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Despite efforts to improve safety, statistics show a plateau in the reduction of these accidents in recent years. To decrease the number of accidents, compliance with established industrial safety standards and regulations by competent authorities must be ensured, including the use of Personal Protective Equipment (PPE). PPE usage is of paramount importance, as it is essential to prevent accidents from occurring. This work aims to improve worker safety by verifying PPE usage. Technology plays a key role here. A cost-effective solution is proposed to monitor PPE usage in real time. Most existing safety control systems are costly and require considerable maintenance. A low-cost computer vision system is proposed to supervise safety in industrial facilities. This system uses object detection and tracking technology in low-cost embedded devices and can generate alarms in real time if PPE is not used. Unlike other works, temporal information is used to generate the alarms. Safety managers receive this information to take necessary actions. Emphasis has been placed on cost, scalability, and ease of use to facilitate system implementation in industrial plants. The result is an effective system that improves worker safety by verifying established safety measures at a reduced cost. The methodology used improves the Average Precision of PPE detection by 6%. In addition, unlike other studies, the problem of application deployment is addressed, which has an impact on its cost.<\/jats:p>","DOI":"10.1007\/s11554-023-01368-7","type":"journal-article","created":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T16:02:18Z","timestamp":1696867338000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Low-cost system for real-time verification of personal protective equipment in industrial facilities using edge computing devices"],"prefix":"10.1007","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0981-7925","authenticated-orcid":false,"given":"Dar\u00edo G.","family":"Lema","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0551-3203","authenticated-orcid":false,"given":"Rub\u00e9n","family":"Usamentiaga","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8499-9744","authenticated-orcid":false,"given":"Daniel F.","family":"Garc\u00eda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,10,9]]},"reference":[{"key":"1368_CR1","unstructured":"Eurostat, \u201cAccidents at work statistics,\u201d accessed on 29 Jun 2022. 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All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}],"article-number":"111"}}