{"id":22606,"date":"2020-10-29T12:59:40","date_gmt":"2020-10-29T11:59:40","guid":{"rendered":"https:\/\/www.regestaitalia.eu\/internet-of-things-how-to-make-the-most-of-the-data-collected-through-machine-learning\/"},"modified":"2025-06-03T15:33:39","modified_gmt":"2025-06-03T13:33:39","slug":"internet-of-things-how-to-make-the-most-of-the-data-collected-through-machine-learning","status":"publish","type":"post","link":"https:\/\/www.regestaitalia.eu\/en\/internet-of-things-how-to-make-the-most-of-the-data-collected-through-machine-learning\/","title":{"rendered":"Internet of Things: how to make the most of the data collected through Machine Learning"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-padding-right-small:0px;--awb-padding-left-small:0px;--awb-margin-bottom:40px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1497.6px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-1\"><p><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">The thrust of the<\/span><b><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">Industry 4.0<\/span> <\/b><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">is leading more and more production lines to be fully sensorized: the IoT devices with which they are equipped generate Data Lake, large amounts of data that are often historicized and never used again.<\/span><\/p>\n<h2 class=\"fusion-responsive-typography-calculated\" data-fontsize=\"44\" data-lineheight=\"52.8px\"><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">How to extrapolate value from data that are in quantities unmanageable by human beings?<\/span><\/h2>\n<p><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">The answer is the <\/span><strong data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">Machine Learning<\/strong><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">, which makes it possible to create algorithms that automate the discovery of knowledge contained in data.<\/span><\/p>\n<\/div><\/div><\/div><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-1 fusion_builder_column_1_2 1_2 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:50%;--awb-margin-top-large:0px;--awb-spacing-right-large:3.84%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:3.84%;--awb-width-medium:50%;--awb-order-medium:0;--awb-spacing-right-medium:3.84%;--awb-spacing-left-medium:3.84%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-video fusion-selfhosted-video\" style=\"max-width:100%;\"><div class=\"video-wrapper\"><video playsinline=\"true\" width=\"100%\" style=\"object-fit: cover;\" autoplay=\"true\" muted=\"true\" loop=\"true\" preload=\"auto\" controls=\"1\"><source src=\"https:\/\/www.regestaitalia.eu\/wp-content\/uploads\/2020\/10\/regestaLab_20-10_ped_infografica.mp4\" type=\"video\/mp4\">Sorry, your browser doesn&#039;t support embedded videos.<\/video><\/div><\/div><\/div><\/div><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-2 fusion_builder_column_1_2 1_2 fusion-flex-column fusion-flex-align-self-stretch\" style=\"--awb-bg-size:cover;--awb-width-large:50%;--awb-margin-top-large:0px;--awb-spacing-right-large:3.84%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:3.84%;--awb-width-medium:50%;--awb-order-medium:0;--awb-spacing-right-medium:3.84%;--awb-spacing-left-medium:3.84%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-center fusion-content-layout-column\"><div class=\"fusion-text fusion-text-2\"><p><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">Perhaps the best known task for which Machine Learning is applied is the<\/span><b><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">training of <\/span><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">predictive models<\/span><\/b><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">: by providing examples derived from the collected data, an algorithm can be trained to make predictions about an objective index, representing the event or business value that one is interested in knowing in advance.<\/span><\/p>\n<p><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">This process enables the creation of a statistical decision support tool to be provided to domain experts.<\/span><\/p>\n<\/div><\/div><\/div><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-3 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-3\"><p data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">The predictive models that can be built fall into two macro-families:<\/p>\n<ul>\n<li><b><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">Models of <\/span><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">classification<\/span><\/b><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">: The objective index is a discrete value; it could be the occurrence or non-occurrence of a particular event to be monitored.<\/span><\/li>\n<li><b><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">Models of <\/span><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">regression<\/span><\/b><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">: the target index is a continuous value, could in this case be a given process variable over time whose trend is to be predicted.<\/span><\/li>\n<\/ul>\n<h2 class=\"fusion-responsive-typography-calculated\" data-fontsize=\"30\" data-lineheight=\"45px\"><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">Data Mining and Machine Learning<\/span><\/h2>\n<p><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">The <\/span><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\"><b>Machine Learning <\/b><\/span><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">however, is not just about creating predictive models: within it is also framed the <\/span><strong data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">Data Mining<\/strong><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">, a set of techniques whose intent is the extrapolation of patterns or rules contained in data.<\/span><\/p>\n<p><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">An example of these approaches is the <\/span><strong data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">clustering<\/strong><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">, which allows examples to be grouped into families, within which similar behaviors are recognized that might be difficult to detect with the human eye.<\/span><\/p>\n<h2 class=\"fusion-responsive-typography-calculated\" data-fontsize=\"44\" data-lineheight=\"66px\"><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">The two <\/span><em><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">use cases<\/span><\/em><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\"> best known where the potential of process data is exploited are certainly:<\/span><\/h2>\n<\/div><\/div><\/div><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-4 fusion_builder_column_1_2 1_2 fusion-flex-column fusion-flex-align-self-stretch\" style=\"--awb-bg-size:cover;--awb-width-large:50%;--awb-margin-top-large:0px;--awb-spacing-right-large:3.84%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:3.84%;--awb-width-medium:50%;--awb-order-medium:0;--awb-spacing-right-medium:3.84%;--awb-spacing-left-medium:3.84%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-center fusion-content-layout-column\"><div class=\"fusion-text fusion-text-4\"><ul>\n<li><strong data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">Predictive Maintenance<\/strong><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">, <\/span><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">where the goal is to estimate the remaining life of components in order to take maintenance action on process assets before they can fail. The goal is to preserve Business Continuity, as maintenance operations have significantly less impact on plant availability than downtime due to failure. <\/span><\/li>\n<li><strong data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">Predictive Quality<\/strong><span data-fusion-font=\"true\" data-fusion-google-font=\"Titillium Web\" data-fusion-google-variant=\"300\">, where the goal is to estimate the quality of a semi-finished or finished product, where a check on it might require working under critical conditions (such as high temperatures) or where taking test samples might be unsustainable in cost or time.<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-5 fusion_builder_column_1_2 1_2 fusion-flex-column fusion-flex-align-self-stretch\" style=\"--awb-bg-size:cover;--awb-width-large:50%;--awb-margin-top-large:0px;--awb-spacing-right-large:3.84%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:3.84%;--awb-width-medium:50%;--awb-order-medium:0;--awb-spacing-right-medium:3.84%;--awb-spacing-left-medium:3.84%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-center fusion-content-layout-column\"><div class=\"fusion-image-element \" style=\"--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\" fusion-imageframe imageframe-none imageframe-1 hover-type-none\"><img decoding=\"async\" width=\"688\" height=\"426\" title=\"regestaLab_20-10_article_post05\" src=\"https:\/\/www.regestaitalia.eu\/wp-content\/uploads\/2020\/10\/regestaLab_20-10_article_post05.jpg\" data-orig-src=\"https:\/\/www.regestaitalia.eu\/wp-content\/uploads\/2020\/10\/regestaLab_20-10_article_post05.jpg\" alt class=\"lazyload img-responsive wp-image-21027\" srcset=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%27http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%27%20width%3D%27688%27%20height%3D%27426%27%20viewBox%3D%270%200%20688%20426%27%3E%3Crect%20width%3D%27688%27%20height%3D%27426%27%20fill-opacity%3D%220%22%2F%3E%3C%2Fsvg%3E\" data-srcset=\"https:\/\/www.regestaitalia.eu\/wp-content\/uploads\/2020\/10\/regestaLab_20-10_article_post05-200x124.jpg 200w, https:\/\/www.regestaitalia.eu\/wp-content\/uploads\/2020\/10\/regestaLab_20-10_article_post05-400x248.jpg 400w, https:\/\/www.regestaitalia.eu\/wp-content\/uploads\/2020\/10\/regestaLab_20-10_article_post05-600x372.jpg 600w, https:\/\/www.regestaitalia.eu\/wp-content\/uploads\/2020\/10\/regestaLab_20-10_article_post05.jpg 688w\" data-sizes=\"auto\" data-orig-sizes=\"(max-width: 640px) 100vw, 688px\" \/><\/span><\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>The vast masses of data acquired through Machine Learning can be leveraged in the Internet of Things. Find out how. <\/p>\n","protected":false},"author":1,"featured_media":21025,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[138],"tags":[],"class_list":["post-22606","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-iot-ml"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Regesta LAB - Internet of Things and data enhancement<\/title>\n<meta name=\"description\" content=\"The vast masses of data acquired through Machine Learning can be leveraged in the Internet of Things. 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