{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,4]],"date-time":"2024-08-04T13:58:06Z","timestamp":1722779886704},"reference-count":13,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2014,12,30]],"date-time":"2014-12-30T00:00:00Z","timestamp":1419897600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"name":"German BMBF","award":["16SV3604"],"award-info":[{"award-number":["16SV3604"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Advances in Artificial Neural Systems"],"published-print":{"date-parts":[[2014,12,30]]},"abstract":"<jats:p>The surging advance in micro- and nanotechnologies allied with neural learning systems allows the realization of miniaturized yet extremely powerful multisensor systems and networks for wide application fields, for example, in measurement, instrumentation, automation, and smart environments. Time and location context is particularly relevant to sensor swarms applied for distributed measurement in industrial environment, such as, for example, fermentation tanks. Common RF solutions face limits here, which can be overcome by magnetic systems. Previously, we have developed the electronic system for an integrated data logger swarm with magnetic localization and sensor node timebase synchronization. The focus of this work is on an approach to improving both localization accuracy and flexibility by the application of artificial neural networks applied as virtual sensors and classifiers in a hybrid dedicated learning system. Including also data from an industrial brewery environment, the best investigated neural virtual sensor approach has achieved an advance in localization accuracy of a factor of 4 compared to state-of-the-art numerical methods and, thus, results in the order of less than 5\u2009cm meeting industrial expectations on a feasible solution for the presented integrated localization system solution.<\/jats:p>","DOI":"10.1155\/2014\/394038","type":"journal-article","created":{"date-parts":[[2014,12,30]],"date-time":"2014-12-30T21:02:52Z","timestamp":1419973372000},"page":"1-17","source":"Crossref","is-referenced-by-count":2,"title":["Neural Virtual Sensors for Adaptive Magnetic Localization of Autonomous Dataloggers"],"prefix":"10.1155","volume":"2014","author":[{"given":"Dennis","family":"Groben","sequence":"first","affiliation":[{"name":"Institute of Integrated Sensor Systems, EIT, TU Kaiserslautern, Erwin-Schr\u00f6dinger-Stra\u00dfe 12, 67663 Kaiserslautern, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kittikhun","family":"Thongpull","sequence":"additional","affiliation":[{"name":"Institute of Integrated Sensor Systems, EIT, TU Kaiserslautern, Erwin-Schr\u00f6dinger-Stra\u00dfe 12, 67663 Kaiserslautern, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abhaya Chandra","family":"Kammara","sequence":"additional","affiliation":[{"name":"Institute of Integrated Sensor Systems, EIT, TU Kaiserslautern, Erwin-Schr\u00f6dinger-Stra\u00dfe 12, 67663 Kaiserslautern, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"K\u00f6nig","sequence":"additional","affiliation":[{"name":"Institute of Integrated Sensor Systems, EIT, TU Kaiserslautern, Erwin-Schr\u00f6dinger-Stra\u00dfe 12, 67663 Kaiserslautern, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"98","reference":[{"key":"20","year":"2013"},{"key":"28","doi-asserted-by":"publisher","DOI":"10.1017\/S1759078709000245"},{"key":"29","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.proeng.2010.09.087","volume":"5","year":"2010","journal-title":"Procedia Engineering"},{"key":"31","volume":"29","year":"2009","journal-title":"e-Newsletter IEEE SMC Society"},{"key":"32","doi-asserted-by":"publisher","DOI":"10.1109\/72.846733"},{"key":"33","series-title":"Advances in Intelligent Systems and Computing","first-page":"149","volume-title":"Advanced methods for 3D magnetic localization in industrial process distributed data-logging with a sparse distance matrix","volume":"223","year":"2014"},{"key":"36","doi-asserted-by":"publisher","DOI":"10.1109\/35.46683"},{"key":"37","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1007\/978-3-642-23863-5_34","volume-title":"Hybrid virtual sensor based on RBFN or SVR compared for an embedded application","volume":"6882","year":"2011"},{"key":"39","series-title":"edited by S. 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