Ingeniería en Sistemas, Electrónica e Industrial

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Subject: search.filters.subject.CONTROL DE ACCESO

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    Sistema de control de acceso automatizado con inteligencia artificial para el monitoreo de estudiantes y docentes en los talleres tecnológicos de la FISEI
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Telecomunicaciones, 2025-02) Barba Proaño Silvia Guadalupe; Brito Moncayo Geovanni Danilo
    The present research work focuses on the development of an automated access control system utilizing artificial intelligence for monitoring students and teachers of the faculty in the technological workshops of the FISEI at the Technical University of Ambato. The project encompasses everything from analyzing technical and operational requirements to implementing an intelligent system that integrates specialized hardware and software. Integration schemes for the system were designed, which include the use of biometric capture devices and facial recognition cameras connected to an artificial intelligence platform. This system enables automatic identification and registration of user entries, ensuring efficient control. Additionally, parameters were established to manage realtime alerts and generate detailed reports on user attendance and duration in the workshops. The implementation of the system included the development of machine learning algorithms to optimize facial recognition and user authentication, as well as the integration of a user-friendly interface that facilitates its use by administrative personnel. Functional tests were conducted in both simulated and real environments, verifying the accuracy of recognition and the robustness of the system under various operational conditions. Finally, the system was validated through pilot tests in the technological workshops, demonstrating its effectiveness in access management and continuous monitoring, contributing to security, and optimizing the use of available resources at FISEI.
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    Algoritmos de procesamiento de señales para el reconocimiento facial y de voz empleando redes neuronales
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Ingeniería en Electrónica y Comunicaciones, 2022-09) Orozco Analuiza, Carlos Alexander; Pallo Noroña, Juan Pablo
    The present titling work deals with the development of an access control system through facial and voice recognition, for the authentication of people in a home. Currently, the levels of insecurity have increased and this has led to an increase in theft and damage to real estate due to the low level of security in a home. The device developed in this project is based on a bimodal access biometric, through machine learning and neural networks, a subfield of Artificial Intelligence. The system has two authentication methods: facial and voice, for which neural network models designed by the researcher were used with the stages of: database formation, image and audio processing, and neural network design. He implements two methods of facial and voice authentication to avoid identity theft, a camera is responsible for capturing the person's face and performing recognition through the neural network, if the user is registered, the microphone is activated to capture the key of access and process it through the neural network, to record the data a LAMP server is used where the system information and user notifications are stored through the Telegram application. This project is aimed at controlling the access of people to a home, avoiding the use of traditional authentication methods.