivity is thought to be the solution to meet food demand of the growing population. In a rapidly changing world, with the prospect of decreasing arable land due to urbanization and industrialization, agricultural output requires a 70 % increase in production levels and efficient growth in the harvesting, distribution and consumption of the resources, to meet demand. There are innovations in Information and Communications Technology that can be applied to the agricultural sector in areas of precision farming, use of farm management software, wireless sensors, and use of agricultural machinery. Remote sensing technology is playing a key role through precision agriculture. This paper highlights ways in which precision agriculture is impacting on agriculture with the use of unmanned aerial vehicles for image capturing, processing and analysis.

The use of aerial platforms such as unmanned aerial vehicles (UAVs), popularly known as drones, has emerged as a promising solution for providing reliable and cost-effective wireless communications. In particular, UAVs can be quickly and efficiently deployed to support cellular networks and enhance their quality-of-service (QoS) by establishing line-of-sight communication links. With their inherent attributes such as mobility, flexibility, and adaptive altitude, UAVs admit several key potential applications in wireless systems. Remarkably, despite these inherent advantages of UAVbased communications, little work has analyzed the performance tradeoffs associated with using UAVs as aerial wireless platforms. The key goal of this dissertation is to develop the analytical foundations for deployment, performance analysis, and optimization of UAV-enabled wireless networks. This dissertation makes a number of fundamental contributions to various areas of UAV communications that include: 1) Efficient deployment of UAVs, 2) Performance evaluation and optimization, and 3) Design of new flying, three-dimensional (3D) wireless systems. For deployment, using tools from optimization theory, holistic frameworks are developed for the optimal 3D placement of UAV base stations in uplink and downlink scenarios. The results show that the proposed deployment approaches significantly improve the downlink coverage for ground users, and enable ultra-reliable and energy-efficient uplink communications in Internet of Things (IoT) applications. For performance optimization, a novel framework is developed for maximizing the performance of a UAV-based wireless system, in terms of data service, under UAVs’ flight time constraints. To this end, using the mathematical framework of optimal transport theory, the optimal cell associations, that lead to a maximum data service to ground users within the limited UAVs’ hover duration, are analytically derived. The results shed light on the tradeoff between hover time and quality-of-service in UAV-based wireless networks. For performance evaluation, this dissertation provides a comprehensive analysis on the performance of a UAV-based communication system in coexistence with a terrestrial network. In particular, a tractable analytical framework is proposed for analyzing the coverage and rate performance of a network with a UAV base station and deviceto-device (D2D) users. The results reveal the fundamental tradeoffs in such a UAV-D2D network that allow adopting appropriate system design parameters. Then, this dissertation sheds light on the design of three new drone-enabled wireless systems. First, a novel framework for effective use of cache-enabled UAVs in wireless networks is developed. The results demonstrate how the users’ quality of experience substantially improves by exploiting UAVs’ mobility and user-centric information. Second, a new framework is proposed for deploying and operating a drone-based antenna array system that delivers wireless service to ground users within a minimum time. The results show significant enhancement in QoS, spectral and energy efficiency while levering the proposed drone antenna array system. Finally, to effectively incorporate various use cases of drones ranging from aerial users to base stations, the new concept of a fully-fledged 3D cellular network is introduced. For this new type of 3D wireless network, a unified framework for deployment, network planning, and performance optimization is developed that yields a maximum coverage and minimum latency in the network. In a nutshell, the analytical foundations and frameworks presented in this dissertation provide key guidelines for effective design and operation of UAV-based wireless communication systems. / Ph. D. / Unmanned aerial vehicles (UAVs), commonly known as drones, have been the subject of concerted research over the past few years, owing to their autonomy, flexibility, and broad range of application domains. Indeed, UAVs have been considered as enablers of various applications that include military, surveillance and monitoring, telecommunications, delivery of medical supplies, and rescue operations. The unprecedented recent advances in drone technology has made it possible to widely deploy UAVs, such small aircrafts, balloons, and airships for wireless communication purposes. In particular, if properly deployed and operated, UAVs can provide reliable and cost-effective wireless communication solutions for a variety of real-world scenarios. On the one hand, drones can be used as aerial base stations that can deliver reliable, cost-effective, and on-demand wireless communications to desired areas. On the other hand, drones can function as aerial user equipments, known as cellular-connected UAVs, in coexistence with ground users. Despite such promising opportunities for drones, one must address a number of technical challenges in order to effectively use them for each specific networking application. For instance, while using drone-BS, the key design considerations include performance characterization, optimal 3D deployment of drones, wireless and computational resource allocation, flight time and trajectory optimization, and network planning. Meanwhile, in the drone-UE scenario, handover management, channel modeling, low-latency control, 3D localization, and interference management are among the main challenges. Therefore, this dissertation addresses the fundamental challenges in UAV-enabled wireless communications that allows providing broadband, wide-scale, cost-effective, and reliable wireless connectivity. To this end, various mathematical frameworks and efficient algorithms are proposed to design, optimize, deploy, and operate UAV-based communication systems. The results shows that, the proposed aerial communication system can deliver ultra-reliable, and cost-effective wireless services, thus providing ubiquitous high speed Internet connectivity for the whole world.

Spring dead spot (SDS) is the most destructive disease of bermudagrass (Cynodon spp.) in Virginia. SDS infects bermudagrass in the fall with symptoms appearing in the spring when dormancy breaks. Patches are sporadically distributed but generally reoccur in the same location. Chemical control options are expensive with inconsistent results. Our objectives were to develop SDS incidence maps, investigate methods to analyze these maps, and evaluate suppression efficacy of incidence-map-based chemical applications. Methods were developed to build SDS incidence maps in 2016 and 2017. 2016 SDS incidence maps were compared for spatial accuracy to Digital Orthophoto Quarter Quadrangle (DOQQ), ground-validated differential GPS coordinates, and to 2017 SDS incidence maps, with average deviations of 1.3 m, 1.6 m, and 0.1 m, respectively. Digital Image Analysis (DIA) of aerial maps was compared to a point-intersect method for validation with a significant linear relationship (r2 = 0.77, P ≤ 0.0001). In the fall of 2016 and 2017, a site-specific penthiopyrad (SSP) treatment was evaluated against blanket, full-coverage applications of penthiopyrad (BP) and tebuconazole (BT), and an untreated control. Treatments were compared using DIA, post-treatment SDS patch count (PC), and SDS patch reduction (PR). Across all three metrics, the penthiopyrad treatments were statistically superior to both the tebuconazole and untreated. SSP compared favorably to BP for DIA, but BP had 2.57 fewer PC (LSD = 2.05) and a greater PR by 2.58 (LSD = 2.55). SSP using SDS incidence maps required 51% less fungicides in 2016 and 65% less in 2017 when compared to BP. / Master of Science in Life Sciences / Spring dead spot (SDS) is one of the most devastating diseases of bermudagrass in Virginia. Bermudagrass is utilized as a playing surface on golf courses and sports fields. During the fall, when the bermudagrass is preparing for winter dormancy, SDS can infect and reduce the turf’s cold tolerance. As a result, dead patches are present in the spring of the year. SDS ruins the integrity of playing surfaces and is slow to recover. The objectives of this research were to develop SDS incidence maps, investigate methods to analyze these maps, and evaluate site-specific chemical applications to control SDS, based on historical incidence. We developed methods for building SDS incidence maps in 2016 and 2017. Maps were evaluated for spatial accuracy as well as their ability to differentiate SDS from healthy bermudagrass. Digital Image Analysis (DIA) was used to calculate SDS coverage. DIA utilizes pixel color values to distinguish SDS from healthy turf. In the fall of 2016 and 2017, a site-specific penthiopyrad (SSP) treatment was evaluated against two full-coverage, blanket fungicides in penthiopyrad (BP) and tebuconazole (BT), as well as an untreated control. These programs were analyzed and across three metrics, DIA, Patch Count (PC) and Patch Reduction (PR), the penthiopyrad treatments were statistically superior to both the tebuconazole and untreated. SSP compared favorably to BP for DIA, but blanket applications were statistically superior when analysis by PC and PR. SSP required 51% less fungicides in 2016 and 65% less in 2017 when compared to BP.

This thesis describes the development of a nonlinear flight dynamics model for a small, fixed-wing unmanned aerial vehicle (UAV). Models developed for UAVs can be used for many applications including risk analysis, controls system design and flight simulators. Several challenges exist for system identification of small, low-cost aircraft including an increased sensitivity to atmospheric disturbances and decreased data quality from a cost-appropriate instrumentation system. These challenges result in difficulties in development of the model structure and parameter estimation. The small size may also limit the scope of flight test experiments and the consequent information content of the data from which the model is developed. Methods are presented to improve the accuracy of system identification which include data selection, data conditioning, incorporation of information from computational aerodynamics and synthesis of information from different flight test maneuvers. The final parameter estimation and uncertainty analysis was developed from the time domain formulation of the output-error method using the fully nonlinear aircraft equations of motion and a nonlinear aerodynamic model structure. The methods discussed increased the accuracy of parameter estimates and lowered the uncertainty in estimates compared to standard procedures for parameter estimation from flight test data. The significant contributions of this thesis are a detailed explanation of the entire system identification process tailored to the needs of a small UAV and incorporation of unique procedures to enhance identification results. This work may be used as a guide and list of recommendations for future system identification efforts of small, low-cost, minimally instrumented, fixed-wing UAVs. / MS / This thesis describes identification of a series of equations to model the flight motion of a small unmanned airplane. Model development for small unmanned aerial vehicles (UAVs) is a challenging process because they are significantly affected by small amounts of wind and they usually contain inexpensive, lower quality sensors. This results in lower quality data measured from flying a small UAV, which is subsequently used in the process to develop a model for the aircraft. In this work, techniques are discussed to improve estimation of model parameters and increase confidence in the validity of the final model. The significant contributions of this thesis are a comprehensive explanation of the model development process specific to a small UAV and implementation of unique procedures to enhance the resulting model. This work as a whole may be used as a guide and list of recommendations for future model development efforts of small, low-cost, unmanned aircraft.

This thesis investigates the possibility of using reinforcement learning (RL) techniques to create a flight controller for a quadrotor Micro Aerial Vehicle (MAV). A capable flight control system is a core requirement of any unmanned aerial vehicle. The challenging and diverse applications in which MAVs are destined to be used, mean that considerable time and effort need to be put into designing and commissioning suitable flight controllers. It is proposed that reinforcement learning, a subset of machine learning, could be used to address some of the practical difficulties. While much research has delved into RL in unmanned aerial vehicle applications, this work has tended to ignore low level motion control, or been concerned only in off-line learning regimes. This thesis addresses an area in which accessible information is scarce: the performance of RL when used for on-policy motion control. Trying out a candidate algorithm on a real MAV is a simple but expensive proposition. In place of such an approach, this research details the development of a suitable simulator environment, in which a prototype controller might be evaluated. Then inquiry then proposes a possible RL-based control system, utilising the Q-learning algorithm, with an adaptive RBF-network providing function approximation. The operation of this prototypical control system is then tested in detail, to determine both the absolute level of performance which can be expected, and the effect which tuning critical parameters of the algorithm has on the functioning of the controller. Performance is compared against a conventional PID controller to maximise the usability of the results by a wide audience. Testing considers behaviour in the presence of disturbances, and run-time changes in plant dynamics. Results show that given sufficient learning opportunity, a RL-based control system performs as well as a simple PID controller. However, unstable behaviour during learning is an issue for future analysis. Additionally, preliminary testing is performed to evaluate the feasibility of implementing RL algorithms in an embedded computing environment, as a general requirement for a MAV flight controller. Whilst the algorithm runs successfully in an embedded context, observation reveals further development would be necessary to reduce computation time to a level where a controller was able to update sufficiently quickly for a real-time motion control application. In summary, the study provides a critical assessment of the feasibility of using RL algorithms for motion control tasks, such as MAV flight control. Advantages which merit interest are exposed, though practical considerations suggest at this stage, that such a control system is not a realistic proposition. There is a discussion of avenues which may uncover possibilities to surmount these challenges. This investigation will prove useful for engineers interested in the opportunities which reinforcement learning techniques represent.

The Multiple Simultaneous Specification controller design method is an elegant means of designing a single controller to satisfy multiple convex closed loop performance specifications. In this thesis, the method is used to design pitch and roll attitude controllers for a Zagi flying-wing unmanned aerial vehicle from Procerus Technologies. A linear model of the aircraft is developed, in which the lateral and longitudinal motions of the aircraft are decoupled. The controllers are designed for this decoupled state space model. Linear simulations are performed in Simulink, and all performance specifications are satisfied by the closed loop system. Nonlinear, hardware-in-the-loop simulations are carried out using the aircraft, on-board computer, and ground station software. Flight tests are also executed to test the performance of the designed controllers. The closed loop aircraft behaviour is generally as expected, however the desired performance specifications are not strictly met in the nonlinear simulations or in the flight tests.

The Multiple Simultaneous Specification controller design method is an elegant means of designing a single controller to satisfy multiple convex closed loop performance specifications. In this thesis, the method is used to design pitch and roll attitude controllers for a Zagi flying-wing unmanned aerial vehicle from Procerus Technologies. A linear model of the aircraft is developed, in which the lateral and longitudinal motions of the aircraft are decoupled. The controllers are designed for this decoupled state space model. Linear simulations are performed in Simulink, and all performance specifications are satisfied by the closed loop system. Nonlinear, hardware-in-the-loop simulations are carried out using the aircraft, on-board computer, and ground station software. Flight tests are also executed to test the performance of the designed controllers. The closed loop aircraft behaviour is generally as expected, however the desired performance specifications are not strictly met in the nonlinear simulations or in the flight tests.

The High Frequency (HF) band, 3-30 MHz, is used when no infrastructure for long-range communications is available. New technology, such as digital signal processing enables higher data rate in the HF band, which in 2000s has resulted in increased commercial use. Reflection of radio waves in the ionosphere allows for beyond horizon communication, and are a unique property of the HF band. However, properties of the ionosphere are highly dependent of radiation from the sun, which varies with geographical location, season and time. The use of unmanned areal vehicle (UAV) has increased during the past years. In this project it is investigated if a HF transmitter can be placed on a small UAV platform. The objective is to get an estimation of the probabilities for successful HF transfer of real-time data from a small UAV. For example, the data could be sensor- or position data. When studying a complex problem having several parameters, such as a HF communication system, it is necessary to use the systems approach. This report illustrates the impact of size of the transmitting antenna, transmitter output power and bandwidth as well as different sources of noise and its levels. The results and analysis, made in this project, shows that there are feasible solutions for every tested case except at very high latitudes. Frequency planning, that is finding the less occupied channel, is almost as important as maximizing the signal to noise ratio. This project has been carried out on behalf of ÅF Technology in Solna, Sweden.

A mitigação de desastres naturais exige respostas rápidas e confiáveis. No Brasil, a estação de chuvas provoca muitos alagamentos em regiões urbanas e, para monitorar esse fenômeno, foi instalada em São Carlos-SP uma rede de sensores sem fio para acompanhar o nível de água dos rios da cidade. Entretanto, essa rede de sensores está suscetível a falhas que podem comprometer o funcionamento do sistema, e a adoção de mecanismos redundantes e de redes móveis 3G podem acarretar em custos proibitivos à monitoração desses rios, além de não garantirem a operação normal desse monitoramento. Assim, este trabalho apresenta uma solução baseada em veículo aéreo não tripulado (VANT) para reduzir os problemas oriundos das falhas em uma rede de sensores para detectar desastres naturais como enchentes e deslizamentos. Na solução proposta, o VANT pode ser transportado para o sítio do desastre para minimizar os problemas provenientes das falhas (por exemplo, para servir como um roteador ou até mesmo para servir como uma mula de dados e transmitir imagens em tempo real para equipes de resgate). Estudos foram conduzidos em um protótipo real, equipado com o UAV Brain (módulo computacional desenvolvido especificamente para este projeto), para uma análise exploratória do consumo energético do VANT e do rádio transmissor que equipa o VANT. Os resultados mostram que a melhor situação para o rádio comunicador se dá quando o VANT está no ar e com uma antena de maior ganho, e os fatores que mais influenciam no consumo energético do rádio são a altura do VANT e o tipo de antena utilizado. Além disso, tais resultados mostram também a viabilidade desta proposta em redes de sensores sem fio linear e esparsa. / The mitigation of natural disasters requires quick and reliable answers. In Brazil, the rainy season causes many flooding in urban areas and, to monitor this phenomenon, a wireless sensor network to monitor the water level of the citys rivers was installed in São Carlos-SP. However, this sensor network is susceptible to failures that may jeopardize the operation of the system, and the adoption of redundant mechanisms and 3G mobile networks may result in prohibitive costs to the monitoring of these rivers, and does not guarantee the normal operation of monitoring. This work presents an aerial vehicle-based solution unmanned (UAV) to reduce the problems originated from failures in a network of sensors to detect natural disasters such as floods and landslides. In the proposed solution, the UAV can be transported to the disaster site to minimize problems arising from failures (eg, to serve as a router or even to serve as a data mule and transmit images in real time for rescue teams). Studies were conducted in a real prototype, equipped with UAV Brain (computational module developed specifically for this project), for an exploratory analysis of the energy consumption UAV and radio transmitter fitted to the UAV. The results show that the best situation for the radio communicator is when the UAV is in the air and with a higher gain antenna, and the factors that most influence on the radio energy consumption are the height of the UAV and the type of antenna used. Furthermore, these results also show the feasibility of this proposal in linear and sparse wireless sensor networks.

This text presents the development of a four-degree-of-freedom (4DOF) quadcopter prototype that allows the vehicle to rotate around the three axes (yaw, pitch and roll) and linear movement along z-axis (altitude). The goal is to obtain a prototype bench that uses a good amount of components used in commercial quadcopters (sensors and actuators) and use it to apply attitude and altitude controllers, using techniques such as PID, LQR and Sliding-Mode. Starting from the system modeling, its specifications are shown followed by listing the components used, finishing with the development of the controllers and their simulations and applications. / Este texto apresenta o desenvolvimento de um protótipo de quadricóptero com quatro graus de liberdade (4DOF), o qual possibilita a rotação do veículo em torno dos três eixos (yaw, pitch e roll) e o deslocamento ao longo do eixo z (altitude). O objetivo é obter um protótipo de bancada que use a maior quantidade de componentes de um quadricóptero comercial (sensores e atuadores) e usá-lo para a aplicação de controladores de atitude e altitude, utilizando técnicas PID, LQR e Sliding-Mode. Partindo da modelagem do sistema, mostra-se as especificações do mesmo, os componentes utilizados e finaliza-se com o desenvolvimento dos controladores, simulação e aplicação deles.