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Article

Smart Maintenance Solutions: AR- and VR-Enhanced Digital Twin Powered by FIWARE

1
IPVC—Instituto Politécnico de Viana do Castelo, 4900-347 Viana do Castelo, Portugal
2
RIOPELE, 4770-405 Vila Nova de Famalicão, Portugal
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(3), 845; https://doi.org/10.3390/s25030845
Submission received: 15 December 2024 / Revised: 9 January 2025 / Accepted: 27 January 2025 / Published: 30 January 2025
(This article belongs to the Section Internet of Things)

Abstract

In the modern era of industrial digitalization, the convergence of the Internet of Things (IoT), advanced data analysis, augmented reality (AR) and virtual reality (VR) is significantly transforming various industrial sectors. This research aimed to study and develop a proposal for an integrated system that combines IoT, data analysis, AR and VR for the monitoring and maintenance of industrial equipment. The importance of this research lies in its potential to contribute to the implementation of predictive maintenance solutions, which can significantly reduce machine downtime in an industrial environment and thus reduce or prevent operational failures. The central research question of this work was the following: how can the integration of IoT, data analysis and augmented and virtual reality contribute to optimizing industrial maintenance? We tested the combination of technologies to enable the creation of an effective predictive maintenance system, capable of alerting operators to anomalous conditions and providing detailed visual instructions for maintenance tasks. As a result, a prototype system was developed and tested, and it has shown the potential to evolve into a real system in an industrial environment.
Keywords: internet of things; data analysis; augmented reality; virtual reality; predictive maintenance; industrial digitization; system integration; operational efficiency internet of things; data analysis; augmented reality; virtual reality; predictive maintenance; industrial digitization; system integration; operational efficiency

Share and Cite

MDPI and ACS Style

Costa, A.; Miranda, J.; Dias, D.; Dinis, N.; Romero, L.; Faria, P.M. Smart Maintenance Solutions: AR- and VR-Enhanced Digital Twin Powered by FIWARE. Sensors 2025, 25, 845. https://doi.org/10.3390/s25030845

AMA Style

Costa A, Miranda J, Dias D, Dinis N, Romero L, Faria PM. Smart Maintenance Solutions: AR- and VR-Enhanced Digital Twin Powered by FIWARE. Sensors. 2025; 25(3):845. https://doi.org/10.3390/s25030845

Chicago/Turabian Style

Costa, André, João Miranda, Duarte Dias, Nuno Dinis, Luís Romero, and Pedro Miguel Faria. 2025. "Smart Maintenance Solutions: AR- and VR-Enhanced Digital Twin Powered by FIWARE" Sensors 25, no. 3: 845. https://doi.org/10.3390/s25030845

APA Style

Costa, A., Miranda, J., Dias, D., Dinis, N., Romero, L., & Faria, P. M. (2025). Smart Maintenance Solutions: AR- and VR-Enhanced Digital Twin Powered by FIWARE. Sensors, 25(3), 845. https://doi.org/10.3390/s25030845

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