This study presents a multi-user virtual reality (VR) tool designed to enhance hands-on learning in engineering education through real-time sensorized digital twins. The motivation stems from the limitations of traditional laboratory settings, such as time constraints and restricted access to physical equipment, which can hinder practical learning. The developed environment allows multiple students, wearing VR headsets, to interact simultaneously with a real-time synchronized virtual model of an engine, replicating its physical counterpart at the Mechanical Engineering Laboratory of the Pontificia Universidad Católica de Valparaíso, Chile. This novel integration of VR and digital twin technology offers students a unique opportunity to observe engine behavior in operation within a safe, controlled virtual space. By bridging theoretical knowledge with practical experience, this approach deepens understanding of complex mechanical concepts while fostering the development of key technical skills. Additionally, the use of real-time data visualization and digital twins provides a safer, more interactive, and efficient alternative to traditional laboratory practices, overcoming constraints like time limitations and equipment availability. This innovative method introduces students to Industry 4.0 principles, encouraging data-driven analysis and informed decision making.

This paper presents an integrated methodology for remote monitoring, technical training and early warning systems in virtual reality environments oriented towards Industry 4.0. The proposal incorporates an engine modeled as a digital twin in Unity 3D, connected to physical sensors, and transmitted through an IoT platform. This architecture allows continuous monitoring and immersive visualization, in addition to generating alerts when operating conditions exceed critical limits, allowing users to simulate fault conditions in real time and perform interactive training without putting equipment or operators at risk. This work proposes a low-cost simulation platform, based on virtual reality and real-time digital twins, designed to support training and capacity building in industrial environments. This methodology seeks to propose general guidelines that allow the integration of these technologies in a general way to enrich both preventive and predictive maintenance mechanisms, as well as training processes.

Work-related musculoskeletal disorders (MSDs) remain a global occupational health priority, with recognized limitations in current point-in-time assessment methodologies. This research extends prior computer vision ergonomic assessment approaches by implementing biological proprioceptive feedback principles into a continuous, real-time monitoring system. Unlike traditional periodic ergonomic evaluation methods such as “Rapid Upper Limb Assessment” (RULA), our bio-inspired system translates natural proprioceptive mechanisms—which enable continuous postural monitoring through spinal feedback loops operating at 50–150 ms latencies—into automated assessment technology. The system integrates (1) markerless 3D pose estimation via MediaPipe Holistic (33 anatomical landmarks at 30 FPS), (2) depth validation via Orbbec Femto Mega RGB-D camera (640 × 576 resolution, Time-of-Flight sensor), and (3) proprioceptive-inspired alert architecture. Experimental validation with 40 adult participants (age 18–25, n = 26 female, n = 14 male) performing standardized load-lifting tasks (6 kg) demonstrated that 62.5% exhibited critical postural risk (RULA ≥ 5) during dynamic movement versus 7.5% at static rest, with McNemar test $p<0.001$ (Cohen’s $h=1.22$, 95% CI: 0.91–0.97). The system achieved 95% Pearson correlation between risk elevation and alert activation, with response latency of $42.1\pm 8.3$ ms. This work demonstrates technical feasibility for continuous occupational monitoring. However, long-term prospective studies are required to establish whether continuous real-time feedback reduces workplace injury incidence. The biomimetic design framework provides a systematic foundation for translating biological feedback principles into occupational health technology.

This work presents an integrated experimental and machine learning study on the fire performance of sisal fiber-reinforced polyester composites treated with magnesium hydroxide as a flame retardant. A total of 43 small-scale fire resistance tests were conducted in a custom-built gas-fired furnace following ISO 834 and NCh935/2 standards. Key parameters—including fiber content, flame retardant proportion, catalyst, and accelerator—were correlated with burn time and mass loss. Linear regression revealed negligible to weak correlations, while nonlinear models (Random Forest, Support Vector Regression, and Deep Neural Network) showed improved predictive capacity. The Deep Neural Network achieved the best performance (MSE = 0.061, R² = 0.334). Experimental results confirm that magnesium hydroxide substantially increases burn time, whereas sisal fiber content alone has a minimal effect on fire resistance. This study highlights an affordable strategy for enhancing the fire safety of bio-based composites and demonstrates the potential of machine learning to optimize material formulations. Future research should expand the dataset and validate the models through standardized large-scale fire tests. However, the findings are limited to small-scale fire resistance tests under controlled laboratory conditions and should not be generalized to full-scale structural applications without further validation.

This paper presents the design, development, and preliminary validation of a haptic virtual reality simulator for Shielded Metal Arc Welding (SMAW) at the Pontificia Universidad Católica de Valparaíso, Chile, aimed at enhancing psychomotor training for mechanical engineering students in line with Industry 4.0 demands. The system integrates Unity 3D, a commercial haptic device, and a custom 3D-printed electrode holder replicating the welding booth, enabling interaction through visual, auditory, and tactile feedback. Thirty students with minimal welding experience and seven experts participated in usability and realism assessments. The results showed that 80% of students perceived motor skill improvement, 60% rated realism as adequate, and 90% preferred hybrid training (simulator + workshop). The prototype was practically implemented at the mechanical engineering school, requiring only a mid-range workstation, the Touch haptic device, and the developed software, demonstrating feasibility in real academic settings. The findings indicate potential to build confidence, support motor coordination, and provide a safe, resource-efficient training environment, while experts emphasized the need for automated feedback and improved haptic fidelity. The modular architecture allows scalability, extension to other welding processes, and adaptation for inclusive education. This prototype demonstrates how locally developed immersive technologies can modernize technical education while promoting sustainability, accessibility, and skill readiness.

This article reports the design, implementation, and formative perception-based evaluation of an early-stage virtual reality (VR) prototype that integrates a virtual cane, localized haptic feedback, 3D audio, and a three-layer bioinspired sensing framework. The prototype was implemented in Unity 2022.3 using the XR Interaction Toolkit and URP and was structured according to design science research methodology (DSRM). The bat–whisker–contact framework was used as a functional abstraction to organize distal auditory reference or warning, proximal haptic feedback, and contact confirmation; it was not evaluated against a non-bioinspired baseline. The completed evaluation consisted of an anonymous, voluntary, post-use questionnaire administered to 25 sighted participants who could select which visual-input configurations to experience. The analysis focused on reported clarity, tolerability, initial signal interpretability, and design feedback; it did not include objective navigation metrics or assess clinical efficacy, training transfer, accessibility outcomes, or orientation-and-mobility performance in blind or low-vision users. General responses suggested favorable perceived clarity and multimodal usefulness, while cane length, floor-versus-wall/obstacle differentiation, and reported discomfort identified priorities for technical refinement. In the simulated no-vision condition (n = 21), participants reported high reliance on the cane response, whereas reported initial insecurity or doubt and basic mental map ratings remained mixed. The study contributes an early-stage technological artifact and a formative basis for subsequent controlled evaluations with objective performance measures, reference conditions, and target users or orientation and mobility specialists.