{"id":10412,"date":"2022-10-20T11:59:49","date_gmt":"2022-10-20T09:59:49","guid":{"rendered":"https:\/\/www.ims-chips.com\/?p=10412"},"modified":"2025-07-10T10:35:58","modified_gmt":"2025-07-10T08:35:58","slug":"dorie-ai","status":"publish","type":"post","link":"https:\/\/www.ims-chips.com\/?p=10412","title":{"rendered":"DoRiE – AI for sensor-related applications in industrial use"},"content":{"rendered":"\t\t
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Newsletter 2\/2022<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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DoRiE - AI for sensor-related applications<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Proprietary AI chip makes sensors \u201csmart\u201d<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Nowadays, sensors are used in all areas\nof technical equipment. They constantly\nprovide data on temperatures, pressure,\ncurrent and voltage curves, etc., which must\nbe reliably and continuously transmitted to\ncentral control units in order to determine\noperating conditions based on sensor data.\nToday, modern machines are equipped\nwith a large number of sensors, which entail\na corresponding amount of effort in terms\nof cabling and data transmission. A central\ncontrol unit then provides a picture of the\ncurrent operating status. A classic sensor\nonly determines the measured value of a\nphysical variable, but does not draw any\nconclusions from it. Using artificial intelligence\n(AI) methods, it is in principle possible\nto evaluate and classify sensor data.\nIdeally, this evaluation is carried out at the\nsensor and not in a control unit the sensor\ntransmits the raw data to. An intelligent\nsensor can, on the one hand, check itself\nand, on the other hand, evaluate the data it\nmeasures. This way, instead of continuously\ntransmitting temperature values, the AI\nsensor can transmit individually evaluated\ndata: \u201cTemperature is within the permissible\nrange\u201d and the amount of data to be\ntransmitted can be drastically reduced,\nwhich greatly reduces the necessary bandwidth\nin communication and simplifies the\nevaluation, especially in applications with\nmany sensors. <\/p>\n\n

The research partners involved in the\nDoRiE project have laid the foundations\nfor their own AI chips over the past two\nyears in the successfully completed Baden-\nW\u00fcrttemberg-funded NeMoH project and\nare now implementing them in industrial\nreference applications. <\/p>\n\n

An exciting application is the ongoing\nself-diagnosis of solenoid valves, in which\nthe AI sensor simply observes the current\ncurve of the valve during the switching\nprocess. Based on the typical course of the\ncurrent curve, the condition of the valve\ncan be determined with a high hit rate. This\ndetermines whether the valve is operating\nwithin normal boundaries, whether the\nmedium is too hot, or whether the pressure\nof the medium is either too high or too\nlow. Also, malfunctions, such as\nforeign bodies in the valve (grain of\nsand, incrustations) can be detected:\n\u201cvalve does not fully open\u201d or\n\u201cvalve does not fully close\u201d. Even\nthe valve component temperature\ncan be ascertained from the current\ncurve. Equipped with the AI\nsensor, a component, such as a\nsolenoid valve, can determine, its\nown operating status, and signal it\nto the outside. <\/p>\n\n

In order to use this capability, numerous\nsystem data must be collected and classified\nin advance. To do this, extensive\nmeasurements with artificially induced fault\nconditions must be carried out on reference\ncomponents in advance. In order to collect\nthis data on the condition, the research\npartners have developed appropriate test\nrigs to automatically generate thousands\nof data sets. These data are used to train\nan artificial neuronal network. Which is\nthen fed with actual measured values in the\nAI sensor application. The neural network\nnow classifies the measured values into\npredefined condition categories. <\/p>\n\n

For another demonstration of AI sensors,\nthe research partners are currently developing\na robotics application in which a\nrobotic arm uses radar sensors (like those\nused to measure distance in distance\ncruise control systems) to orient itself in its\nenvironment and can be controlled by a\nhuman using hand gestures. The radar sensors\ngenerate very large amounts of data\nduring operation, illustrating distances to\nand movements of objects. Again, neural\nnetworks are trained on different condition\ncategories to be evaluated by an AI system\nclose to the sensor in the application.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Robotic arm with sensor-based AI enables gesture control, object recognition<\/em>
and grabbing objects by sensing them<\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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The project is accompanied by an industry\nadvisory board consisting of the Balluff,\nNEXT.robotics, Pilz, Schunk, Staiger and\nSwoboda companies, which helps define\nsystem requirements and monitors the\nimplementation of the applications. In addition,\nthe project offers a free opportunity\nfor companies from Baden-W\u00fcrttemberg to\ncheck their own applications or ideas for\npossible AI sensor potential at any time. For\nthis purpose, interested parties can apply\nfor a QuickCheck for a feasibility study or\nan Exploring Project for a more in-depth\ninvestigation: ki.ims-chips.de<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\tContact:\nThomas Deuble<\/strong>
\nPhone: +49 711 21855\u00a0 244
\nE-Mail deuble@ims-chips.de<\/a>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Companies from Baden-W\u00fcrttemberg as well as the IMS CHIPS, FZI and Hahn-
\nSchickard research facilities are jointly developing reference applications that
\ndemonstrate the sensor-related use of artificial intelligence. The Ministry of
\nEconomics in Baden-W\u00fcrttemberg is supporting DoRiE with 2 million euros.<\/p>\n","protected":false},"author":1,"featured_media":10442,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[34],"tags":[21,20],"class_list":["post-10412","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-projekte-archiv-2023","tag-ai","tag-dorie"],"yoast_head":"\nDoRiE - AI for sensor-related applications in industrial use - Institut f\u00fcr Mikroelektronik Stuttgart<\/title>\n<meta name=\"description\" content=\"Companies from Baden-W\u00fcrttemberg as well as the IMS CHIPS, FZI and Hahn-Schickard research facilities are jointly developing reference applications thatdemonstrate the sensor-related use of artificial intelligence.\" \/>\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.ims-chips.com\/?p=10412\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"DoRiE - 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