{"id":380,"date":"2026-06-07T17:27:45","date_gmt":"2026-06-07T14:27:45","guid":{"rendered":"https:\/\/neurotechnologijos.com\/services\/nt-adaptive-raspberry-pi\/"},"modified":"2026-06-17T05:34:47","modified_gmt":"2026-06-17T02:34:47","slug":"nt-adaptive-raspberry-pi","status":"publish","type":"service","link":"https:\/\/neurotechnologijos.com\/es\/services\/nt-adaptive-raspberry-pi\/","title":{"rendered":"NT Adaptive \u2122 Raspberry Pi"},"content":{"rendered":"<h3>M\u00d3DULO NEUROM\u00d3RFICO PARA RASPBERRY PI<\/h3>\n<section class=\"news-content-section\">\n<div class=\"container news-content-grid\">\n<div class=\"news-content-image\">\n<p>M\u00f3dulo NT Adaptive con 576 neuronas, dise\u00f1ado para la demostraci\u00f3n, formaci\u00f3n y desarrollo de las capacidades de los chips neurom\u00f3rficos. El m\u00f3dulo se conecta f\u00e1cilmente a Raspberry Pi y a otros ordenadores mediante micro USB.<\/p>\n<h4>Ejemplos de v\u00eddeo<\/h4>\n<h4 class=\"link-youtube\"><a href=\"https:\/\/www.youtube.com\/channel\/UCSzZjhhL-AkvKnRfq5Dt1Hw\/videos\">Todos los v\u00eddeos en YouTube &gt;&gt;&gt;<\/a><\/h4>\n<p><iframe loading=\"lazy\" title=\"Reproductor de v\u00eddeo de YouTube\" src=\"https:\/\/www.youtube.com\/embed\/-vcuw6BBTLE?si=Nmie31bVErVDfxPr\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p>Se presenta la capacidad de la tecnolog\u00eda neurom\u00f3rfica para identificar las posiciones de interruptores autom\u00e1ticos y LED que indican el estado de equipos reales.<\/p>\n<p><iframe loading=\"lazy\" title=\"Reproductor de v\u00eddeo de YouTube\" src=\"https:\/\/www.youtube.com\/embed\/ofTy-4CKhmw?si=v_AG9bAbzdGMy29b\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p>El programa est\u00e1 desarrollado en Python y combina varias opciones para demostrar las posibilidades de los chips neurom\u00f3rficos. Reconocimiento de posiciones de unidades autom\u00e1ticas de alimentaci\u00f3n, indicaci\u00f3n luminosa de l\u00e1mparas de control, indicaciones de man\u00f3metros de aguja, valores de indicadores de siete segmentos y posiciones de conmutadores rotativos.<\/p>\n<p><iframe loading=\"lazy\" title=\"Reproductor de v\u00eddeo de YouTube\" src=\"https:\/\/www.youtube.com\/embed\/Rzo8LsORMmg?si=cUJ_gdeKpKHygDfF\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p>Se muestra un programa de demostraci\u00f3n escrito en Python. Este programa utiliza una combinaci\u00f3n de la biblioteca abierta OpenCV y el chip CM1K (NM500) al trabajar con la placa de expansi\u00f3n PCIe. OpenCV se utiliz\u00f3 para buscar rostros en fotograf\u00edas, mientras que el entrenamiento y el reconocimiento de los propios rostros se realizaron mediante chips neurom\u00f3rficos.<\/p>\n<p><iframe loading=\"lazy\" title=\"Reproductor de v\u00eddeo de YouTube\" src=\"https:\/\/www.youtube.com\/embed\/ZByaW1v9zaU?si=0-XsnwZAxD4hpvWJ\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p>Demostraci\u00f3n del programa desarrollado en Python. Demostraci\u00f3n de la secuencia de selecci\u00f3n de im\u00e1genes, selecci\u00f3n de ROI, selecci\u00f3n y ajuste de par\u00e1metros de un chip neurom\u00f3rfico, como MAXIF, categor\u00edas, entrenamiento y verificaci\u00f3n de los resultados del aprendizaje. Este programa utiliza chips neurom\u00f3rficos en una placa PCIe.<\/p>\n<\/div>\n<div class=\"news-content-text\">\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-75\" src=\"https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-300x173.png\" alt=\"\" width=\"300\" height=\"173\" srcset=\"https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-300x173.png 300w, https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-1024x589.png 1024w, https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-768x442.png 768w, https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi.png 1200w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p><strong>NT Adaptive Raspberry PI<\/strong> M\u00f3dulo de inteligencia artificial dise\u00f1ado para la identificaci\u00f3n de diversas se\u00f1ales. El m\u00f3dulo puede reconocer im\u00e1genes est\u00e1ticas, sonidos, diversas se\u00f1ales el\u00e9ctricas, textos y datos. El proceso de reconocimiento neurom\u00f3rfico a nivel de hardware acelerar\u00e1 las capacidades de inteligencia artificial de cualquier ordenador. El m\u00f3dulo reconoce se\u00f1ales en microsegundos con solo milivatios de potencia.<\/p>\n<h3>Posibilidades:<\/h3>\n<ul>\n<li>Identificaci\u00f3n;<\/li>\n<li>Clasificaci\u00f3n;<\/li>\n<li>Detecci\u00f3n de novedad;<\/li>\n<li>Detecci\u00f3n de anomal\u00edas;<\/li>\n<li>Segmentaci\u00f3n contextual de im\u00e1genes;<\/li>\n<li>Detecci\u00f3n de bordes;<\/li>\n<li>Eliminaci\u00f3n de ruido;<\/li>\n<li>Compresi\u00f3n de im\u00e1genes;<\/li>\n<\/ul>\n<p>y otras.<\/p>\n<h3>\u00c1reas de aplicaci\u00f3n:<\/h3>\n<ul>\n<li>Hobby;<\/li>\n<li>Educaci\u00f3n;<\/li>\n<li>Estudios;<\/li>\n<li>Industria;<\/li>\n<li>Agricultura;<\/li>\n<li>Medicina;<\/li>\n<li>Seguridad;<\/li>\n<li>Estad\u00edstica;<\/li>\n<\/ul>\n<p>y otras.<\/p>\n<p>Dimensiones del m\u00f3dulo NT Adaptive Raspberry PI: 52x20x10 mm<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-76\" src=\"https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-ism2-300x203.png\" alt=\"\" width=\"300\" height=\"203\" srcset=\"https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-ism2-300x203.png 300w, https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-ism2.png 662w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>El m\u00f3dulo puede conectarse mediante Micro USB o pines TTL.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-77\" src=\"https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-zoom4-1024x1024-1-300x300.png\" alt=\"\" width=\"300\" height=\"300\" srcset=\"https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-zoom4-1024x1024-1-300x300.png 300w, https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-zoom4-1024x1024-1-150x150.png 150w, https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-zoom4-1024x1024-1-768x768.png 768w, https:\/\/neurotechnologijos.com\/wp-content\/uploads\/2026\/06\/NT-Adaptive-raspberry-pi-zoom4-1024x1024-1.png 1024w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<\/div>\n<\/div>\n<\/section>\n","protected":false},"excerpt":{"rendered":"<p>M\u00d3DULO NEUROM\u00d3RFICO PARA RASPBERRY PI M\u00f3dulo NT Adaptive con 576 neuronas, dise\u00f1ado para la demostraci\u00f3n, formaci\u00f3n y desarrollo de las capacidades de los chips neurom\u00f3rficos. El m\u00f3dulo se conecta f\u00e1cilmente a Raspberry Pi y a otros ordenadores mediante micro USB. Ejemplos de v\u00eddeo Todos los v\u00eddeos en YouTube &gt;&gt;&gt; Se presenta la capacidad de la [&hellip;]<\/p>\n","protected":false},"featured_media":24,"menu_order":0,"template":"","service_category":[60],"class_list":["post-380","service","type-service","status-publish","has-post-thumbnail","hentry","service_category-nt-adaptive"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>M\u00f3dulo de Expansi\u00f3n<\/title>\n<meta name=\"description\" content=\"M\u00f3dulo de Expansi\u00f3n listo para conectar a Raspberry Pi, que permite acceder a 576 neuronas para aprender, clasificar y monitorizar datos. 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