IDENTIFICACIÓN AUTOMÁTICA DE COMPUERTAS DIGITALES CON DISPOSITIVO MÓVIL Y REALIDAD AUMENTADA (AUTOMATIC IDENTIFICATION OF DIGITAL GATES THROUGH MOBILE DEVICE AND AUGMENTED REALITY)

Carlos Avilés Cruz, Juan Villegas Cortez, Arturo Zúñiga López, Eduardo Rodríguez Martínez, Andrés Ferreyra Ramírez

Resumen


Los conceptos fundamentales de los dispositivos electrónicos generalmente son enseñados en los cursos iniciales de ingeniería eléctrica-electrónica. Es de suma importancia manejar los conceptos básicos que hacen posible las computadoras y los sistemas digitales en general. De entre los conceptos, destaca la álgebra booleana y la lógica de compuertas. La parte práctica es angular en la adquisición correcta de los conceptos. En el presente trabajo se aborda de una forma práctica la identificación de los circuitos integrados (CI) que hacen posible operaciones lógicas: and, or, not, nor, nand. La identificación se lleva a cabo vía realidad aumentada (RA) y por medio de un dispositivo móvil corriendo en sistema operativo android. Se identifican CI’s de forma automática, desplegando en  pantalla el tipo de CI que se trate, adicionalmente se proporciona información de sus terminales y la operación lógica respectiva. El porcentaje de reconocimiento es de 100 % sobre 5 tipos de compuertas lógicas.

The fundamental concepts of electronic devices are generally taught in initial electrical-electronic engineering courses. It is of the utmost importance to handle the basic concepts that make computers and digital systems possible. Among the concepts, the Boolean algebra and the logic gates stand out. The practical part is angular in the correct acquisition of the concepts. This paper deals in a practical way with how to identify the integrated circuits (ICs) that make logical operations possible: and, or, not, nor, nand, through out augmented reality (AR). Across a mobile-based device running on an android operating system, you can automatically identify ICs by displaying the location and type of IC on the screen of the mobile device. The system has a recognition rate of 100.


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