<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1405-7743</journal-id>
<journal-title><![CDATA[Ingeniería, investigación y tecnología]]></journal-title>
<abbrev-journal-title><![CDATA[Ing. invest. y tecnol.]]></abbrev-journal-title>
<issn>1405-7743</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Facultad de Ingeniería]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-77432016000200211</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Sistema sensor para el monitoreo ambiental basado en redes Neuronales]]></article-title>
<article-title xml:lang="en"><![CDATA[Sensor System Based in Neural Networks for the Environmental Monitoring]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Rubio]]></surname>
<given-names><![CDATA[José de Jesús]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández-Aguilar]]></surname>
<given-names><![CDATA[José Alberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ávila-Camacho]]></surname>
<given-names><![CDATA[Francisco Jacob]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Stein-Carrillo]]></surname>
<given-names><![CDATA[Juan Manuel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Meléndez-Ramírez]]></surname>
<given-names><![CDATA[Adolfo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Instituto Politécnico Nacional ESIME Azcapotzalco SEPI]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Autónoma del Estado de Morelos  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>México</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Tecnológico de Estudios Superiores de Ecatepec  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Tecnológico de Estudios Superiores de Ecatepec  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af5">
<institution><![CDATA[,Tecnológico de Estudios Superiores de Ecatepec  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2016</year>
</pub-date>
<volume>17</volume>
<numero>2</numero>
<fpage>211</fpage>
<lpage>222</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-77432016000200211&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-77432016000200211&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-77432016000200211&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: En las tareas de monitoreo ambiental resulta de gran importancia contar con sistemas compactos y portátiles capaces de identificar contaminantes ambientales que faciliten las tareas relacionadas con el manejo de los residuos y la restauración ambiental. En este trabajo se describe el desarrollo de un sistema sensor prototipo creado para identificar contaminantes en el ambiente. Este prototipo está conformado con un arreglo de sensores de gas de óxido de estaño SnO2 utilizados para identificar vapores químicos, una etapa de adquisición de datos implementada con una plataforma ARM (Advanced RISC Machine) de bajo costo (Arduino) y una red neuronal capaz de identificar contaminantes ambientales automáticamente. La red neuronal se utiliza para identificar la composición del contaminante censado. En el sistema de cómputo, la carga computacional intensa se presenta únicamente en el proceso de entrenamiento, una vez que la red neuronal es entrenada, la operación consiste en propagar los datos a través de la red con una carga computacional mucho más ligera, la cual consiste principalmente en una multiplicación vector-matriz y una búsqueda en tablas que lleva a cabo la función de activación para identificar rápidamente muestras desconocidas.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: In the tasks of environmental monitoring is of great importance to have compact and portable systems able to identify environmental contaminants that facilitate tasks related to waste management and environmental restoration. In this paper, a prototype sensor is described to identify contaminants in the environment. This prototype is made with an array of tin oxide SnO2 gas sensors used to identify chemical vapors, a step of data acquisition implemented with ARM (Advanced RISC Machine) low-cost platform (Arduino) and a neural network able to identify environmental contaminants automatically. The neural network is used to identify the composition of contaminant census. In the computer system, the heavy computational load is presented only in the training process, once the neural network has been trained, the operation is to spread the data across the network with a much lighter computational load, which consists mainly of a vector-matrix multiplication and a search table that holds the activation function to quickly identify unknown samples.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[redes neuronales]]></kwd>
<kwd lng="es"><![CDATA[inteligencia artificial]]></kwd>
<kwd lng="es"><![CDATA[contaminación ambiental]]></kwd>
<kwd lng="es"><![CDATA[sensores]]></kwd>
<kwd lng="es"><![CDATA[reconocimiento de patrones]]></kwd>
<kwd lng="en"><![CDATA[neural networks]]></kwd>
<kwd lng="en"><![CDATA[artificial intelligence]]></kwd>
<kwd lng="en"><![CDATA[environmental pollution]]></kwd>
<kwd lng="en"><![CDATA[sensors]]></kwd>
<kwd lng="en"><![CDATA[pattern recognition]]></kwd>
</kwd-group>
</article-meta>
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