Mobile augmented reality-based visualization framework for lifecycle O&amp;M support of urban underground pipe networks

Li, Minghao; Feng, Xin; Han, Yang; Liu, Xudu

doi:10.1016/j.tust.2023.105069

Cited by 13 publications

(12 citation statements)

References 40 publications

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“…Moreover, the accessibility and usability of these technologies for individuals with varying levels of fitness and technical proficiency remain areas for improvement. Ensuring that these systems are user-friendly and adaptable to different user needs is essential for their broader acceptance and effectiveness [31].…”

Section: F Challenges and Limitations Of Existing Systemsmentioning

confidence: 99%

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Tileubay,

Yerekeshova,

Baiganova

et al. 2024

IJACSA

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The fusion of augmented reality (AR) and deep learning technologies has ushered in a transformative era in the realm of real-time physical activity monitoring. This research paper introduces a system that harnesses the capabilities of PoseNet-based skeletal keypoint extraction and deep neural networks to achieve unparalleled accuracy and real-time functionality in the identification and classification of a wide spectrum of physical activities. With an impressive accuracy rate of 98% within 100 training epochs, the system proves its mettle in precise activity recognition, making it invaluable in domains such as fitness training, physical education, sports coaching, and home-based fitness. The system's real-time feedback mechanism, bolstered by AR technology, not only enhances user engagement but also motivates users to optimize their exercise routines. This paper not only elucidates the system's architecture and functionality but also highlights its potential applications across diverse fields. Furthermore, it delineates the trajectory of future research avenues, including the development of advanced feedback mechanisms, exploration of multi-modal sensing techniques, personalization for users, assessment of long-term impacts, and endeavors to ensure accessibility, inclusivity, and data privacy. In essence, this research sets the stage for the evolution of real-time physical activity monitoring, offering a compelling framework to improve fitness, physical education, and athletic training while promoting healthier lifestyles and the overall well-being of individuals worldwide.

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Section: F Challenges and Limitations Of Existing Systemsmentioning

confidence: 99%

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Tileubay,

Yerekeshova,

Baiganova

et al. 2024

IJACSA

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“…The detection of underground pipelines using classical methods is an important challenge in maintenance, repair, and risk assessment activities. Methods based on augmented reality technology may be useful for accurate on-site detection and mapping of underground pipe networks and their conditions, dynamic construction, maintenance, and emergency response [114].…”

Section: Systematic Literature Review Findingsmentioning

confidence: 99%

Bridging Geo-Data and Natural Gas Pipeline Design Standards: A Systematic Review of BIM-GIS Integration for Natural Gas Pipeline Asset Management

Demir,

Yomralioglu

2024

Energies

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In today’s world, effective management and the use of spatial data are of great importance in many sectors. Industries such as land management, asset management, and infrastructure management are areas where spatial data are heavily utilized. Advanced technologies such as Geographic Information Systems (GISs) and Building Information Modeling (BIM) are used in the processes of collecting, analyzing, and managing geographically enabled data (geo-data). These technologies enable the effective processing of large datasets, improve decision-making processes based on geographic information, and facilitate more efficient collaboration across sectors. This study conducts an in-depth examination of the existing literature on asset management, infrastructure management, and BIM-GIS integration using bibliometric analysis and systematic literature review methods. Bibliometric analysis is employed to determine statistical values such as current research trends, frequently cited authors, most used keywords, and country performances in the relevant field. This study’s results highlight future research trends and significant gaps in the areas of asset management, infrastructure management, natural gas pipelines, and BIM-GIS integration. In particular, this study demonstrates the critical importance of asset management and BIM-GIS integration for sustainable infrastructure design, construction, and management. In this context, attention is drawn to the importance of data standardization, digitization, systematic integration, and contemporary land management requirements.

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“…Li, Feng, Han and Liu [6] developed a mobile augmented reality-based framework to visualize static and dynamic data of a real-life urban gas pipe network. Tarek and Marzouk [28] developed a smartphone AR application to visualize infrastructure networks, thereby improving infrastructure operation and maintenance workflows.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Although the visualization of pipe conditions in a GIS map provides a powerful interface, inaccuracies in geographical data may inhibit the usefulness of such maps for operation and maintenance tasks. Recent studies reveal that visualization through augmented reality is one of the most cost-effective and dependable approaches for the operation and maintenance of urban underground pipe networks [6,7].…”

Section: Introductionmentioning

confidence: 99%

Utilization of Augmented Reality Technique for Sewer Condition Visualization

Nguyen,

Bui,

Seidu

2023

Water

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Wastewater pipelines are largely buried underground, and techniques for assessing and visualizing their condition are critical for planning and rehabilitation. This paper introduces a framework for integrating Geographic Information System (GIS), 3D-creation platform, augmented reality (AR) techniques, and machine learning algorithms for the dynamic visualization of the condition of sewer networks. A sewer network in Ålesund City, Norway, was used as a case study, and the developed framework was implemented on an Android OS and Microsoft HoloLens. The results show the potential applications of the integrated framework of GIS, AR, and 3D models for sewer condition visualization. The positioning accuracy of the application for 2D objects is equivalent to that of well-designed GPS receivers (approximately 1–3 m), depending on the handheld device used. Loading and locating 3D objects will be limited by the performance of the devices used.

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Mobile augmented reality-based visualization framework for lifecycle O&M support of urban underground pipe networks

Cited by 13 publications

References 40 publications

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Bridging Geo-Data and Natural Gas Pipeline Design Standards: A Systematic Review of BIM-GIS Integration for Natural Gas Pipeline Asset Management

Utilization of Augmented Reality Technique for Sewer Condition Visualization

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