A review of augmented reality visualization methods for subsurface utilities. (January 2022)

• Record Type: Journal Article
• Authors: Muthalif, Mohamed Zahlan Abdul; Shojaei, Davood; Khoshelham, Kourosh
• Is Part Of: Advanced engineering informatics. Volume 51(2022)
• Publication Date: 2022-01
• Subjects: Subsurface utility -- Visualization -- Augmented reality -- Depth perception -- Parallax effect; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2021.101498
• Languages: English
• ISSNs: 1474-0346

Abstract

Abstract: S ubsurface utilities are important assets that need to be perceived during any construction activities. Positioning and visualizing the subsurface utilities before the construction work starts has significant benefits for the effective management of construction projects. Augmented Reality (AR) is a promising technology for the visualization of subsurface utilities. The aim of this paper is to provide a comprehensive review of the state-of-the-art in AR visualization of subsurface utilities, including existing AR visualization methods, categorization of the methods and their drawbacks, comprehensive discussion on the challenges, research gaps and potential solutions. The paper begins with an introduction of current practice of locating subsurface utilities and an overview of different reality technologies including AR. We propose a taxonomy of AR visualization methods including X-Ray view, transparent view, shadow view, topo view, image rendering and cross-section view. We provide a comparison of existing methods in terms of quality of depth perception, occlusion of real world, complexity of visualization and parallax effect followed by a discussion of the drawbacks in these methods. Poor depth perception, parallax effect caused by the user movement, poor positional accuracy in Global Navigation Satellite System (GNSS) deprived or indoor areas and unavailability of accurate location information for generating virtual models are identified as main challenges and topics of future research in effective AR visualization of subsurface utilities.