Identification of application areas for Augmented Reality in industrial construction based on technology suitability

Research studies in the application of Augmented Reality (AR) in the Architecture, Engineering, and Construction (AEC) industry have suggested its feasibility. However, realization of the use of AR in AEC requires not only demonstration of feasibility but also validation of its suitability. This paper comprehensively identifies AR application areas in industrial construction based on suitability of AR technologies. In order to successfully explore suitability of AR, this paper assesses work tasks from the viewpoint of human factors regarding visual information requirements to find rationale for the benefits of AR in work tasks. Based on the assessment of work tasks, this paper presents a comprehensive map that identifies AR application areas in industrial construction. The comprehensive map reveals that eight work tasks (layout, excavation, positioning, inspection, coordination, supervision, commenting, and strategizing) out of 17 classified work tasks may potentially benefit from AR support.

[1]  Steven K. Feiner,et al.  Augmented Reality in Architectural Construction, Inspection, and Renovation , 1996 .

[2]  R. Shepard,et al.  Mental Rotation of Three-Dimensional Objects , 1971, Science.

[3]  Bonsang Koo,et al.  Feasibility study of 4D CAD in commercial construction , 2002 .

[4]  Alexander H. Slocum,et al.  Automation and robotics opportunities: Construction versus manufacturing , 1994 .

[5]  A. Larsen,et al.  Pattern matching: Effects of size ratio, angular difference in orientation, and familiarity , 1985, Perception & psychophysics.

[6]  Robert W. Proctor,et al.  Human factors in simple and complex systems , 1993 .

[7]  Ronald Azuma,et al.  Recent Advances in Augmented Reality , 2001, IEEE Computer Graphics and Applications.

[8]  L. Cooper,et al.  Mental transformations and visual comparison processes: effects of complexity and similarity. , 1976, Journal of experimental psychology. Human perception and performance.

[9]  James H. Garrett,et al.  Potential of mobile augmented reality for infrastructure field tasks , 2002 .

[10]  Alan Dodson,et al.  The Use of Augmented Reality, GPS and INS for Subsurface Data Visualisation , 2002 .

[11]  G. Loftus,et al.  Short-Term Memory Factors in Ground Controller/Pilot Communication , 1979 .

[12]  Steve Wilson,et al.  A High-Performance, High-Accuracy RTK GPS Machine Guiadance System , 2000, GPS Solutions.

[13]  John G Everett Construction automation--basic task selection and development of the CRANIUM , 1991 .

[14]  Phillip S. Dunston,et al.  Mixed Reality Benefits for Design Perception , 2002 .

[15]  D. Alan Allport,et al.  SHIFTING INTENTIONAL SET - EXPLORING THE DYNAMIC CONTROL OF TASKS , 1994 .

[16]  Bruce H. Thomas,et al.  Using Augmented Reality to Visualise Architecture Designs in an Outdoor Environment , 1999 .

[17]  S. Monsell,et al.  Costs of a predictible switch between simple cognitive tasks. , 1995 .

[18]  Jie Shen,et al.  Urban Planning Using Augmented Reality , 2001 .

[19]  James Jerome O'Brien Construction inspection handbook : total quality management , 1997 .

[20]  Yuichi Ohta,et al.  Mixed Reality: Merging Real and Virtual Worlds , 1999 .

[21]  Dale Goodhue,et al.  Task-Technology Fit and Individual Performance , 1995, MIS Q..

[22]  C. Bundesen,et al.  Visual transformation of size. , 1975, Journal of experimental psychology. Human perception and performance.

[23]  S. Kosslyn,et al.  Varieties of size-specific visual selection. , 1989, Journal of experimental psychology. General.

[24]  Paul Milgram,et al.  A Taxonomy of Real and Virtual World Display Integration , 1999 .

[25]  Marc Schiler,et al.  Augmented Reality: An Application for Architecture , 2000 .