{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T11:57:47Z","timestamp":1770983867677,"version":"3.50.1"},"reference-count":113,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T00:00:00Z","timestamp":1681948800000},"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>This paper proposes the use of the AHP-Gaussian method to support the selection of a smart sensor installation for an electric motor used in an escalator in a subway station. The AHP-Gaussian methodology utilizes the Analytic Hierarchy Process (AHP) framework and is highlighted for its ability to save the decision maker\u2019s cognitive effort in assigning weights to criteria. Seven criteria were defined for the sensor selection: temperature range, vibration range, weight, communication distance, maximum electric power, data traffic speed, and acquisition cost. Four smart sensors were considered as alternatives. The results of the analysis showed that the most appropriate sensor was the ABB Ability smart sensor, which scored the highest in the AHP-Gaussian analysis. In addition, this sensor could detect any abnormalities in the equipment\u2019s operation, enabling timely maintenance and preventing potential failures. The proposed AHP-Gaussian method proved to be an effective approach for selecting a smart sensor for an electric motor used in an escalator in a subway station. The selected sensor was reliable, accurate, and cost-effective, contributing to the safe and efficient operation of the equipment.<\/jats:p>","DOI":"10.3390\/s23084131","type":"journal-article","created":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T02:05:31Z","timestamp":1682042731000},"page":"4131","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":54,"title":["Evaluation of Smart Sensors for Subway Electric Motor Escalators through AHP-Gaussian Method"],"prefix":"10.3390","volume":"23","author":[{"given":"Ruan Carlos Alves","family":"Pereira","sequence":"first","affiliation":[{"name":"Military Engineering Institute\u2014IME, Rio de Janeiro 22290-270, Brazil"}]},{"suffix":"Jr.","given":"Orivalde Soares","family":"da Silva","sequence":"additional","affiliation":[{"name":"Military Engineering Institute\u2014IME, Rio de Janeiro 22290-270, Brazil"}]},{"given":"Renata Albergaria","family":"de Mello Bandeira","sequence":"additional","affiliation":[{"name":"Military Engineering Institute\u2014IME, Rio de Janeiro 22290-270, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1533-5535","authenticated-orcid":false,"given":"Marcos","family":"dos Santos","sequence":"additional","affiliation":[{"name":"Department of Production Engineering, Faculty of Engineering, Praia Vermelha Campus, Federal Fluminense University, Niteroi 22040-036, Brazil"}]},{"suffix":"Jr.","given":"Claudio","family":"de Souza Rocha","sequence":"additional","affiliation":[{"name":"Department of Production Engineering, Faculty of Engineering, Praia Vermelha Campus, Federal Fluminense University, Niteroi 22040-036, Brazil"}]},{"given":"Cristian dos Santos","family":"Castillo","sequence":"additional","affiliation":[{"name":"Department of Production Engineering, Faculty of Engineering, Praia Vermelha Campus, Federal Fluminense University, Niteroi 22040-036, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6865-0275","authenticated-orcid":false,"given":"Carlos Francisco Sim\u00f5es","family":"Gomes","sequence":"additional","affiliation":[{"name":"Department of Production Engineering, Faculty of Engineering, Praia Vermelha Campus, Federal Fluminense University, Niteroi 22040-036, Brazil"}]},{"given":"Daniel Augusto","family":"de Moura Pereira","sequence":"additional","affiliation":[{"name":"Production Engineering Department, Federal University of Campina Grande (UFCG), Campina Grande 58428-830, Brazil"}]},{"given":"Fernando Martins","family":"Muradas","sequence":"additional","affiliation":[{"name":"Operational Research Department, Naval Systems Analysis Center (CASNAV), Rio de Janeiro 20091-000, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"02010","DOI":"10.1051\/matecconf\/201820302010","article-title":"Industry revolution IR 4.0: Future opportunities and challenges in Construction Industry","volume":"203","author":"Alaloul","year":"2018","journal-title":"MATEC Web Conf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1087","DOI":"10.1088\/0022-3735\/20\/9\/003","article-title":"Smart sensors in industry","volume":"20","author":"Favennec","year":"1987","journal-title":"J. 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