{"id":9953,"date":"2019-01-18T10:00:53","date_gmt":"2019-01-18T09:00:53","guid":{"rendered":"https:\/\/www.statigeneralinnovazione.it\/?p=9953"},"modified":"2023-03-06T09:00:40","modified_gmt":"2023-03-06T08:00:40","slug":"infrastructure-monitoring-for-predictive-maintenance","status":"publish","type":"post","link":"https:\/\/www.statigeneralinnovazione.it\/en\/infrastructure-monitoring-for-predictive-maintenance\/","title":{"rendered":"Infrastructure Monitoring for Predictive Maintenance \u2013 Updated 01\/18\/2019"},"content":{"rendered":"<p>We highlight the contributions<a href=\"https:\/\/www.key4biz.it\/cdti-forum-ponte-morandi-i-crolli-si-evitano-con-lia-e-manutenzione-predittiva-iot-di-tutte-le-infrastrutture\/233523\/\"><strong>Ponte Morandi, collapses are avoided with AI and IoT predictive maintenance of all infrastructures<\/strong><\/a>\u201d (key4biz, October 3, 2018), \u201c<a href=\"https:\/\/www.itismagazine.it\/news\/16211\/i-sistemi-shm-per-la-manutenzione-e-la-sicurezza-delle-infrastrutture\/#.W9S4MI9PrIU\"><strong>SHM systems for infrastructure maintenance and safety<\/strong><\/a><strong>\u201d <\/strong>(BitMAT ITIS Magazine, 22 October 2018) and \u201c<a href=\"https:\/\/www.corrierecomunicazioni.it\/digital-economy\/infrastrutture-a-prova-di-crollo-iot-e-intelligenza-artificiale-prevedono-i-rischi\/\"><strong>Crash-proof infrastructure, IoT and artificial intelligence \u201cforesee\u201d the risks\u201c <\/strong>(CorCom, 30 November 2018) <\/a><span style=\"font-size: medium;\">And &quot;<\/span><a href=\"https:\/\/www.corrierecomunicazioni.it\/digital-economy\/strade-e-opere-di-ingegneria-civile-la-chiave-di-volta-e-la-manutenzione-predittiva\/\"><span style=\"font-size: medium;\"><b>Roads and civil engineering works, the keystone is predictive maintenance<\/b><\/span><\/a><span style=\"font-size: medium;\">\u201d (CorCom, 18 January 2019)<\/span>.<a href=\"https:\/\/www.corrierecomunicazioni.it\/digital-economy\/infrastrutture-a-prova-di-crollo-iot-e-intelligenza-artificiale-prevedono-i-rischi\/\">.<\/a><\/p>\n\n\n\n<p>They offer some preliminary considerations on a topic of the utmost topicality and relevance (in Italy there are <strong>tens or hundreds of thousands of suspended structures potentially at risk of collapse!<\/strong>), of enormous impact on daily life and the development of our Society, with recommendations to intervene extremely quickly on a national scale. Starting from the existing structures (\u201cbrownfield\u201d), to then apply modern structural prevention design criteria (eg \u201cdigital twin\u201d) and ICT monitoring to new buildings (\u201cgreenfield\u201d).<\/p>\n\n\n\n<p>In order to investigate the issue as a whole (number of structures, costs, times, ...), a <strong>Working group<\/strong> operational on the project &quot;<strong>Infrastructure Monitoring for Predictive Maintenance<\/strong>&quot; (IMPREM), trying to focus on some concrete &quot;use cases&quot; representative of real situations to develop a concrete propositional initiative at a political-institutional level to be extended with full knowledge of the facts to Government decision-makers. As <a href=\"https:\/\/www.statigeneralinnovazione.it\/en\/\">States General of Innovation<\/a> we want to place our specific skills and professionalism in support of the Institutions that deem to take charge of the above, as regards <em>advisory<\/em> and technical support \u2013 including project or sub-project management \u2013 to the implementation of IoT \/ SHM monitoring (<em>internet of things \/ structural health monitoring<\/em>) and related prediction paradigms \/ Artificial Intelligence.<\/p>\n\n\n\n<p>At the moment we have some initial ideas \u2013 partly derived from the contributions mentioned above.<\/p>\n\n\n\n<ol class=\"wp-block-list\"><li>An initial (rather crude) analysis would identify the annual allocation necessary for the &#039;predictive monitoring&#039; of all suspended infrastructures in a fraction of a point of GDP.<\/li><li>Various contributions to the magazine <a href=\"https:\/\/www.ingenio-web.it\/\">genius<\/a> they dealt extensively and with many articles on the collapse of the Morandi bridge starting from 15 August last, hoping for increasingly &quot;resilient&quot; infrastructures.<\/li><li>In this framework, i <a href=\"https:\/\/www.itismagazine.it\/news\/16211\/i-sistemi-shm-per-la-manutenzione-e-la-sicurezza-delle-infrastrutture\/\">modern SHM systems (<em>structural heath monitoring<\/em><\/a>), which allow you to continuously monitor the state of health of the structures and maintenance <em>targeted<\/em>, preventing situations of collapse from occurring.<\/li><li>SHM systems allow you to check the health of the structure, through <em>non-destructive evaluations<\/em>(NDE) of the static or dynamic type, the localization of problems \/ defects, producing the necessary alarms \/ <em>alert <\/em>and indications on the residual life in safety (<em>safe lifetime<\/em>).<\/li><li>SHM requires multidisciplinary collaboration between Civil Engineering and Electronics \/ ICT, accelerating the transition from <em>culture of<\/em> <em>project<\/em> to that of the <em>maintenance and management<strong>. <\/strong><\/em>It is not (only) a matter of positioning sensors \/ actuators and collecting \/ processing data, but of using the guidelines for structural monitoring (see UNI\/TR 11634:2016 standard) also during the construction phase, e.g. with simulation techniques <em>building information modeling<\/em> (BIM).<\/li><li>A SHM system can monitor one or more structures, using both satellite observations in low orbit (for static type monitoring) and aerial observations (helicopters or drones) and from ground devices - which allow both static and dynamic monitoring, using sensors and very low consumption technologies (eg <a href=\"https:\/\/lora-alliance.org\/\">Time<\/a>) connected via <em>wireless sensor network<\/em> (WSN) and the like.<\/li><li>Thanks to the wide availability of data collected in this way, it would be relatively easy to create one <em>maintenance<\/em> <em>predictive<\/em> (&#039;on condition&#039;), using the continued progress in (<em>big)<\/em> <em>data mining \/ machine learning, <\/em>with massive use of Artificial Intelligence (AI) to derive estimates on possible behaviors and measures to be taken in good time.<\/li><\/ol>\n\n\n\n<p>In summary, for the safety of the road network in operation, it would first of all be necessary to promulgate - in an extremely short time<strong> \u2013 binding framework rules to equate infrastructural prevention with the safety obligations established by current legislation. At the same time, activate an infrastructure mapping<\/strong> (See example of <a href=\"https:\/\/www.sinfi.it\/portal\/\">SINFI<\/a>)<strong>, building a computerized register of civil works (eg. <em>blockchain-based<\/em>) which identifies its age, structural parameters, state of &quot;health&quot;, history of maintenance interventions, ... capable of constituting a<\/strong>cadastre&#039; organized by classes of potential risks and relative priorities of the maintenance interventions to be implemented, with <strong>contextual installation of adequate SHM sensors<\/strong>.<\/p>\n\n\n\n<p>With regard to the civil works to be carried out (&quot;greenfield&quot;), impose the application of the aforementioned framework standards <strong>of infrastructural prevention, and the related modern techniques of structural design <\/strong>to the geological, environmental, logistic, ... characteristics of the reference territory, with extensive use of ICT and &quot;digital twin&quot; methodologies \/ Enterprise 4.0 (<em>industrial internet of things<\/em>, IIoT), very low latency communications (5G), AI algorithms and models for predicting risk events, etc.<\/p>\n\n\n\n<p>Last but not least, a precise and constant <strong>information to citizens<\/strong> on the potential risks in the transitional period of making the entire national road network safe, which - far from creating panic situations - puts the population in a position to be able to implement all the precautions and the most appropriate route choices for the respective needs of safe travel .<\/p>\n\n\n\n<p><strong>\u00ab<\/strong><strong>It is necessary to know in order to be able to decide<\/strong>\u00bb (L. Einaudi)<\/p>","protected":false},"excerpt":{"rendered":"<p>Segnaliamo i contributi \u201cPonte Morandi, i crolli si evitano con l\u2019IA e manutenzione predittiva IoT di tutte le infrastrutture\u201d (key4biz, 3 ottobre 2018), \u201cI Sistemi SHM per la manutenzione e la sicurezza delle infrastrutture\u201d (BitMAT [&hellip;]<\/p>\n","protected":false},"author":2987,"featured_media":9957,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[30],"tags":[702,711],"class_list":["post-9953","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-opinioni","tag-blockchain","tag-machine-learning"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.1 (Yoast SEO v27.4) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Infrastructure Monitoring for Predictive Maintenance - aggiornamento del 18\/01\/2019 - Stati Generali dell&#039;Innovazione<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.statigeneralinnovazione.it\/en\/infrastructure-monitoring-for-predictive-maintenance\/\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.statigeneralinnovazione.it\\\/infrastructure-monitoring-for-predictive-maintenance\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.statigeneralinnovazione.it\\\/infrastructure-monitoring-for-predictive-maintenance\\\/\"},\"author\":{\"name\":\"Fulvio Ananasso\",\"@id\":\"https:\\\/\\\/www.statigeneralinnovazione.it\\\/#\\\/schema\\\/person\\\/9e28a50f1749afb3ee2dad5fb2bad504\"},\"headline\":\"Infrastructure Monitoring for Predictive Maintenance &#8211; 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