Tesis Telecomunicaciones

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    Sistema de teledetección aérea para control de agentes patógenos y enfermedades en cultivos de brócoli con el uso de visión artificial
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Telecomunicaciones, 2023-09) Laura Telenchana, Darwin Ronaldo; Urrutia Urrutia, Elsa Pilar
    Broccoli is one of the agricultural products in Ecuador with the highest rate of imports worldwide, due to this the development of the crop must be routinely inspected to counteract the curses that harm its production such as pests or diseases and preserve its high rate of productive quality. For this reason, the present research project is oriented to carry out inspection of broccoli crops by air with pre programmed flight plans that help to analyze the health status of the crop to be treated on time. The design and implementation of the aerial remote sensing system for the control of pathogens and diseases in broccoli crops is developed through the use of the YOLO v5x artificial vision algorithm for deep learning of the system in various production circumstances. The aerial remote sensing system uses a drone that helps to move the active and passive sensors that interact in the system. This drone is autonomous thanks to the implementation of a GPS module on its flight control board, which helps planning grid-type pre-programmed flights. This system receives the analysis of the health status of the broccoli crop by capturing images through a high-definition camera incorporated into the drone. Each image is captured in a time frame of 10 seconds to carry out its respective processing in real time through a graphical interface programmed in Python. The image consists of positioning data such as altitude and latitude obtained through a geolocation system that was implemented in the drone. These data help to locate the specific point where the images were captured and interpret the results obtained in the analysis of the culture for each one of them. The results of the image processing are stored in a database, for the autonomous training of the artificial vision algorithm and improvement of the prototype in the detection of false positives and false negatives
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    Optimización de trayectorias en plataformas robóticas móviles usando técnicas de inteligencia artificial
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Telecomunicaciones, 2023-08) Soto Rodríguez, Andrés David; Manzano Villafuerte, Víctor Santiago
    As time progresses, the growth of the robotics industry is exponential and companies that seek to automate their processes do so to optimize resources, such as the time spent. The use of artificial intelligence is one of the current solutions for the optimization of various processes, by allowing learning in supervised environments, where robotic instrumentation tends to minimize the margin of error in the future thanks to implementations of AI algorithms. In the present project, a solution for the optimization of trajectories is exposed using as support an AI algorithm of reinforcement learning with neural networks implemented in the omnidirectional robotic platform of the KUKA youBot robot to move from one point to another avoiding obstacles presented in its path. The AI algorithm used for learning is Deep Q Network (DQN), this algorithm consists of deep neural networks to maximize some notion of rewards in a cumulative way. whereby means of a Hokuyo lidar motion sensor, placed in the front part of the robotic platform, they are acquired. You sample data from an environment, which is processed in the algorithm to be recognized as collisions or rewards. As the rewards learned by the algorithm are greater. the possibility of collision with an obstacle decreases, moving the robotic platform towards an obstacle-free zone. The programming language of this DON algorithm is based on Python 2, this language works together with ROS (robotic operating system) and allows to know, in an understandable way, how the execution of the movement is carried out through the publication and subscription to the topics corresponding to the robotic platform, thus facilitating the calibration of the parameters used in it.