An Implementation Methodology for Augmented Reality Applications
Phan, T.H.G. (2023)
Objective:
To develop an industry-agnostic, tool-agnostic Augmented Reality implementation methodology
(ARIM) for guiding the implementation of AR use cases across different industries (i.e., industry-agnostic). The methodology should assist project teams in choosing suitable AR tools for their
target use cases instead of prescribing any specific tool (i.e., tool-agnostic).
Methods:
The research consists of phase 1 literature review and phase 2 artifact design. The literature
review sets the scientific foundation for the artifact and identified research gaps in existing AR
implementation frameworks.
The identified research gaps translate to three key questions to be answered by the ARIM:
1. How to determine if a process can be enhanced with the use of AR?
2. How to determine which AR platform (webAR vs. native AR vs. AR headset) is most
suitable for the selected process?
3. How to determine which AR development tools (tracking and rendering engines) are
most suitable for the selected process and AR platform?
To answer the first question, 39 academic and industry AR use cases for multiple sectors
(industrials, entertainment, healthcare, education, emergency & rescue, military, and
miscellaneous sectors) were reviewed to synthesize common characteristics which make a
process an ideal candidate for AR.
To answer the remaining two questions, success factors for AR adoptions from existing
literature were translated to high-level selection criteria for AR platforms and AR development
tools. These high-level selection criteria are further contextualized with example AR use cases
and subsequently decomposed into low-level selection criteria. With this approach, the ARIM is
firmly built upon AR adoption success factors, enabling AR solutions implemented using the
methodology to achieve high user acceptance.
Results:
The proposed ARIM is illustrated in Figure 46. For demonstrating how the proposed ARIM can
be used in practice, a webAR application for monitoring the health of houseplants is
implemented as guided by the ARIM.
For validating how useful the ARIM is, three semi-structured interviews were conducted with
Accenture’s industry experts. Experts responded positively to the simplicity, thoroughness, and
value-add of the methodology. Additionally, expert feedback was used to further finetune and
align the methodology with Accenture’s current practice – see the revised ARIM in Figure 52.
PHAN_MA_EEMCS.pdf