{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T06:12:01Z","timestamp":1776319921822,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ASI"],"abstract":"<jats:p>This paper addresses the design of a system to facilitate individual environmental risk assessment and long-term risk management in the Industry 4.0 work context. The solution is based on IoT to provide data related to workers\u2019 exposure to hazardous agents (dust, noise, ultraviolet radiation, poor lighting, and inappropriate temperature and humidity) through a simple interface for employees and employers. The system includes a monitoring device and a server and performs employee registration, receives secure messages from the monitoring devices, shows information about the workers\u2019 exposure, and triggers alarms when the measures reach or exceed the limits established by applicable legislation and\/or standards. The system was tested in a controlled environment, and the results are presented in this work. Our solution is still under development, and in future stages, it will include a smartphone app for employees to check their exposures and the use of artificial intelligence on the server, which is expected to enable long-term planning by companies based on the analysis of employees\u2019 health history and their exposures to hazardous agents.<\/jats:p>","DOI":"10.3390\/asi5050088","type":"journal-article","created":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T21:27:17Z","timestamp":1662067637000},"page":"88","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Individual Environmental Risk Assessment and Management in Industry 4.0: An IoT-Based Model"],"prefix":"10.3390","volume":"5","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"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1691-1709","authenticated-orcid":false,"given":"Pedro D.","family":"Gaspar","sequence":"additional","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"},{"name":"C-MAST-Centre for Mechanical and Aerospace Science and Technologies, 6201-001 Covilh\u00e3, Portugal"}]},{"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-Centre for Mechanical and Aerospace Science and Technologies, 6201-001 Covilh\u00e3, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e032528","DOI":"10.1136\/bmjopen-2019-032528","article-title":"Evidence-based occupational health and safety interventions: A comprehensive overview of reviews","volume":"9","author":"Teufer","year":"2019","journal-title":"BMJ Open"},{"key":"ref_2","unstructured":"(2022, July 15). 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