Augmented reality for ndimensional building information modelling : Contextualization, Customization and Curation

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Augmented Reality for nDimensional
Building Information Modelling
Contextualization, Customization and Curation
XIA SHENG LEE, MOHD FARIS KHAMIDI
School of Built Environment
University of Reading Malaysia
Educity, Iskandar Puteri, Johor, Malaysia.
x.s.lee@reading.edu.my, m.f.khamidi@reading.edu.my
TIM JOHN LEES
School of Construction Management and Engineering
University of Reading
Whiteknights, Reading Berkshire, United Kingdom.
t.j.lees@reading.ac.uk
ZI SIANG SEE
Centre for Research-Creation in Digital Media
Sunway University
Bandar Sunway, Selangor, Malaysia.
zisiangsee@sunway.edu.my
CHANGSAAR CHAI
Department of Structure and Materials
Faculty of Civil Engineering, Universiti Teknologi Malaysia
Johor, Malaysia.
cschai@utm.my
Abstract— This paper presents an experimental method and
apparatus of augmented reality (AR) for nDimensional (nD)
building information modeling (BIM). BIM allows nD
information to be visualized simultaneously by architects,
engineers and constructors to gain a synchronized understanding
viewing from different perspectives. However, BIM is
conventionally being operated on a desktop-based computer
which makes collaboration less flexible, and it also creates an
isolation gap between the model and reality. This isolation gap
does not severely affect experienced and skilled professionals, as
they can bridge the isolation gap with their intuition developed
over the years. Nevertheless, users who are lack of such
experience will feel the isolation gap between the digital realm
and practicable reality, which could be the hurdle in project
participation and decision making. AR allows virtual content to
be mixed with real environment for user experience. In the
context of our study, AR is functional to present the nD
information of BIM, at the same time retaining users’ connection
with the reality. It is not just being utilized solely for
presentation, but also to maximize the potential for
communication, interaction and experience. This pilot study
investigates effective technological approach of using AR as an
effective collaboration technology combining with BIM through
proposed key aspects of contextualization, customization and
curation. Contextualization is significant to enable users to
understand the AR content by making the presented information
meaningful to the target audience, implemented thru the means
of 2D annotations, animations and options comparison. This
study compares both AR BIM with and without
contextualization. Customization can generate unique virtual
environment and content for different level of users tailored to
their needs and preference to create intuitive interaction with AR
BIM. Curation is crucial to provide users with a reliable
experience, and to formulate a continually improving AR BIM
thru log data and users’ feedback. All in all, this paper explores
the major aspects of contextualization, customization and
curation, to distinguish effective approach in the currently “free
for all” AR BIM development. Finally, an implication is provided
for future study in terms of balance in information sufficiency
and complexity for AR BIM.
Keywords— augmented reality; building information
modelling; contextualization; customization; curation
I. INTRODUCTION
Technology advancement in the form of “future shock” [1]
is developing at an exponential speed with synergy of diverse
emerging digital innovations. Collaborations among different
specializations are becoming more common than before [2], as
technologies that are previously enigmatic and expensive are
now widely available and affordable. This paper revisits two
maturing digital developments - augmented reality (AR) and
building information modelling (BIM) to explore the
combined application. While it is essential to review the
current industrial trends, this paper imaginatively explores the
combination of AR and BIM from the major aspects of
contextualization, customization and curation. Users who are
utilizing BIM in AR understand and appreciate the content
through contextualization, undergo unique experience
matching their preferences though customization, and
remember and archive the content through curation. These
aspects are instrumental to stimulate the adoption and
implementation process leading to practical functions, instead
of short-lived technological hype. This research adopted
framework analysis that visualizes interviewees’ preferences
and opinions reacting to different types of AR BIM models.
Such findings are later being scrutinized to understand each
model types’ strengths and weakness in contextualization,
customization and curation. It is noteworthy that such research
is significant to mitigate the fluctuation of technological
adoption and implementation as described in Gartner's hype
cycle [3]. This pilot study focuses on AR and BIM, but the
applied approach is suitable for other types of digital contents.

II. AUGMENTED REALITY
Augmented Reality (AR) [4] allows combination of a live
real-world visual experience with virtual interactive content on
computing devices [5] [6]. AR becomes widely available
along with the recent advances of mobile devices with usable
computing capabilities. One enabler for mobile AR is tracking
technology, such as computer vision techniques for tracking
off pre-defined markers or markerless images. The industrial
interest and need of integrating BIM with AR which allows
the physical context of each construction activity or task to be
visualized has been highlighted in previous study [7] [8].
Various accessibility of augmented visualization methods
allow BIM-related projects to be made available for
developers and end-users at faster speed, smaller devices, and
higher level of graphical details.
In this study, several graphical reproduction options of
BIM-project are being experimented to gauge the usefulness
of AR visualization. Markerless AR experience which allows
content library to be visualized on mobile devices can be
developed using AR browser systems (eg. Augment) or offline
mobile applications (eg. Unity and Vuforia). Typically AR
browser allows greater numbers of BIM content to be stored
online and presented without any constraint of mobile storage
in users’ devices. However, the stability of user experiences
highly relies on internet network speed. Therefore it is logical
and essential to deliver a moderate amount usable details for
AR objects with selective information to be presented in each
context related to the BIM-based project.
III. BUILDING INFORMATION MODELLING
Building Information modelling (BIM) is a fresh process
integrating multidimensional information [9] [10] to improvise
design, construction, and facility management for the whole
built environment [11]. BIM provides an efficient delivery
foundation that benefits all construction industry stakeholders
[12]. Such digital process makes it possible to invigorate
integration between BIM with AR to accommodate decision
making [13] by creating user-centric interface [14].
IV. DIGITAL CONTENT USER PERCEPTION AND SATISFACTION
In this study, digital content delivery focus in
contextualization is of the utmost importance [15] [16].
Contextualization is to localize the AR BIM applications
by ensuring that the correct meanings of source strings are
conveyed. In other words, it is giving meanings to AR BIM
content, so that it is understandable. Without
contextualization, users’ perception and satisfaction will be
hampered. It is also now much easier to provide unique
contents of direct relevance to individual customer [17] by
studying user perception and satisfaction [18].
Customization is defined as typically developed in
response to specific order by end users. It is to personalizing
AR BIM content, so that it suits specific needs. Digital
contents should be managed from the curation aspects by
maintaining and adding value to the content for both current
and future use [19]. Generally, researchers are familiar with
how to be an author, but now they have to learn how to
become a digital content curator [20] [21].
Curation is about maintaining and adding value to AR
BIM. It is deciding and archiving AR BIM content, so that it is
usable in the future. It is an active management and appraisal
of digital information over its entire life cycle [19]. In this
circumstance, AR BIM is specifically developed to improve
construction project management monitoring and control
through combination of live real-world visual and BIM model.
Therefore, it is expected to overcome project delivery
hindrance such as cost overrun and delay [22].
V. RESEARCH METHODOLOGY
In this case study, interview and literature review are the
selected methods for data collection purpose. Such methods
are perfect suited to distinguish objectives that have to be
complied, to accomplish the required outcomes and avoidance
of any entanglement or inaccuracy of data, which will then
distract the genuine intentions at the very initial phase.
During the study, the literature review is established ahead.
This inevitably would link to the obtainment of much precious
background knowledge regarding the arisen issues, in
contemporaneous with the gaining of more detailed review to
equip with the relevance outcomes to be stroke. Undoubtedly,
the data is been fully utilized to outline the conceptual phase,
explicate and elaborate the study’s criteria.
The personal interviews are executed to generate findings
for the desired objectives. This approach is best suited as the
upcoming results required have to be specific and personal-
oriented. The interviews are directed to respective personnel
of BIM-related projects; as inevitably, actual and professional
perspectives and facts are highly demanded to boost the
results’ reliability. It is important to choose personal interview
as abundant private and confidential data and information
were necessitate for current research and thus, privacy and
approval are decisive.
The interview sessions were carried out in September
2016. The data obtained from the interviews is transcribed and
analyzed. The framework analysis [23] is used to analyze the
interview data. Srivastava & Thomson (2009) defined
framework analysis as a qualitative method that is well-
appropriated for applied policy research. Framework analysis
is portraying satisfying performance when adapted to research
that has specific questions, a limited time frame, a pre-
designed sample and a priori issues. During the analysis
process, data is sifted, charted and sorted in parallel with key
themes using five steps, which are: (1) familiarization:
transcribing and reading the data, (2) identifying a thematic
framework, (3) indexing/ coding: using numerical or textual
codes to identify specific piece of data which correspond to
different themes, (4) charting, (5) mapping and interpretation.
In this study, there are 4 types of AR BIM models: (1)
texturized model (Fig. 1), (2) geometry with 2D info model

Fig. 1. Texturized model.
Fig. 2. Geometry with 2D info model.
Fig. 3. Geometry only model.
Fig. 4. Wire frame model.
(Fig. 2), (3) geometry only model (Fig. 3), and (4) wire frame
model (Fig. 4). TABLE I list the codes for different
interviewee’s opinion.
TABLE I. CODE FOR INTERVIEWEE’S OPINION
Code Description of interviewee’s opinion
C01 Improves job quality
C02 Increase productivity
C03 Enhances effectiveness
C04 Increase profit
C05 Access more information
C06 Helps in decision making
C07 Easy to learn with it
C08 Interaction is clear and understandable
C09 Can be used without expert help
C10 Improve communication in organization
C11 I want to use it
C12 I like the idea of using this model
The data obtained from the study is transcribed and
analyzed. Due to the limited numbers of interviewees that
understand both AR and BIM, only acceptance percentage
above 70% are considered valid. Simple data visualizations
are perform to better understand the results.
VI. FINDINGS AND DISCUSSIONS
There are five (5) architects, three (3) civil and structure
engineers and one (1) each of mechanical engineer and
electrical engineer participated in the interview. It is found
that 70% of the interviewees are middle executive level and
above, indicating a high credible of respondent profile in
terms of managerial level and working experience which are
salient to justify AR BIM contribution in this matter. The
findings are summarized in 3 tables: (1) TABLE II. Model
acceptance for contextualization, (2) TABLE III. Model
acceptance for customization and (3) TABLE IV. Model
acceptance for curation.
TABLE II. MODEL ACCEPTANCE FOR CONTEXTUALIZATION
Code
Type of Model
Texturized
Geometry
With
2D Info
Geometry
Only Wire Frame
C01 100.0% 100.0% 80.0% 50.0%
C02 90.0% 100.0% 70.0% 60.0%
C03 100.0% 100.0% 70.0% 60.0%
C04 70.0% 90.0% 40.0% 50.0%
C05 90.0% 100.0% 80.0% 60.0%
C06 100.0% 100.0% 60.0% 40.0%
C07 90.0% 90.0% 80.0% 50.0%
C08 90.0% 90.0% 50.0% 40.0%
C09 70.0% 80.0% 40.0% 40.0%
C10 100.0% 100.0% 70.0% 40.0%
C11 100.0% 100.0% 60.0% 60.0%
C12 100.0% 100.0% 70.0% 60.0%

TABLE III. MODEL ACCEPTANCE FOR CUSTOMIZATION
Code
Type of Model
Texturized
Geometry
With
2D Info
Geometry
Only Wire Frame
C01 90.0% 100.0% 70.0% 40.0%
C02 100.0% 100.0% 80.0% 50.0%
C03 100.0% 90.0% 70.0% 50.0%
C04 100.0% 100.0% 60.0% 50.0%
C05 100.0% 90.0% 60.0% 50.0%
C06 100.0% 100.0% 70.0% 50.0%
C07 100.0% 100.0% 70.0% 50.0%
C08 100.0% 100.0% 70.0% 50.0%
C09 80.0% 80.0% 50.0% 40.0%
C10 90.0% 80.0% 50.0% 50.0%
C11 100.0% 100.0% 50.0% 50.0%
C12 100.0% 100.0% 60.0% 50.0%
TABLE IV. MODEL ACCEPTANCE FOR CURATION
Code
Type of Model
Texturized
Geometry
With
2D Info
Geometry
Only Wire Frame
C01 100.0% 90.0% 50.0% 70.0%
C02 100.0% 80.0% 50.0% 70.0%
C03 100.0% 90.0% 50.0% 70.0%
C04 90.0% 80.0% 40.0% 60.0%
C05 100.0% 100.0% 60.0% 60.0%
C06 100.0% 80.0% 60.0% 60.0%
C07 80.0% 80.0% 70.0% 60.0%
C08 100.0% 80.0% 60.0% 60.0%
C09 70.0% 60.0% 50.0% 50.0%
C10 100.0% 80.0% 60.0% 60.0%
C11 100.0% 80.0% 60.0% 60.0%
C12 100.0% 80.0% 70.0% 50.0%
I. CONCLUSION
The findings demonstrate consistency among the
interviewees’ preferences. The most preferred type of model is
texturized model, followed by geometry with 2D info model.
These two types of models are recognized from the aspects of
helping users to contextualize to customize AR BIM contents.
As comparison, geometry only and wireframe models are not
as widely recognized as a good AR BIM application. While
this pilot study mainly focuses on construction industry
professionals, it is interesting using the same models and
interface to investigate other target groups based on different
categories such as genders, age, expertise levels etc. The
potential of AR BIM is both promising and challenging and
there are great potential for a new research direction from the
aspects of contextualization, customization and curation.
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