{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T23:32:35Z","timestamp":1774481555346,"version":"3.50.1"},"reference-count":74,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia (FCT) and C-MAST (Centre for Mechanical and Aerospace Science and Technologies)","doi-asserted-by":"publisher","award":["UIDB\/00151\/2020"],"award-info":[{"award-number":["UIDB\/00151\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>This paper describes an integrated monitoring system designed for individualized environmental risk assessment and management in the workplace. The system incorporates monitoring devices that measure dust, noise, ultraviolet radiation, illuminance, temperature, humidity, and flammable gases. Comprising monitoring devices, a server-based web application for employers, and a mobile application for workers, the system integrates the registration of workers\u2019 health histories, such as common diseases and symptoms related to the monitored agents, and a web-based recommendation system. The recommendation system application uses classifiers to decide the risk\/no risk per sensor and crosses this information with fixed rules to define recommendations. The system generates actionable alerts for companies to improve decision-making regarding professional activities and long-term safety planning by analyzing health information through fixed rules and exposure data through machine learning algorithms. As the system must handle sensitive data, data privacy is addressed in communication and data storage. The study provides test results that evaluate the performance of different machine learning models in building an effective recommendation system. Since it was not possible to find public datasets with all the sensor data needed to train artificial intelligence models, it was necessary to build a data generator for this work. By proposing an approach that focuses on individualized environmental risk assessment and management, considering workers\u2019 health histories, this work is expected to contribute to enhancing occupational safety through computational technologies in the Industry 5.0 approach.<\/jats:p>","DOI":"10.3390\/computers13050120","type":"journal-article","created":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T03:34:01Z","timestamp":1715571241000},"page":"120","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Enhancing Workplace Safety through Personalized Environmental Risk Assessment: An AI-Driven Approach in Industry 5.0"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1105-1260","authenticated-orcid":false,"given":"Jana\u00edna","family":"Lemos","sequence":"first","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"}]},{"given":"Vanessa Borba","family":"de Souza","sequence":"additional","affiliation":[{"name":"Postgraduate Program in Computing, Federal University of Rio Grande do Sul, Av. Bento Gon\u00e7alves, 9500, Porto Alegre 91501-970, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6457-4164","authenticated-orcid":false,"given":"Frederico Soares","family":"Falcetta","sequence":"additional","affiliation":[{"name":"Laboratory Diagnostic Service, HCPA Hospital, R. Ramiro Barcelos, 2350, Porto Alegre 90035-903, Brazil"}]},{"given":"Fernando Kude","family":"de Almeida","sequence":"additional","affiliation":[{"name":"Oncology Division, F\u00eamina Hospital, R. Mostardeiro, 17, Porto Alegre 90430-001, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7540-3854","authenticated-orcid":false,"given":"T\u00e2nia M.","family":"Lima","sequence":"additional","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"},{"name":"C-MAST\u2014Centre for Mechanical and Aerospace Science and Technologies, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1691-1709","authenticated-orcid":false,"given":"Pedro Dinis","family":"Gaspar","sequence":"additional","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"},{"name":"C-MAST\u2014Centre for Mechanical and Aerospace Science and Technologies, 6201-001 Covilh\u00e3, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"ref_1","unstructured":"(2023, October 28). WHO. 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