Research and Application of YOLOv11-Based Object Segmentation in Intelligent Recognition at Construction Sites DOI Creative Commons

Luhao He,

Yongzhang Zhou, Lei Liu

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(12), P. 3777 - 3777

Published: Nov. 26, 2024

With the increasing complexity of construction site environments, robust object detection and segmentation technologies are essential for enhancing intelligent monitoring ensuring safety. This study investigates application YOLOv11-Seg, an advanced target technology, recognition on sites. The research focuses improving 13 categories, including excavators, bulldozers, cranes, workers, other equipment. methodology involves preparing a high-quality dataset through cleaning, annotation, augmentation, followed by training YOLOv11-Seg model over 351 epochs. loss function analysis indicates stable convergence, demonstrating model’s effective learning capabilities. evaluation results show [email protected] average 0.808, F1 Score(B) 0.8212, Score(M) 0.8382, with 81.56% test samples achieving confidence scores above 90%. performs effectively in static scenarios, such as equipment Xiong’an New District, dynamic real-time workers vehicles, maintaining performance even at 1080P resolution. Furthermore, it demonstrates robustness under challenging conditions, nighttime, non-construction scenes, incomplete images. concludes that exhibits strong generalization capability practical utility, providing reliable foundation safety Future work may integrate edge computing UAV to support digital transformation management.

Language: Английский

The Future of Education: A Multi-Layered Metaverse Classroom Model for Immersive and Inclusive Learning DOI Creative Commons
Leyli Nouraei Yeganeh, Nicole S. Fenty, Yu Chen

et al.

Future Internet, Journal Year: 2025, Volume and Issue: 17(2), P. 63 - 63

Published: Feb. 4, 2025

Modern education faces persistent challenges, including disengagement, inequitable access to learning resources, and the lack of personalized instruction, particularly in virtual environments. In this perspective, we envision a transformative Metaverse classroom model, Multi-layered Immersive Learning Environment (Meta-MILE) address these critical issues. The Meta-MILE framework integrates essential components such as immersive infrastructure, interactions, social collaboration, advanced assessment techniques enhance student engagement inclusivity. By leveraging three-dimensional (3D) environments, artificial intelligence (AI)-driven personalization, gamified pathways, scenario-based evaluations, model offers tailored experiences that traditional classrooms often struggle achieve. Acknowledging potential challenges accessibility, infrastructure demands, data security, study proposed practical strategies ensure equitable safe interactions within Metaverse. Empirical findings from our pilot experiment demonstrated framework’s effectiveness improving skill acquisition, with broader implications for educational policy competency-based, experiential approaches. Looking ahead, advocate ongoing research validate long-term outcomes technological advancements make more accessible secure. Our perspective underscores shaping inclusive, future-ready environments capable meeting diverse needs learners worldwide.

Language: Английский

Citations

3
Advancing Building and Construction Higher Education: The Online Real-Time Block Model’s Contributions to Professional Skills, Gender Equity, and Industry Preparedness DOI Creative Commons
Nima Izadyar, Le Li,

Shuo Chen

et al.

Buildings, Journal Year: 2025, Volume and Issue: 15(2), P. 165 - 165

Published: Jan. 8, 2025

Traditional In-Person Semester-Length (IP-SL) courses often struggle with inherent time constraints, lack of flexibility, and geographic limitations, delaying effective learning accessibility for students. Moreover, the extended duration (SL) structure reduce focus due to engagement multiple subjects simultaneously, increased stress, limited timely feedback assessment. This study evaluates Online Real-Time Block Model (ORT-BM), an intensive online model, highlighting its potential enhance engagement, satisfaction, inclusivity in project-based programs like construction higher education. Building surveying as a critical field is selected case since professional surveyors must stay current rapidly evolving building codes, regulations, sustainability practices. However, rigid IP-SL leaves graduates less prepared meet industry needs. Conducting comparative analysis study, Bachelor Surveying program (NBBS) at Victoria University, research compares three teaching models: (2016–2018), (IP-BM, 2019–2020), ORT-BM (2020–2023) using Student Evaluation Units (SEU) data Quality Indicators Learning Teaching (QILT) metrics. Findings, derived from SEU QILT, reveal that improves student accelerates course completion rates, fosters gender equity through inclusive environments while enhancing geographically dispersed disadvantaged By integrating advanced digital tools virtual site visits, enhances readiness, aligning education standards. Future may explore developing hybrid models optimize cognitive load further, improve accessibility, flexibility.

Language: Английский

Citations

0
Drivers of VR Adoption by Generation Z: Education, Entertainment, and Perceived Marketing Impact DOI Creative Commons
Camelia Surugiu, Cătălin Grădinaru, Marius-Răzvan Surugiu

et al.

Administrative Sciences, Journal Year: 2025, Volume and Issue: 15(2), P. 41 - 41

Published: Feb. 2, 2025

Virtual reality (VR) can influence people’s lives and business development. It bring immersive experiences for people strengthen the relationships between customers companies. In this paper, Generation Z (Gen Z) members’ interest in VR is analyzed various domains, like education, entertainment, marketing. This study considers Technology Acceptance Model (TAM) theoretical framework explores factors influencing Gen Z’s perceptions of potential. The approach based on hypotheses a survey-based investigation, followed by logistic regression modeling. results show that attracts members to educational entertainment activities. Also, they believe important marketing importance investments VR, all three adapting strategies leverage VR’s potential effectively.

Language: Английский

Citations

0
Research and Application of YOLOv11-Based Object Segmentation in Intelligent Recognition at Construction Sites DOI Creative Commons

Luhao He,

Yongzhang Zhou, Lei Liu

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(12), P. 3777 - 3777

Published: Nov. 26, 2024

With the increasing complexity of construction site environments, robust object detection and segmentation technologies are essential for enhancing intelligent monitoring ensuring safety. This study investigates application YOLOv11-Seg, an advanced target technology, recognition on sites. The research focuses improving 13 categories, including excavators, bulldozers, cranes, workers, other equipment. methodology involves preparing a high-quality dataset through cleaning, annotation, augmentation, followed by training YOLOv11-Seg model over 351 epochs. loss function analysis indicates stable convergence, demonstrating model’s effective learning capabilities. evaluation results show [email protected] average 0.808, F1 Score(B) 0.8212, Score(M) 0.8382, with 81.56% test samples achieving confidence scores above 90%. performs effectively in static scenarios, such as equipment Xiong’an New District, dynamic real-time workers vehicles, maintaining performance even at 1080P resolution. Furthermore, it demonstrates robustness under challenging conditions, nighttime, non-construction scenes, incomplete images. concludes that exhibits strong generalization capability practical utility, providing reliable foundation safety Future work may integrate edge computing UAV to support digital transformation management.

Language: Английский

Citations

2