{"id":1422,"date":"2022-01-13T13:27:36","date_gmt":"2022-01-13T13:27:36","guid":{"rendered":"https:\/\/picockpit.com\/raspberry-pi\/?p=1422"},"modified":"2023-11-13T09:44:59","modified_gmt":"2023-11-13T09:44:59","slug":"teach-bme688-how-to-smell","status":"publish","type":"post","link":"https:\/\/picockpit.com\/raspberry-pi\/fr\/teach-bme688-how-to-smell\/","title":{"rendered":"Apprenez \u00e0 votre BME688 \u00e0 sentir bon."},"content":{"rendered":"<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"960\" height=\"638\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/Teach-Your-BME688-How-To-Smell-Title-Image.png\" alt=\"Apprenez \u00e0 votre BME688 \u00e0 sentir Image de titre\" class=\"wp-image-5957\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/Teach-Your-BME688-How-To-Smell-Title-Image.png 960w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/Teach-Your-BME688-How-To-Smell-Title-Image-300x199.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/Teach-Your-BME688-How-To-Smell-Title-Image-768x510.png 768w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/Teach-Your-BME688-How-To-Smell-Title-Image-18x12.png 18w\" sizes=\"auto, (max-width: 960px) 100vw, 960px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Un guide complet sur la fa\u00e7on d'entra\u00eener votre capteur BME688<\/h2>\n\n\n\n<p>Bonjour \u00e0 tous les passionn\u00e9s de technologie ! Bosch a publi\u00e9 le <a href=\"https:\/\/buyzero.de\/en\/products\/luftqualitatssensor-bosch-bme688-breakout-board?_pos=2&amp;_sid=9d841f7fd&amp;_ss=r\">BME688<\/a>Le BME688, un nouveau capteur g\u00e9nial qui peut distinguer jusqu'\u00e0 quatre odeurs diff\u00e9rentes. Ce guide vous expliquera tous les d\u00e9tails pour apprendre \u00e0 votre BME688 \u00e0 distinguer les odeurs. Ne vous inqui\u00e9tez pas si vous \u00eates novice en IA ou en Python. Ce guide est adapt\u00e9 aux d\u00e9butants.<\/p>\n\n\n\n<p>Alors, allons-y.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Conditions pr\u00e9alables<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/buyzero.de\/en\/products\/raspberry-pi-4-model-b-8gb?_pos=1&amp;_sid=2d20515a2&amp;_ss=r&amp;variant=40326643974324\">Raspberry Pi<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/buyzero.de\/en\/products\/luftqualitatssensor-bosch-bme688-breakout-board?_pos=2&amp;_sid=9d841f7fd&amp;_ss=r\">BME688 Breakout Board<\/a> ou <a href=\"https:\/\/buyzero.de\/en\/products\/bosch-bme688-gas-sensor-developer-kit?variant=37884583182516\">Kit de d\u00e9veloppement du capteur de gaz Bosch BME688<\/a><\/li>\n\n\n\n<li>Des sp\u00e9cimens qui produisent les odeurs souhait\u00e9es<\/li>\n\n\n\n<li>Un r\u00e9cipient herm\u00e9tique pour contenir le capteur et l'\u00e9chantillon.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.bosch-sensortec.com\/software-tools\/software\/bme688-software\/\">BSEC et AI Studio par Bosch<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.picockpit.com\/\">PiCockpit<\/a><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">\u00c9tapes<\/h3>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Choisissez votre application<\/li>\n\n\n\n<li>Donn\u00e9es d'enregistrement<\/li>\n\n\n\n<li>Entra\u00eener l'algorithme<\/li>\n\n\n\n<li>D\u00e9tecter les odeurs<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">1. Choisissez votre application<\/h2>\n\n\n\n<p>La premi\u00e8re \u00e9tape consiste \u00e0 choisir votre application. Pour ce guide, je vais utiliser la viande et le fromage comme exemples. Mais il existe une gamme infinie de possibilit\u00e9s. Vous pouvez distinguer les fruits des l\u00e9gumes ou les produits de nettoyage des parfums. Vous pouvez \u00e9galement essayer de d\u00e9terminer quand un aliment a tourn\u00e9.<\/p>\n\n\n\n<p>Il y a certains \u00e9l\u00e9ments que vous devez prendre en compte lorsque vous choisissez une application. Vous avez besoin de nombreux sp\u00e9cimens pour chaque classe que vous souhaitez distinguer, afin de garantir la robustesse de l'algorithme. Pour commencer, vous devez choisir un produit bon march\u00e9 et largement disponible. Gardez \u00e9galement \u00e0 l'esprit qu'il est conseill\u00e9 d'utiliser l'air normal comme l'une des classes, car il sera presque toujours pr\u00e9sent.<\/p>\n\n\n\n<p>Pour cr\u00e9er un algorithme robuste, vous devez utiliser au moins une demi-heure de donn\u00e9es de mesure pour chaque sp\u00e9cimen. Par cons\u00e9quent, les sp\u00e9cimens qui produisent une odeur constante sont un bon choix. Veillez \u00e9galement \u00e0 utiliser un large \u00e9ventail de sp\u00e9cimens. Si, par exemple, vous n'utilisez que des oranges, des citrons et des citrons verts pour votre classe de fruits, le capteur risque de ne pas classer une framboise comme un fruit, car elle est trop diff\u00e9rente des sp\u00e9cimens utilis\u00e9s pour la formation. Plus vous utilisez de sp\u00e9cimens diff\u00e9rents, mieux c'est.<\/p>\n\n\n\n<p>Une fois que vous avez finalis\u00e9 votre choix, il est temps de cr\u00e9er un nouveau projet AI Studio. Ouvrez AI Studio et appuyez sur le bouton <span style=\"background-color:#0a3ec2\" class=\"tadv-background-color\"> <span style=\"color:#074b68\" class=\"has-inline-color\"><strong><span style=\"color:#ffffff\" class=\"tadv-color\">Cr\u00e9er un projet ...<\/span><\/strong><\/span> <\/span> Bouton. Appuyez sur <strong>Configurer la carte BME<\/strong> si vous voulez enregistrer des donn\u00e9es avec une configuration sp\u00e9cifique.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">2. Enregistrer les donn\u00e9es<\/h2>\n\n\n\n<p>Ce processus varie, selon que vous utilisez l'option <a style=\"font-size: revert;\" href=\"https:\/\/buyzero.de\/en\/products\/luftqualitatssensor-bosch-bme688-breakout-board?_pos=2&amp;_sid=9d841f7fd&amp;_ss=r\">BME688 Breakout Board<\/a><span style=\"font-size: revert; color: initial;\"> ou <\/span><a style=\"font-size: revert;\" href=\"https:\/\/buyzero.de\/en\/products\/bosch-bme688-gas-sensor-developer-kit?variant=37884583182516\">Kit de d\u00e9veloppement du capteur de gaz Bosch BME688<\/a> (autre carte navette). La carte navette est plus facile \u00e0 utiliser et capture les donn\u00e9es huit fois plus vite que la carte breakout, mais elle est beaucoup plus ch\u00e8re. Je vais expliquer les deux m\u00e9thodes en d\u00e9tail dans les sections suivantes.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p><strong><span style=\"color:#6038b2\" class=\"has-inline-color\">Note :<\/span><\/strong> Le capteur BME688 a besoin d'un certain temps pour s'adapter \u00e0 l'environnement et s'habituer. Veillez \u00e0 le laisser fonctionner pendant au moins 24 heures avant d'enregistrer vos donn\u00e9es d'entra\u00eenement.<\/p>\n<\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\">Enregistrer des donn\u00e9es avec la carte navette BME688<\/h3>\n\n\n\n<p>BOSCH a \u00e9quip\u00e9 la navette de huit capteurs BME688, ce qui lui permet de produire huit fois plus de donn\u00e9es dans le m\u00eame laps de temps. Tous les logiciels sont d\u00e9j\u00e0 install\u00e9s et l'appareil est pr\u00eat \u00e0 fonctionner d\u00e8s sa sortie de la bo\u00eete. Regardez <a href=\"https:\/\/youtu.be\/4vdliMRtxBY\">ce tutoriel vid\u00e9o de Bosch<\/a> pour en savoir plus sur le processus de mesure.<\/p>\n\n\n\n<p>Si vous enregistrez de nombreux sp\u00e9cimens en une seule session, vous pouvez noter l'ordre des sp\u00e9cimens pour \u00e9viter toute confusion. Vous pouvez toujours recadrer les donn\u00e9es dans AI Studio par la suite, alors n'ayez pas peur de capturer beaucoup de donn\u00e9es.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Enregistrer des donn\u00e9es avec la carte BME688 Breakout Board<\/h3>\n\n\n\n<p>Si vous utilisez le <a style=\"font-size: revert;\" href=\"https:\/\/buyzero.de\/en\/products\/luftqualitatssensor-bosch-bme688-breakout-board?_pos=2&amp;_sid=9d841f7fd&amp;_ss=r\">BME688 Breakout Board<\/a><span style=\"font-size: revert; color: initial;\"> <\/span>Je vous conseille quand m\u00eame de regarder le <a href=\"https:\/\/youtu.be\/4vdliMRtxBY\">Tutoriel Bosch<\/a> car il fournit des informations utiles sur le processus de formation dans AI Studio. Mais pour enregistrer les donn\u00e9es de formation, certaines \u00e9tapes suppl\u00e9mentaires sont n\u00e9cessaires.<\/p>\n\n\n\n<p>Nous, \u00e0 <a href=\"https:\/\/pi3g.com\/\">pi3g<\/a> a cr\u00e9\u00e9 une biblioth\u00e8que python pour les capteurs BME68X, que vous pouvez mettre \u00e0 jour avec <a href=\"https:\/\/www.bosch-sensortec.com\/software-tools\/software\/bme688-software\/\">Boschs BSEC 2.0<\/a>. Il est donc utile que vous ayez une certaine exp\u00e9rience de Python, mais ce n'est pas n\u00e9cessaire.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p><strong><span style=\"color:#6038b2\" class=\"has-inline-color\">Note :<\/span><\/strong> Voir les instructions d'installation et d'utilisation directement sur notre <a href=\"https:\/\/github.com\/pi3g\/bme68x-python-library\">GitHub<\/a>.<\/p>\n<\/blockquote>\n\n\n\n<p>Commencez par cloner notre <a href=\"https:\/\/github.com\/pi3g\/bme68x-python-library\">bme68x-python-library<\/a>. Ceci peut \u00eatre fait en ex\u00e9cutant la commande suivante dans un terminal bash.<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:block;padding:16px 0 0 16px;margin-bottom:-1px;width:100%;text-align:left;background-color:#2e3440ff\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"54\" height=\"14\" viewbox=\"0 0 54 14\"><g fill=\"none\" fill-rule=\"evenodd\" transform=\"translate(1 1)\"><circle cx=\"6\" cy=\"6\" r=\"6\" fill=\"#FF5F56\" stroke=\"#E0443E\" stroke-width=\".5\"><\/circle><circle cx=\"26\" cy=\"6\" r=\"6\" fill=\"#FFBD2E\" stroke=\"#DEA123\" stroke-width=\".5\"><\/circle><circle cx=\"46\" cy=\"6\" r=\"6\" fill=\"#27C93F\" stroke=\"#1AAB29\" stroke-width=\".5\"><\/circle><\/g><\/svg><\/span><span role=\"button\" tabindex=\"0\" data-code=\"git clone https:\/\/github.com\/pi3g\/bme68x-python-library.git\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copie\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code data-no-translation=\"\"><span class=\"line\"><span style=\"color: #D8DEE9\">git<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #D8DEE9\">clone<\/span><span style=\"color: #D8DEE9FF\"> https<\/span><span style=\"color: #ECEFF4\">:<\/span><span style=\"color: #616E88\">\/\/github.com\/pi3g\/bme68x-python-library.git<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>Vous devez maintenant construire et installer le module python bme68x. Le site <a href=\"https:\/\/www.bosch-sensortec.com\/software-tools\/software\/bme688-software\/\">BSEC 2.0<\/a> est un logiciel propri\u00e9taire, vous devez donc t\u00e9l\u00e9charger la version 2.0.6.1 directement de Bosch et accepter leur licence. D\u00e9compressez-le dans le dossier bme68x-python-library et proc\u00e9dez aux commandes suivantes.<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:block;padding:16px 0 0 16px;margin-bottom:-1px;width:100%;text-align:left;background-color:#2e3440ff\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"54\" height=\"14\" viewbox=\"0 0 54 14\"><g fill=\"none\" fill-rule=\"evenodd\" transform=\"translate(1 1)\"><circle cx=\"6\" cy=\"6\" r=\"6\" fill=\"#FF5F56\" stroke=\"#E0443E\" stroke-width=\".5\"><\/circle><circle cx=\"26\" cy=\"6\" r=\"6\" fill=\"#FFBD2E\" stroke=\"#DEA123\" stroke-width=\".5\"><\/circle><circle cx=\"46\" cy=\"6\" r=\"6\" fill=\"#27C93F\" stroke=\"#1AAB29\" stroke-width=\".5\"><\/circle><\/g><\/svg><\/span><span role=\"button\" tabindex=\"0\" data-code=\"cd path\/to\/bme68x-python-librarysudo python3 setup.py install\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copie\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code data-no-translation=\"\"><span class=\"line\"><span style=\"color: #D8DEE9\">cd<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #D8DEE9\">path<\/span><span style=\"color: #81A1C1\">\/<\/span><span style=\"color: #D8DEE9\">to<\/span><span style=\"color: #81A1C1\">\/<\/span><span style=\"color: #D8DEE9\">bme68x<\/span><span style=\"color: #81A1C1\">-<\/span><span style=\"color: #D8DEE9\">python<\/span><span style=\"color: #81A1C1\">-<\/span><span style=\"color: #D8DEE9\">library<\/span><\/span>\n<span class=\"line\"><span style=\"color: #D8DEE9\">sudo<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #D8DEE9\">python3<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #D8DEE9\">setup<\/span><span style=\"color: #ECEFF4\">.<\/span><span style=\"color: #D8DEE9\">py<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #D8DEE9\">install<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>Vous pouvez maintenant ex\u00e9cuter le <strong>bmerawdata.py<\/strong> avec les param\u00e8tres par d\u00e9faut.<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:block;padding:16px 0 0 16px;margin-bottom:-1px;width:100%;text-align:left;background-color:#2e3440ff\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"54\" height=\"14\" viewbox=\"0 0 54 14\"><g fill=\"none\" fill-rule=\"evenodd\" transform=\"translate(1 1)\"><circle cx=\"6\" cy=\"6\" r=\"6\" fill=\"#FF5F56\" stroke=\"#E0443E\" stroke-width=\".5\"><\/circle><circle cx=\"26\" cy=\"6\" r=\"6\" fill=\"#FFBD2E\" stroke=\"#DEA123\" stroke-width=\".5\"><\/circle><circle cx=\"46\" cy=\"6\" r=\"6\" fill=\"#27C93F\" stroke=\"#1AAB29\" stroke-width=\".5\"><\/circle><\/g><\/svg><\/span><span role=\"button\" tabindex=\"0\" data-code=\"cd tools\/bmerawdatapython3 bmerawdata.py\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copie\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code data-no-translation=\"\"><span class=\"line\"><span style=\"color: #D8DEE9\">cd<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #D8DEE9\">tools<\/span><span style=\"color: #81A1C1\">\/<\/span><span style=\"color: #D8DEE9\">bmerawdata<\/span><\/span>\n<span class=\"line\"><span style=\"color: #D8DEE9\">python3<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #D8DEE9\">bmerawdata<\/span><span style=\"color: #ECEFF4\">.<\/span><span style=\"color: #D8DEE9\">py<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>Le script affichera les donn\u00e9es enregistr\u00e9es apr\u00e8s chaque mesure. Terminez le script et enregistrez les donn\u00e9es dans un fichier compatible AI Studio en appuyant sur <strong>Ctrl+c<\/strong>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">3. Entra\u00eener l'algorithme<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Importer des donn\u00e9es<\/h3>\n\n\n\n<p>Peu importe que vous utilisiez le <a style=\"font-size: revert;\" href=\"https:\/\/buyzero.de\/en\/products\/luftqualitatssensor-bosch-bme688-breakout-board?_pos=2&amp;_sid=9d841f7fd&amp;_ss=r\">BME688 Breakout Board<\/a><span style=\"font-size: revert; color: initial;\"> ou le <\/span><a style=\"font-size: revert;\" href=\"https:\/\/buyzero.de\/en\/products\/bosch-bme688-gas-sensor-developer-kit?variant=37884583182516\">Kit de d\u00e9veloppement du capteur de gaz Bosch BME688<\/a>L'\u00e9tape suivante consiste \u00e0 importer les donn\u00e9es dans AI Studio. Appuyez sur le bouton <span style=\"background-color:#0a3ec2\" class=\"tadv-background-color\"> <span style=\"color:#074b68\" class=\"has-inline-color\"><strong><span style=\"color:#ffffff\" class=\"tadv-color\">Importer des donn\u00e9es<\/span><\/strong><\/span> <\/span> et s\u00e9lectionnez votre fichier .bmerawdata.<\/p>\n\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"919\" height=\"762\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ImportData.png\" alt=\"\" class=\"wp-image-1453\" style=\"width:509px;height:421px\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ImportData.png 919w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ImportData-300x249.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ImportData-768x637.png 768w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ImportData-14x12.png 14w\" sizes=\"auto, (max-width: 919px) 100vw, 919px\" \/><figcaption class=\"wp-element-caption\">Dialogue d'importation de donn\u00e9es<\/figcaption><\/figure>\n<\/div>\n\n\n<p>Votre session doit avoir un nom significatif. Il convient de choisir une \u00e9num\u00e9ration des sp\u00e9cimens.<\/p>\n\n\n\n<p>Vous pouvez voir un graphique de vos donn\u00e9es, par exemple pour le canal de donn\u00e9es sur les gaz, comme indiqu\u00e9 ci-dessous.<\/p>\n\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"456\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-GasDataChannel-1024x456.png\" alt=\"\" class=\"wp-image-1454\" style=\"width:705px;height:314px\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-GasDataChannel-1024x456.png 1024w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-GasDataChannel-300x134.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-GasDataChannel-768x342.png 768w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-GasDataChannel-18x8.png 18w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-GasDataChannel.png 1402w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Canal de donn\u00e9es sur les gaz<\/figcaption><\/figure>\n<\/div>\n\n\n<p>Si les donn\u00e9es proviennent de la carte navette, vous pouvez basculer entre les donn\u00e9es des huit capteurs. Chacune des lignes color\u00e9es repr\u00e9sente une \u00e9tape du profil de chauffe qui a \u00e9t\u00e9 utilis\u00e9 pour capturer les donn\u00e9es.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p><strong><span style=\"color:#6038b2\" class=\"has-inline-color\">Note :<\/span><\/strong> Dans la plupart des cas, vous ne devez utiliser que le canal de donn\u00e9es du gaz pour la formation.<\/p>\n<\/blockquote>\n\n\n\n<p>Nous devons maintenant \u00e9tiqueter nos sp\u00e9cimens. Si vous avez enregistr\u00e9 les donn\u00e9es \u00e0 l'aide de la carte navette et utilis\u00e9 les boutons embarqu\u00e9s pour marquer les sp\u00e9cimens, vous pourrez d\u00e9j\u00e0 voir un mod\u00e8le pour chacun d'entre eux. Vous pouvez \u00e9galement recadrer les sp\u00e9cimens et en cr\u00e9er de nouveaux (par exemple si vous avez enregistr\u00e9 plusieurs sp\u00e9cimens \u00e0 l'aide de notre tableau d'affichage).<\/p>\n\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"419\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-SpecimenLabels-1024x419.png\" alt=\"\" class=\"wp-image-1455\" style=\"width:620px;height:253px\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-SpecimenLabels-1024x419.png 1024w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-SpecimenLabels-300x123.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-SpecimenLabels-768x314.png 768w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-SpecimenLabels-18x7.png 18w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-SpecimenLabels.png 1146w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">\u00c9tiquettes de sp\u00e9cimen et horodateurs<\/figcaption><\/figure>\n<\/div>\n\n\n<p>Apr\u00e8s avoir termin\u00e9 l'\u00e9dition de la session, appuyez sur le bouton<span style=\"color:#074b68\" class=\"has-inline-color\"><strong> <span style=\"background-color:#0a3ec2\" class=\"tadv-background-color\"> <span style=\"color:#074b68\" class=\"has-inline-color\"><strong><span style=\"color:#ffffff\" class=\"tadv-color\">Importer des donn\u00e9es<\/span><\/strong><\/span> <\/span> <\/strong><\/span>dans le coin inf\u00e9rieur droit de la bo\u00eete de dialogue.<\/p>\n\n\n\n<p>Une fois que vous avez import\u00e9 et \u00e9tiquet\u00e9 tous vos sp\u00e9cimens, il est temps de cr\u00e9er et d'entra\u00eener l'algorithme.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Cr\u00e9er l'algorithme<\/h3>\n\n\n\n<p>S\u00e9lectionnez <span class=\"tadv-color\" style=\"color:#0a3ec2\"><span class=\"tadv-background-color\" style=\"background-color:#f5f5f5\"> <strong>Mes algorithmes<\/strong><\/span><\/span> en haut et cliquez sur <span class=\"tadv-background-color\" style=\"background-color:#0a3ec2\"> <mark style=\"background-color:rgba(0, 0, 0, 0);color:#074b68\" class=\"has-inline-color\"><strong><span class=\"tadv-color\" style=\"color:#ffffff\">+ Nouvel algorithme<\/span><\/strong><\/mark> <\/span>. Donnez \u00e0 votre algorithme un nom qui repr\u00e9sente ce qu'il est cens\u00e9 faire, dans mon cas <strong>AirMeatCheese<\/strong>. Ensuite, ajoutez les classes. J'ai appel\u00e9 mes classes NormalAir, Viande et Fromage. S\u00e9lectionnez quels sp\u00e9cimens appartiennent \u00e0 quelle classe et choisissez une couleur pour chaque classe.<\/p>\n\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"529\" height=\"339\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-NameAlgorithm.png\" alt=\"Nommez votre algorithme\" class=\"wp-image-1458\" style=\"width:420px;height:269px\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-NameAlgorithm.png 529w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-NameAlgorithm-300x192.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-NameAlgorithm-18x12.png 18w\" sizes=\"auto, (max-width: 529px) 100vw, 529px\" \/><figcaption class=\"wp-element-caption\">Nommez votre algorithme<\/figcaption><\/figure>\n<\/div>\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"397\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Classes-1024x397.png\" alt=\"Modifier vos classes\" class=\"wp-image-1459\" style=\"width:685px;height:265px\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Classes-1024x397.png 1024w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Classes-300x116.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Classes-768x298.png 768w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Classes-18x7.png 18w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Classes.png 1147w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Modifier vos classes<\/figcaption><\/figure>\n<\/div>\n\n\n<p>Pour ajouter ou supprimer des sp\u00e9cimens, vous pouvez cliquer sur l'une des classes. Voici un exemple de ce que le <strong>Viande<\/strong> ressemble \u00e0 une classe.<\/p>\n\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"699\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassSettings-1024x699.png\" alt=\"Vue de la classe de viande\" class=\"wp-image-1460\" style=\"width:679px;height:463px\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassSettings-1024x699.png 1024w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassSettings-300x205.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassSettings-768x524.png 768w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassSettings-18x12.png 18w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassSettings.png 1297w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Vue de la classe de viande<\/figcaption><\/figure>\n<\/div>\n\n\n<p>Sous les classes, vous pouvez voir quelques donn\u00e9es suppl\u00e9mentaires sur l'algorithme.<\/p>\n\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"520\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassesData-1024x520.png\" alt=\"Donn\u00e9es suppl\u00e9mentaires sur l&#039;algorithme\" class=\"wp-image-1462\" style=\"width:663px;height:336px\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassesData-1024x520.png 1024w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassesData-300x152.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassesData-768x390.png 768w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassesData-18x9.png 18w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ClassesData.png 1147w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Donn\u00e9es suppl\u00e9mentaires sur l'algorithme<\/figcaption><\/figure>\n<\/div>\n\n\n<p>La balance des donn\u00e9es montre la dur\u00e9e totale de mesure pour chaque classe. Pour garantir les meilleures performances, la dur\u00e9e de mesure de chaque classe doit \u00eatre \u00e9gale. Si la dur\u00e9e de mesure de l'une des classes est beaucoup plus longue, l'algorithme risque de privil\u00e9gier cette classe. Notez \u00e9galement le bouton point d'interrogation situ\u00e9 devant chaque rubrique. Appuyez dessus pour obtenir des informations plus d\u00e9taill\u00e9es.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-style-default is-layout-flow wp-block-quote-is-layout-flow\">\n<p><strong><span style=\"color:#6038b2\" class=\"has-inline-color\">Note :<\/span><\/strong> Pour plus d'informations, consultez la documentation du BME688 AI Studio.<\/p>\n<\/blockquote>\n\n\n\n<p>Dans la section des canaux de donn\u00e9es, vous pouvez s\u00e9lectionner, parmi les quatre sorties de capteur, celle que vous souhaitez utiliser pour votre algorithme. Je recommande de n'utiliser que le canal de donn\u00e9es du gaz, car les autres canaux d\u00e9pendent principalement de l'environnement et non de l'\u00e9chantillon. Une fois que vous avez tout configur\u00e9, il est temps de proc\u00e9der \u00e0 l'entra\u00eenement.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Formation et exportation<\/h3>\n\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"473\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Training-1024x473.png\" alt=\"Entra\u00eenez votre algorithme\" class=\"wp-image-1464\" style=\"width:719px;height:332px\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Training-1024x473.png 1024w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Training-300x139.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Training-768x355.png 768w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Training-18x8.png 18w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-Training.png 1158w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Entra\u00eenez votre algorithme<\/figcaption><\/figure>\n<\/div>\n\n\n<p>Vous pouvez y s\u00e9lectionner la m\u00e9thode de formation, le nombre maximal de tours et le fractionnement des donn\u00e9es. Si vous \u00eates novice en mati\u00e8re de r\u00e9seaux neuronaux, vous devriez laisser les param\u00e8tres par d\u00e9faut. N\u00e9anmoins, je vais essayer d'expliquer bri\u00e8vement chacun de ces param\u00e8tres.<\/p>\n\n\n\n<p>La seule m\u00e9thode de formation disponible au moment o\u00f9 j'\u00e9cris ces lignes est l'optimiseur ADAM. Il s'agit d'une m\u00e9thode sp\u00e9cifique pour trouver un minimum dans la fonction d'erreur (moins d'erreur signifie des pr\u00e9dictions plus pr\u00e9cises). Vous pouvez s\u00e9lectionner diff\u00e9rentes tailles de lots pour am\u00e9liorer la vitesse et la stabilit\u00e9 de l'apprentissage.<\/p>\n\n\n\n<p>L'augmentation du nombre maximal de cycles de formation est un autre moyen d'am\u00e9liorer les performances de l'algorithme. Pour chaque tour (souvent appel\u00e9 \"\u00e9poque\"), AI Studio fait passer l'ensemble des donn\u00e9es de formation dans le r\u00e9seau neuronal. Cela signifie qu'un nombre plus \u00e9lev\u00e9 de cycles maximum augmentera le temps n\u00e9cessaire \u00e0 l'entra\u00eenement de l'algorithme. La plupart du temps, AI Studio d\u00e9tecte si un minimum est atteint et termine la formation avant que les tours maximums ne soient atteints. Cela permet de r\u00e9duire le temps de formation et d'\u00e9viter le surajustement.<\/p>\n\n\n\n<p>Le surajustement signifie que le r\u00e9seau neuronal s'est trop adapt\u00e9 aux donn\u00e9es de formation. Si l'algorithme obtient une pr\u00e9cision tr\u00e8s \u00e9lev\u00e9e lors de la formation, mais qu'il est peu performant lors des tests en situation r\u00e9elle, il est pr\u00e9f\u00e9rable de r\u00e9duire le nombre maximal de cycles de formation.<\/p>\n\n\n\n<p>Le param\u00e8tre de division des donn\u00e9es vous permet de s\u00e9lectionner la part de vos donn\u00e9es enregistr\u00e9es qui sera utilis\u00e9e pour la formation et celle qui sera utilis\u00e9e pour les tests. Vous devez \u00e9viter d'utiliser plus d'un tiers des donn\u00e9es pour les tests. Comme son nom l'indique, l'algorithme n'utilisera que les donn\u00e9es de formation pour la formation. Une fois la formation termin\u00e9e, AI Studio \u00e9valuera l'algorithme en utilisant les donn\u00e9es de test, qu'il n'a jamais vues auparavant.<\/p>\n\n\n\n<p>Appuyez sur <span style=\"color:#074b68\" class=\"has-inline-color\"><strong><span style=\"background-color:#0a3ec2\" class=\"tadv-background-color\"> <span style=\"color:#074b68\" class=\"has-inline-color\"><strong><span style=\"color:#ffffff\" class=\"tadv-color\">Former le r\u00e9seau neuronal<\/span><\/strong><\/span> <\/span><\/strong><\/span> pour commencer l'entra\u00eenement. Vous verrez le temps de formation restant estim\u00e9 et le graphique lin\u00e9aire de la pr\u00e9cision et des pertes.<\/p>\n\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"549\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-TrainingProcess-1024x549.png\" alt=\"Progression de la formation\" class=\"wp-image-1467\" style=\"width:772px;height:413px\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-TrainingProcess-1024x549.png 1024w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-TrainingProcess-300x161.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-TrainingProcess-768x412.png 768w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-TrainingProcess-18x10.png 18w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-TrainingProcess.png 1107w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Progression de la formation<\/figcaption><\/figure>\n<\/div>\n\n\n<p>\u00c0 chaque \u00e9poque, la pr\u00e9cision et la pr\u00e9cision de validation devraient s'am\u00e9liorer, tandis que la perte et la perte de validation devraient diminuer. Attendez que l'entra\u00eenement soit termin\u00e9.<\/p>\n\n\n\n<p>Lorsque la formation est termin\u00e9e, v\u00e9rifiez la matrice de confusion. Elle contient des informations importantes sur les r\u00e9sultats de la formation. La statistique la plus int\u00e9ressante est la pr\u00e9cision, mais si vos donn\u00e9es d'entra\u00eenement sont r\u00e9parties de mani\u00e8re in\u00e9gale, le score F1 peut \u00eatre une meilleure mesure.<\/p>\n\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"505\" src=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ConfusionMatrix-1024x505.png\" alt=\"Matrice de confusion et r\u00e9sultats de la formation\" class=\"wp-image-1468\" style=\"width:702px;height:346px\" srcset=\"https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ConfusionMatrix-1024x505.png 1024w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ConfusionMatrix-300x148.png 300w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ConfusionMatrix-768x379.png 768w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ConfusionMatrix-18x9.png 18w, https:\/\/picockpit.com\/raspberry-pi\/wp-content\/uploads\/2022\/01\/BME688-ConfusionMatrix.png 1096w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Matrice de confusion et r\u00e9sultats de la formation<\/figcaption><\/figure>\n<\/div>\n\n\n<p>Vous obtiendrez rarement une pr\u00e9cision sup\u00e9rieure \u00e0 90%. Si la pr\u00e9cision est sup\u00e9rieure \u00e0 80%, vous devriez exporter l'algorithme pour le tester. Nous d\u00e9tecterons les odeurs en utilisant notre <a style=\"font-size: revert;\" href=\"https:\/\/www.picockpit.com\/\">PiCockpit<\/a> interface web. Assurez-vous d'exporter l'algorithme pour la version 2.0.6.1 de BSEC depuis <a style=\"font-size: revert;\" href=\"https:\/\/www.picockpit.com\/\">PiCockpit<\/a> ne prend en charge que cette version pour l'instant.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p><strong><span style=\"color:#6038b2\" class=\"has-inline-color\">Note :<\/span><\/strong> Dans la plupart des cas, la formation sera termin\u00e9e avant que la dur\u00e9e estim\u00e9e ne soit atteinte.<\/p>\n<\/blockquote>\n\n\n\n<h2 class=\"wp-block-heading\">4. D\u00e9tecter les odeurs<\/h2>\n\n\n\n<p>Pour d\u00e9tecter les odeurs, il suffit d'installer le <a style=\"font-size: revert;\" href=\"https:\/\/www.picockpit.com\/\">PiCockpit<\/a> et le connecter \u00e0 votre compte. Si vous n'avez pas <a style=\"font-size: revert;\" href=\"https:\/\/www.picockpit.com\/\">PiCockpit<\/a> mais il suffit de s'inscrire gratuitement et de suivre les instructions qui y sont donn\u00e9es. Notre application Digital Nose vous permet de t\u00e9l\u00e9charger votre algorithme entra\u00een\u00e9 et de voir les pr\u00e9dictions en direct via l'interface web. Consultez le <a href=\"https:\/\/picockpit.com\/raspberry-pi\/bme688-digitalnose-detect-different-smell-patterns-with-bosch-bme688-sensor-and-ai-technology\/\">Aide num\u00e9rique pour le nez<\/a> pour une explication compl\u00e8te sur la fa\u00e7on d'utiliser l'application.<\/p>\n\n\n\n<p>Une autre fa\u00e7on de d\u00e9tecter les odeurs est d'utiliser notre <a href=\"https:\/\/github.com\/pi3g\/bme68x-python-library\">Extension Python BME68X<\/a>. Cela n\u00e9cessite un peu de codage python mais offre plus de contr\u00f4le et vous permet de cr\u00e9er vos propres applications en utilisant votre algorithme. Reportez-vous au <a href=\"https:\/\/github.com\/pi3g\/bme68x-python-library\/blob\/main\/README.md\">README.md<\/a>le <a href=\"https:\/\/github.com\/pi3g\/bme68x-python-library\/blob\/main\/PythonDocumentation.md\">Documentation.md<\/a> et le <a href=\"https:\/\/github.com\/pi3g\/bme68x-python-library\/tree\/main\/examples\">exemples<\/a> pour savoir comment installer et utiliser l'extension.<\/p>\n\n\n\n<p>Et voil\u00e0, vous l'avez. Vous devriez maintenant \u00eatre en mesure d'enregistrer des donn\u00e9es, d'entra\u00eener votre algorithme et de d\u00e9tecter des odeurs. Veuillez me faire savoir si vous avez trouv\u00e9 ce guide utile ou si vous avez rencontr\u00e9 des difficult\u00e9s en le suivant.<\/p>\n\n\n\n<p>Contactez-moi \u00e0 l'adresse nathan@pi3g.com<\/p>\n<div class=\"shariff shariff-align-center shariff-widget-align-left shariff-buttonstretch\"><ul class=\"shariff-buttons theme-white orientation-horizontal buttonsize-medium\"><li class=\"shariff-button twitter shariff-nocustomcolor\" style=\"background-color:#595959\"><a href=\"https:\/\/twitter.com\/share?url=https%3A%2F%2Fpicockpit.com%2Fraspberry-pi%2Ffr%2Fteach-bme688-how-to-smell%2F&text=Teach%20your%20BME688%20how%20to%20smell\" title=\"Envoyer par X\" aria-label=\"Envoyer par X\" role=\"button\" rel=\"noopener nofollow\" class=\"shariff-link\" style=\"; background-color:#000; color:#000\" target=\"_blank\"><span class=\"shariff-icon\" style=\"fill:#000\"><svg width=\"32px\" height=\"20px\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 24 24\"><path fill=\"#000\" d=\"M14.258 10.152L23.176 0h-2.113l-7.747 8.813L7.133 0H0l9.352 13.328L0 23.973h2.113l8.176-9.309 6.531 9.309h7.133zm-2.895 3.293l-.949-1.328L2.875 1.56h3.246l6.086 8.523.945 1.328 7.91 11.078h-3.246zm0 0\"\/><\/svg><\/span><span class=\"shariff-text\" style=\"color:#000\">partager<\/span>&nbsp;<\/a><\/li><li class=\"shariff-button facebook shariff-nocustomcolor\" style=\"background-color:#4273c8\"><a href=\"https:\/\/www.facebook.com\/sharer\/sharer.php?u=https%3A%2F%2Fpicockpit.com%2Fraspberry-pi%2Ffr%2Fteach-bme688-how-to-smell%2F\" title=\"Envoyer par Facebook\" aria-label=\"Envoyer par Facebook\" role=\"button\" rel=\"nofollow\" class=\"shariff-link\" style=\"; background-color:#3b5998; color:#3b5998\" target=\"_blank\"><span class=\"shariff-icon\" style=\"fill:#3b5998\"><svg width=\"32px\" height=\"20px\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 18 32\"><path fill=\"#3b5998\" d=\"M17.1 0.2v4.7h-2.8q-1.5 0-2.1 0.6t-0.5 1.9v3.4h5.2l-0.7 5.3h-4.5v13.6h-5.5v-13.6h-4.5v-5.3h4.5v-3.9q0-3.3 1.9-5.2t5-1.8q2.6 0 4.1 0.2z\"\/><\/svg><\/span><span class=\"shariff-text\" style=\"color:#3b5998\">partager<\/span>&nbsp;<\/a><\/li><li class=\"shariff-button telegram shariff-nocustomcolor\" style=\"background-color:#4084A6\"><a href=\"https:\/\/telegram.me\/share\/url?url=https%3A%2F%2Fpicockpit.com%2Fraspberry-pi%2Ffr%2Fteach-bme688-how-to-smell%2F&text=Teach%20your%20BME688%20how%20to%20smell\" title=\"Envoyer par Telegram\" aria-label=\"Envoyer par Telegram\" role=\"button\" rel=\"noopener nofollow\" class=\"shariff-link\" style=\"; background-color:#0088cc; color:#0088cc\" target=\"_blank\"><span class=\"shariff-icon\" style=\"fill:#0088cc\"><svg width=\"32px\" height=\"20px\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 32 32\"><path fill=\"#0088cc\" d=\"M30.8 6.5l-4.5 21.4c-.3 1.5-1.2 1.9-2.5 1.2L16.9 24l-3.3 3.2c-.4.4-.7.7-1.4.7l.5-7L25.5 9.2c.6-.5-.1-.8-.9-.3l-15.8 10L2 16.7c-1.5-.5-1.5-1.5.3-2.2L28.9 4.3c1.3-.5 2.3.3 1.9 2.2z\"\/><\/svg><\/span><span class=\"shariff-text\" style=\"color:#0088cc\">partager<\/span>&nbsp;<\/a><\/li><li class=\"shariff-button reddit shariff-nocustomcolor\" style=\"background-color:#ff5700\"><a href=\"https:\/\/www.reddit.com\/submit?url=https%3A%2F%2Fpicockpit.com%2Fraspberry-pi%2Ffr%2Fteach-bme688-how-to-smell%2F\" title=\"Envoyer par Reddit\" aria-label=\"Envoyer par Reddit\" role=\"button\" rel=\"noopener nofollow\" class=\"shariff-link\" style=\"; background-color:#ff4500; color:#ff4500\" target=\"_blank\"><span class=\"shariff-icon\" style=\"fill:#ff4500\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 512 512\"><path fill=\"#ff4500\" d=\"M440.3 203.5c-15 0-28.2 6.2-37.9 15.9-35.7-24.7-83.8-40.6-137.1-42.3L293 52.3l88.2 19.8c0 21.6 17.6 39.2 39.2 39.2 22 0 39.7-18.1 39.7-39.7s-17.6-39.7-39.7-39.7c-15.4 0-28.7 9.3-35.3 22l-97.4-21.6c-4.9-1.3-9.7 2.2-11 7.1L246.3 177c-52.9 2.2-100.5 18.1-136.3 42.8-9.7-10.1-23.4-16.3-38.4-16.3-55.6 0-73.8 74.6-22.9 100.1-1.8 7.9-2.6 16.3-2.6 24.7 0 83.8 94.4 151.7 210.3 151.7 116.4 0 210.8-67.9 210.8-151.7 0-8.4-.9-17.2-3.1-25.1 49.9-25.6 31.5-99.7-23.8-99.7zM129.4 308.9c0-22 17.6-39.7 39.7-39.7 21.6 0 39.2 17.6 39.2 39.7 0 21.6-17.6 39.2-39.2 39.2-22 .1-39.7-17.6-39.7-39.2zm214.3 93.5c-36.4 36.4-139.1 36.4-175.5 0-4-3.5-4-9.7 0-13.7 3.5-3.5 9.7-3.5 13.2 0 27.8 28.5 120 29 149 0 3.5-3.5 9.7-3.5 13.2 0 4.1 4 4.1 10.2.1 13.7zm-.8-54.2c-21.6 0-39.2-17.6-39.2-39.2 0-22 17.6-39.7 39.2-39.7 22 0 39.7 17.6 39.7 39.7-.1 21.5-17.7 39.2-39.7 39.2z\"\/><\/svg><\/span><span class=\"shariff-text\" style=\"color:#ff4500\">partager<\/span>&nbsp;<\/a><\/li><\/ul><\/div>","protected":false},"excerpt":{"rendered":"<p>Un guide complet sur la fa\u00e7on d'entra\u00eener votre capteur BME688 Salut les amateurs de technologie ! Bosch a lanc\u00e9 le BME688, un nouveau capteur g\u00e9nial qui peut distinguer jusqu'\u00e0 quatre odeurs diff\u00e9rentes. Ce guide vous expliquera tous les d\u00e9tails pour apprendre \u00e0 votre BME688 \u00e0 distinguer les odeurs. Ne vous inqui\u00e9tez pas si vous \u00eates novice en IA ou en Python.....<\/p>","protected":false},"author":3,"featured_media":5957,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[67,3],"tags":[210,850,849,856,797,851,816,858,854,462,855,193,486,447,476,187,853,857,852],"class_list":["post-1422","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-picockpit-apps","category-raspberry-pi-how-to","tag-ai","tag-ai-studio","tag-beginners-guid","tag-bme-board","tag-bme688","tag-bosch","tag-bsec","tag-digital-nose","tag-fragrance","tag-newbie","tag-perfume","tag-picockpit","tag-project","tag-projects","tag-python","tag-raspberry-pi","tag-scent","tag-shuttle-board","tag-smell"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Teach your BME688 how to smell | 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