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dc.contributor.authorMárquez Sánchez, Sergio
dc.contributor.authorHuerta Muñoz, Jorge
dc.contributor.authorHerrera Santos, Jorge
dc.contributor.authorGonzález Arrieta, María Angélica 
dc.contributor.authorPrieta Pintado, Fernando de la 
dc.date.accessioned2024-01-29T09:01:54Z
dc.date.available2024-01-29T09:01:54Z
dc.date.issued2023-09-01
dc.identifier.issn1570-8705
dc.identifier.urihttp://hdl.handle.net/10366/154830
dc.description.abstract[EN]The detection and measurement of gas levels have become very important in both domestic and industrial fields. This is a result of the realization that certain gases are toxic and may have a harmful or even lethal effect on humans (and/or the environment), depending on exposure time or concentration. For this reason, gas sensors play a crucial role, especially in industries, where they help to prevent risks by detecting and measuring the presence of harmful gases in the workers’ environment. There is a wide variety of sensors and techniques used to detect gases and determine their characteristics. The case study presented in this paper analyzes the presence of gases in a train hangar. Using a range of low-cost sensors, it is possible to measure the concentration of different gases over time and identify the moments where these concentrations are higher. In this study, it has been determined that these periods are usually related to moments when maintenance works are taking place in the hangar and their relationship with the measurements of a high-accuracy CO2 sensor. Detecting and predicting when these events take place allows to alert employees in case gas levels are considered dangerous for human health, or to take different actions to counteract this threat. An analysis of how to improve the energetic efficiency of the hangar is also carried out, estimating the losses caused by an inefficient ventilation system. Finally, some ideas are given to help improve the well-being of the workers, and also reduce energy costs.es_ES
dc.language.isoenges_ES
dc.rightsAtribución-NoComercial-CompartirIgual 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectGas measurementes_ES
dc.subjectSensing in industryes_ES
dc.subjectRisk preventiones_ES
dc.subjectAmbient intelligentes_ES
dc.titleGas sensing in industry. A case study: Train hangares_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publishversionhttps://www.sciencedirect.com/science/article/pii/S1570870523001257es_ES
dc.identifier.doi10.1016/j.adhoc.2023.103205
dc.relation.projectIDPID2021-123673OB-C33es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleAd Hoc Networkses_ES
dc.volume.number148es_ES
dc.page.initial103205es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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