Maestría en Electrónica y Automatización

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    Sistema de control con visión artificial para cultivos con luz artificial
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Electrónica y Automatización, 2022) Núñez Acosta, Rodrigo Santiago; Galarza Zambrano, Eddie Egberto
    The present investigation shows the design, construction and operation of two prototypes of intelligent systems for vertical crops with the application of artificial light and natural light, which optimize plant growth and eliminate the need of using fungicides and pesticides by being isolated and having an electronically controlled environment. It has been tested specifically for lettuce plantations; however, the control conditions can be adjusted for the development of other crop vegetable species. A correlation of the application of natural light and artificial light with an environment under the same conditions of temperature, humidity and drip culture system was performed; artificial vision was used to verify the growth optimization and verify the efficacy of artificial light, by taking samples every so often and applying the Open CV color and edge techniques.
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    Aplicación android utilizando realidad aumentada aplicada al proceso de venta de muebles de relax de la fábrica Msoto
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Electrónica y Automatización, 2022) Campos Freire, Celson Guillermo; Galarza Zambrano, Eddie Egberto
    The presented work is based on the design and implementation of an Android augmented reality application, focused on helping the community and construction professionals to preview indoor and outdoor furniture models in the home. Analyzing different design tools for augmented reality, evaluate the best options, then acquire formal knowledge and implement basic applications based on the objectives demonstrated in the document. A variety of interceptions implemented in mobile applications are also presented and operational variants of the developed mobile systems are described. The progress made is evaluated based on the knowledge gained and expectations regarding the use of AR technology; Several paths to explore in the short and medium term have been identified. The mobile application will solve the problem of crowding inside the MSOTO store in the salon furniture area to reduce crowds and provide customers with a satisfying shopping experience. The project is built using React Native, which allows integration with the ViroReact platform, allowing you to create virtual and augmented reality applications. By using this framework, it allows you to turn the app into one that works natively for Android and IOS devices. Next, an application for Android devices will appear that will allow us to choose furniture from a list of 10 models, which after choosing a model we will be able to show and interact with both the furniture and the permanent advice by the sales assistant of the MSOTO factory.
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    Diseño de un controlador multivariable utilizando herramientas de inteligencia artificial aplicado al proceso de incubación de embriones de Gallus Gallus Domesticus
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Electrónica y Automatización, 2022) Balseca Chicaiza, Alvaro Bladimiro; Herrera Garzón, Marco Antonio
    This project presents, a multivariable control using fuzzy logic and genetic algorithms (GA) as Artificial Intelligence (AI) tools, applied to the hatching process of “Gallus gallus domesticus” embryos. The incubation process is a system with high interactions among its input and output variables. To reduce these interactions, a dynamic decoupling network is used through Relative Gain Array (RGA) analysis. The proportional integral (PI) controllers and the linear decoupler are designed from singlevariable control structures obtained from a parametric identification for systems that can be pproximated to first order and first order with delay (FOPDT) models. Performance of PI, PI-Fuzzy and PI-Fuzzy controllers tuned with Genetic Algorithms (GA), are evaluated through a comparison of the integral squared error (ISE), integral absolute error (IAE) and total variation control (TVu) through simulations in MATLAB® and experimental tests using the NODEMCU ESP-WROOM-32 embedded system.
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    Controlador para alimentación de peces empleando Deep Learning
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Electrónica y Automatización, 2022) Cañar Yumbolema, Willam Patricio; Galarza Zambrano, Eddie Egberto
    This degree project consists of the design and implementation of a controller for fish feeding using Deep Learning for which a Raspberry minicomputer and a lowcost Web camera were used, this significantly reduced the investment for project development. The main objective consists in the creation of a manually labeled dataset (set of images) of several zebra-type fish (Danio Rerio) located inside a fish tank uniformly illuminated by white LED light. In this case, it was decided to use two videos with the presence of 4 and 6 fish, respectively. Through the use of a computational algorithm, the sequence of images of the fish where their movements can be identified were obtained. This information is used to train a convolutional network using the ACF (Aggregated Channel Characteristics) image object detection algorithm. Once the location of the fish inside the fish tank is determined, the feeling of the school is identified through the implementation of three zones, that is, the developed algorithm will allow knowing if the fish are in a satisfaction zone, a normal zone or a normal zone. feeding. Finally, the FuzzySN, FuzzySH and FuzzyNH indices contain the feeling of the fish and are the inputs of a fuzzy controller which in turn contains the feeding rules based on the natural behavior of the fish; In this way, the developed system is capable of feeding the fish automatically. The minimum identification error reached was 29.5%, but the identification of the behavior of the school of fish had a success rate of 100%. The test carried out to validate the algorithm was given for a case of manual feeding by an operator, where the system was able to correctly identify the feeling of the school as satisfied.
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    Sistema cuantificador de calidad de cultivo de manzana para monitoreo de la producción utilizando algoritmos de Aprendizaje Profundo con Visión Artificial y Segmentación de Instancias
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Electrónica y Automatización, 2022) Garcés Cadena, Andrés Alejandro; Prado Romo, Álvaro Javier
    Nowadays, agriculture is an activity of marked influence in the economy world, therefore, in order to satisfy the progressive food needs, human beings have been introducing technological tools for the optimization of agricultural practices, this management is also known as Precision Agriculture (PA) Artificial Vision is a technology that has given greater support to Precision Agriculture (PA), granting a wide range of tools with the ability to reduce difficulties faced by the farmer during his hand labor. The aim of this project is to provide farmers a tool to improve the process for apple harvest management, by using Deep Learning (DL) algorithms and a Computer Vision system. The system development includes two study analyses: apple type detection and quality quantification for its inspection and validation using a non-invasive method. For apple type detection, SSD-MobileNet model was used and for apple quality segmentation, a fully convolutional network FCN-ResNet-18 was used. For both studies, networks were retrained with customized databases generated specifically for the development of this project. Lastly, evaluation parameters of the detection and segmentation systems are presented with metrics such as confusion matrices, and overlapping of objects on the IoU, respectively.
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    Desarrollo de una aplicación de realidad aumentada y visión artificial para el mantenimiento de ventiladores mecánicos
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Electrónica y Automatización, 2022) Poveda Ocaña, Héctor Fabián; Galarza Zambrano, Eddie Egberto
    The present work shows the development of a maintenance system for the Savina 300 intensive care ventilator using augmented reality as a guide for the user. The identification algorithm has used a neural network trained with a 3D model of the respirator and the configuration of several relevant details for the training process. The objective execution platform is a mobile device with Android 11 operating system and motion sensors (gyroscope and accelerometer) that allows versatility, mobility and a low-cost implementation of the solution. The detection has been successful in execution times which allows an overlay of the 3D elements on top of the real fan. The proposed structure and work route offers robustness for the implementation of more maintenance tasks in the future. The validation has been carried out using the well-known SUS usability test in which the application reached a value of 82.5, which indicates that it is advisable to make improvements at the user interface and message display level in case of needing a better coefficient.
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    Prototipo robótico para la desinfección de ambientes cerrados COVID
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Electrónica y Automatización, 2022) Frías Moyón, Jefferson Ramiro; Gavilanes Carrión, Javier José
    An IoT robotic prototype applied for the fumigation of closed spaces with COVID was implemented, the same one that allows reducing the effort and infections of the personnel. The robot is made up of a caterpillar-type mobile platform, powered by 12v Pololu motors, it has an ESP32 camera with 180 degrees of freedom for visualization of the space to be sanitized, it has a 1.5-liter reservoir tank for liquids, a 4-cell LiPo battery at 4Amperes whose duration is 2 hours with a recharge of 1 hour, in addition the platform has the ability to move on floors such as tiles, concrete and not very pronounced irregular areas. To control the prototype we will do it remotely through 2 ways; (1) IoT control through the internet that allows the device to be tele-operated between cities or even countries (2) through an RF control that will be located where the prototype is going to carry out the fumigation, used in an emergency when it loses communication over the internet. The sanitizer module is derived from current domestic humidification systems, this system together with the combined sanitizer chemical compound (Quaternary Ammonium, Glycerin, Water), together form an important disinfectant option to include in future robotic platforms; It is important to note that the automatic option is configured so that the thermal fogger works continuously in case of losing the internet connection, which has a range of 1.50 to 2 meters. The use of fumigation by smoke agent has been gaining importance in recent years due to the global COVID-19 pandemic with the aim of reducing the impact of the virus. It was used for this study, it will finally incorporate sensors such as Air Quality, Temperature, etc, which are part of the telemetry of the IoT mobile robot.
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    Sistema electrónico de control y etiquetado de molduras para cuadros en tiempo-real mediante machine learning
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Electrónica y Automatización, 2022) Chávez Pico, David Alejandro; Herrera Garzón, Marco Antonio
    In this work, a real-time system is presented that performs the detection of the different types of moldings made from the analysis of the image processing of their different surfaces, silhouettes and colors. The need to use this electronic system for the control and labeling of moldings for paintings in real time through machine learning is to reduce production times and store the number of moldings manufactured in a database in order to avoid downtime on the part of workers and thus increase productivity in the factory. In addition, it has the tools, software and hardware to be able to do it, in this case a device called NVIDIA's Jetson Nano will be used for image analysis with its respective camera, which allows artificial vision applications. On the other hand, this control system allows the moldings manufactured to be labeled with their specific characteristics by means of a QR code to make it functional and practical in the factory. This will benefit production since the amount of molding will increase, since costs will be reduced and there will be an increase in profits. Another important aspect is that with this system it is intended to have scalability for the future due to the fact that there are different branches where the moldings are transported and it will help to have a more exact control from the time the load leaves until the load arrives to avoid delays in counting as conventionally. It has been done in recent years, this data can be taken directly to the accounting department who are in charge of the amount of production that is carried out in the factory and the amount that is transported to the headquarters and each of the branches.