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[EN] Transitioning toward Industry 4.0 requires major investment in devices and mechanisms enabling interconnectivity between people, machines, and processes. In this article, we present a low-cost system based on the Raspberry Pi platform to measure the overall equipment effectiveness (OEE) in real time, and we propose two filtering mechanisms for electromagnetic interferences (EMIs) to measure OEE accurately. The first EMI filtering mechanism is the database filter (DBF), which has been designed to record sealing signals accurately. The DBF works on the database by filtering erroneous signals that have been inserted in it. The second mechanism is the smart coded filter (SCF), which is used to filter erroneous signals associated with machine availability measurements. We have validated our proposal in several production lines in a food industry. The results show that our system works properly, and that it considerably reduces implementation costs compared with proprietary systems offering similar functions. After implementing the proposed system in actual industrial settings, the results show a mean error (ME) of -0.43% and a root mean square error (RMSE) of 4.85 in the sealing signals, and an error of 0% in the availability signal, thus enabling an accurate estimate of OEE. ; This work was supported in part by the Government of Aragon and the European Social Fund "Construyendo Europa desde Aragon" under Grant T40_20D Research Group, and in part by the "Ministerio de Ciencia, Innovacion y Universidades, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2018," Spain, under Grant RTI2018-096384-B-I00. ; Herrero, ÁC.; Sangüesa, JA.; Martínez, FJ.; Garrido, P.; Tavares De Araujo Cesariny Calafate, CM. (2021). Mitigating Electromagnetic Noise When Using Low-Cost Devices in Industry 4.0. IEEE Access. 9:63267-63282. https://doi.org/10.1109/ACCESS.2021.3074588 ; S ; 63267 ; 63282 ; 9

© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. ; Road traffic is experiencing a drastic increase, and vehicular traffic congestion is becoming a major problem, especially in metropolitan environments throughout the world. Additionally, in modern Intelligent Transportation Systems (ITS) communications, the high amount of information that can be generated and processed by vehicles will significantly increase message redundancy, channel contention, and message collisions, thus reducing the efficiency of message dissemination processes. In this work, we present a V2X architecture to estimate traffic density on the road that relies on the advantages of combining V2V and V2I communications. Our proposal uses both the number of beacons received per vehicle (V2V) and per RSU (V2I), as well as the roadmap topology features to estimate the vehicle density. By using our approach, modern Intelligent Transportation Systems will be able to reduce traffic congestion and also to adopt more efficient message dissemination protocols. ; This work was partially supported by the Ministerio de Ciencia e Innovación, Spain, under Grant TIN2011-27543-C03-01, by the Fundación Universitaria Antonio Gargallo and the Obra Social de Ibercaja, under Grant 2013/B010, as well as the Government of Aragón and the European Social Fund (T91 Research Group). ; Barrachina Villalba, J.; Sangüesa, JA.; Fogue, M.; Garrido, P.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM. (2013). V2X-d: a Vehicular Density Estimation System that combines V2V and V2I Communications. IEEE. https://doi.org/10.1109/WD.2013.6686518 ; S