Smart adaptive augmented reality SAARTool for personalized training in advanced industrial assembly operations

Abstract Enhancing technical training through adaptive augmented reality (AR) is crucial for improving skill acquisition and operational efficiency in industrial environments. This paper presents SAARTool, an innovative Smart and Adaptive Augmented Reality Tool designed for workforce training in olive oil sector. By integrating geometric constraints and real-time feedback, SAARTool ensures precise assembly execution and disassembly tasks, addressing key limitations in XR training solutions. SAARTool employs real-time feedback and three novel dynamic adaptive algorithms, optimizing task complexity based on user performance across 15 structured training stages guided by defined control parameters. Experimental results show that SAARTool significantly enhances practical skill acquisition, reducing execution times and improving performance consistency compared to conventional AR-based training. Statistical analyses, including Student’s T-test, Mann–Whitney U and Two-Way Anova, confirm superior SAARTool effectiveness in standardizing procedural training outcomes, particularly for individuals with limited experience. Unlike conventional AR solutions that require high-performance computing, SAARTool operates efficiently with minimal hardware, lowering adoption barriers.

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Publication Details

Journal
Virtual Reality
Published
2026-05-12
DOI
https://doi.org/10.1007/s10055-026-01385-4
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Smart adaptive augmented reality SAARTool for personalized training in advanced industrial assembly operations

Juan de Dios Caballero-Garcia, Adonis Jose Pabuena-García, Cristina Martín-Doñate, Diego Francisco García-Molina et al.
Virtual Reality
Augmented Reality Applications
article

Smart adaptive augmented reality SAARTool for personalized training in advanced industrial assembly operations

Juan de Dios Caballero-Garcia, Adonis Jose Pabuena-García, Cristina Martín-Doñate, Diego Francisco García-Molina, Jorge Manuel Mercado-Colmenero
article en

Abstract

Abstract Enhancing technical training through adaptive augmented reality (AR) is crucial for improving skill acquisition and operational efficiency in industrial environments. This paper presents SAARTool, an innovative Smart and Adaptive Augmented Reality Tool designed for workforce training in olive oil sector. By integrating geometric constraints and real-time feedback, SAARTool ensures precise assembly execution and disassembly tasks, addressing key limitations in XR training solutions. SAARTool employs real-time feedback and three novel dynamic adaptive algorithms, optimizing task complexity based on user performance across 15 structured training stages guided by defined control parameters. Experimental results show that SAARTool significantly enhances practical skill acquisition, reducing execution times and improving performance consistency compared to conventional AR-based training. Statistical analyses, including Student’s T-test, Mann–Whitney U and Two-Way Anova, confirm superior SAARTool effectiveness in standardizing procedural training outcomes, particularly for individuals with limited experience. Unlike conventional AR solutions that require high-performance computing, SAARTool operates efficiently with minimal hardware, lowering adoption barriers.

Virtual Reality
Universidad de Jaén (ES), C.P.Q. Ibérica (Spain) (ES)
Universidad de Jaén
Openalex Percentile: Top 5%
Augmented Reality Applications
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