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dc.contributor.author | Ramos-Sorroche, Emilio | es_ES |
dc.contributor.author | Rubio-Aparicio, Jesus | es_ES |
dc.contributor.author | Santa, Jose | es_ES |
dc.contributor.author | Guardiola, Carlos | es_ES |
dc.contributor.author | Egea-Lopez, Esteban | es_ES |
dc.date.accessioned | 2024-12-17T19:02:29Z | |
dc.date.available | 2024-12-17T19:02:29Z | |
dc.date.issued | 2024-04 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/213009 | |
dc.description.abstract | [EN] Accurate environmental monitoring is becoming the basis for assuring sustainable development in administrations at different levels, including cities and industry as key actors. However, current techniques rely on static stations that may not be representative of larger areas, for the case of outdoor scenarios, or even not considering indoor spaces where people can remain for long periods. This is the case of vehicles. The COVID-19 pandemic has remarked the importance of measuring air quality indoors, for instance. With the aim of solving this twofold issue, this work proposes an in-cabin and outdoor air pollution monitoring system to assure healthy conditions when travelling, driving and operating vehicles, and to analyse the evolution of environmental parameters in cities. This effort is carried out exploiting distributed computing with micro-services, betting for an on-board hardware solution provided with sensors for measuring particulate matter, CO, CO2, NO2, O3, temperature and humidity. While basic data pre-processing is carried out in this acquisition unit, edge processing is performed on a single board computer aboard and intermediary communication nodes in the network path from the vehicle to the cloud. Vehicle connectivity is provided by 4G cellular and Low-Power Wide Area (LPWAN) networks. Global environmental perception is acquired by cloud-based software powered by machine learning and time series analysis. The whole solution has been validated and tested in the city of Cartagena (Spain), with good performance in terms of data collection, communication links and service offered. | es_ES |
dc.description.sponsorship | This work was supported by the grants PID2020-112675RBC41 (ONOFRE-3) , funded by MCIN/AEI/10.13039/501100011033; RYC-2017-23823, funded by MCIN/AEI/10.13039/501100011033 and by "ESF Investing in your future"; CNS2022-136150 (WILLIOT) , funded by MCIN/AEI/10.13039/501100011033 and by "European Union NextGenerationEU/PRTR"; and H2020 957258 (ASSIST-IoT) , funded by the European Commission. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Internet of Things | es_ES |
dc.rights | Reconocimiento - No comercial (by-nc) | es_ES |
dc.subject | Environmental monitoring | es_ES |
dc.subject | IoT | es_ES |
dc.subject | Smart cities | es_ES |
dc.subject | Intelligent transportation systems | es_ES |
dc.subject | Crowdsensing | es_ES |
dc.subject | Edge computing | es_ES |
dc.subject.classification | MAQUINAS Y MOTORES TERMICOS | es_ES |
dc.title | In-cabin and outdoor environmental monitoring in vehicular scenarios with distributed computing | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.iot.2023.101009 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-112675RB-C41/ES/ADAPTACION DE RECURSOS DE COMPUTO Y RED DESDE LA NUBE AL EXTREMO: PLANIFICACION Y ACCESO COORDINADO OPTIMO (ONOFRE-3-UPCT)/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/957258/EU/Architecture for Scalable, Self-*, human-centric, Intelligent, Secure, and Tactile next generation IoT/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI//RYC-2017-23823/ES/Vehicular Telematics for Next-Generation Moving Smart Spaces | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//CNS2022-136150/ES/INTERNET DE LAS COSAS MOVILES CON TECNOLOGIAS INALAMBRICAS DE NUEVA GENERACION | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials | es_ES |
dc.description.bibliographicCitation | Ramos-Sorroche, E.; Rubio-Aparicio, J.; Santa, J.; Guardiola, C.; Egea-Lopez, E. (2024). In-cabin and outdoor environmental monitoring in vehicular scenarios with distributed computing. Internet of Things. 25. https://doi.org/10.1016/j.iot.2023.101009 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.iot.2023.101009 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 25 | es_ES |
dc.identifier.eissn | 2542-6605 | es_ES |
dc.relation.pasarela | S\508727 | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Ministerio de Ciencia e Innovación | es_ES |