{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T16:17:24Z","timestamp":1761581844973,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T00:00:00Z","timestamp":1560902400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>We report on a self-sustainable, wireless accelerometer-based system for wear detection in a band saw blade. Due to the combination of low power hardware design, thermal energy harvesting with a small thermoelectric generator (TEG), an ultra-low power wake-up radio, power management and the low complexity algorithm implemented, our solution works perpetually while also achieving high accuracy. The onboard algorithm processes sensor data, extracts features, performs the classification needed for the blade\u2019s wear detection, and sends the report wirelessly. Experimental results in a real-world deployment scenario demonstrate that its accuracy is comparable to state-of-the-art algorithms executed on a PC and show the energy-neutrality of the solution using a small thermoelectric generator to harvest energy. The impact of various low-power techniques implemented on the node is analyzed, highlighting the benefits of onboard processing, the nano-power wake-up radio, and the combination of harvesting and low power design. Finally, accurate in-field energy intake measurements, coupled with simulations, demonstrate that the proposed approach is energy autonomous and can work perpetually.<\/jats:p>","DOI":"10.3390\/s19122747","type":"journal-article","created":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T10:43:32Z","timestamp":1560941012000},"page":"2747","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["SmarTEG: An Autonomous Wireless Sensor Node for High Accuracy Accelerometer-Based Monitoring"],"prefix":"10.3390","volume":"19","author":[{"given":"Michele","family":"Magno","sequence":"first","affiliation":[{"name":"Integrated Systems Laboratory, ETH Zurich, 8092 Zurich, Switzerland"},{"name":"DEI, University of Bologna, 40126 Bologna, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4983-8889","authenticated-orcid":false,"given":"Lukas","family":"Sigrist","sequence":"additional","affiliation":[{"name":"Integrated Systems Laboratory, ETH Zurich, 8092 Zurich, Switzerland"}]},{"given":"Andres","family":"Gomez","sequence":"additional","affiliation":[{"name":"Integrated Systems Laboratory, ETH Zurich, 8092 Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1767-7715","authenticated-orcid":false,"given":"Lukas","family":"Cavigelli","sequence":"additional","affiliation":[{"name":"Integrated Systems Laboratory, ETH Zurich, 8092 Zurich, Switzerland"}]},{"given":"Antonio","family":"Libri","sequence":"additional","affiliation":[{"name":"Integrated Systems Laboratory, ETH Zurich, 8092 Zurich, Switzerland"}]},{"given":"Emanuel","family":"Popovici","sequence":"additional","affiliation":[{"name":"School of Engineering, University College Cork, T12 K8AF Cork, Ireland"}]},{"given":"Luca","family":"Benini","sequence":"additional","affiliation":[{"name":"Integrated Systems Laboratory, ETH Zurich, 8092 Zurich, Switzerland"},{"name":"DEI, University of Bologna, 40126 Bologna, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"924","DOI":"10.1109\/TIA.2006.876065","article-title":"A survey of efficiency-estimation methods for in-service induction motors","volume":"42","author":"Lu","year":"2006","journal-title":"IEEE Trans. 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