Macías-Quijas, Ricardo

Preferred name
Macías-Quijas, Ricardo
Official Name
Ricardo Macías Quijas
Alternative Name
rmacias
Main Affiliation
ORCID
0000-0001-8825-9655
Scopus Author ID
57200114870
Researcher ID
DEM-3721-2022

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    Tecnología Funcional de Nariz Electrónica para el Monitoreo de Gases en el Aire
    (Escuela Politecnica Nacional, 2025-11-30)
    ;
    Claudia L. Garzón-Castro
    ;
    Annamaría Filomena-Ambrosio
    ;
    ;
    Roberto De Fazio
    En los últimos años, las narices electrónicas se han consolidado como herramientas innovadoras para el monitoreo ambiental, particularmente en la detección de contaminantes en el aire. En este trabajo, se presenta el diseño e implementación de una tecnología funcional, portátil y de bajo costo de nariz electrónica, capaz de identificar gases como el monóxido de carbono, el metano y varios compuestos volátiles. Esta tecnología integra un arreglo de sensores y un módulo de adquisición de datos junto con algoritmos avanzados de procesamiento de señales. Se propone la aplicación del Método de Filtrado y Diagonalización (FDM) para la extracción de características espectrales, combinado con Bosques Aleatorios (RF) para la clasificación de gases. Los resultados experimentales demuestran una precisión del 96.4 % en la identificación de compuestos gaseosos, validando la efectividad de la combinación FDM-RF. Este estudio contribuye al avance de tecnologías accesibles para el monitoreo de la calidad del aire y así como de nuevos métodos de detección y clasificación de gases ambientales.
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    Reliable e-nose for air toxicity monitoring by filter diagonalization method
    (2022)
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    ;
    Roberto De Fazio
    ;
    Paolo Visconti
    ;
    Nicola Ivan Giannoccaro
    <jats:p>This paper introduces a compact, affordable electronic nose (e-nose) device devoted to detect the presence of toxic compounds that could affect human health, such as carbon monoxide, combustible gas, hydrogen, methane, and smoke, among others. Such artificial olfaction device consists of an array of six metal oxide semiconductor (MOS) sensors and a computer-based information system for signal acquisition, processing, and visualization. This study further proposes the use of the filter diagonalization method (FDM) to extract the spectral contents of the signals obtained from the sensors. Preliminary results show that the prototype is functional and that the FDM approach is suitable for a later classification stage. Example deployment scenarios of the proposed e-nose include indoor facilities (buildings and warehouses), compromised air quality places (mines and sanitary landfills), public transportation, mobile robots, and wireless sensor networks.</jats:p>
    Scopus© Citations 3  7  1
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    Linear and Nonlinear Control Approaches for the Cart Inverted Pendulum Problem
    (2021)
    Enrique Preza
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    ;
    ;
    ;
    Paolo Visconti
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    Environmental odor detection and classification with electronic nose system
    (Institute of Advanced Engineering and Science (IAES), 2025-04)
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    ;
    ;
    Rafal Lizut
    ;
    Paolo Visconti
    A prototype of an electronic nose (e-nose) system integrating a set of general-purpose gas sensors, an electronic module, and signal processing and classification methods has been designed and implemented to detect certain environmental odors that might pose a risk to human health. The proposed device explores the filter diagonalization method (FDM), an advanced signal processing technique for accurate spectral estimation, to detect the presence of odors together with random forest (RF), a popular machine learning algorithm, to classify the features of such spectra. Experimental results show that the proposed FDM-RF approach can recognize the targeted odors with an accuracy of 96.4%.
      25
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    Scopus© Citations 4  10  1
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    Development of an Electronic Nose Device for Security Applications
    (2019)
    ;
    Autumn Geil
    ;
    ;
    Aime Lay-Ekuakille
    Scopus© Citations 1  8  1