Building Information Monitoring via Gamiﬁcation

Peter K

, Peter Ferschin

2 a

, Meliha Honic

3 b

and Iva Kovacic

3 c

Institute of Visual Computing and Human-Centered Technology, TU Wien, Vienna, Austria

Institute of Architectural Sciences, TU Wien, Vienna, Austria

Institute of Interdisciplinary Construction Process Management, TU Wien, Vienna, Austria

Keywords:

Gamiﬁcation, Building Monitoring, Building Information Modeling, Spatial Localization, 3D Visualization,

Mobile Applications, Crowdsourcing.

Abstract:

For efﬁcient facility management it is of high importance to monitor building information, such as energy con-

sumption, indoor temperature, occupancy as well as changes in building structure. In this paper we present a

novel methodology for monitoring information about building via gamiﬁcation. In our approach, the employ-

ees of a facility record the states of building elements by playing a competitive mobile game. Traditionally,

external sensors are used to automatically collect information about the building usage. In contrast to that, our

methodology utilizes personal mobile phones of employees as sensors to identify objects of interest and report

their state. Moreover, we propose to use crowdsourcing as a tool for data collection. This way the users of the

mobile game are collecting points and compete with each other. At the end of the game the winning team gets

the reward. We utilized various gamiﬁcation strategies to increase motivation of users to collect building data.

We extended the traditional 3D BIM model with temporal domain to enable tracking of building changes over

time. Finally, we run an experiment with real use case building in which the employees used our system for the

duration of three months. We studied our approach and our motivation strategies in a post-experiment study.

Our results suggest that gamiﬁcation can be a viable tool for building information monitoring. Additionally,

we note that motivation plays a critical role in the data acquisition by gamiﬁcation.

1 INTRODUCTION

Efﬁcient management of buildings is a challenging

task because of big amount of required information.

This building information may contain data about the

usage of a building such as rooms occupancy, uti-

lization of natural ventilation, usage of air condition,

heating preferences, direct sun exposure, load of com-

puting hardware, and many other factors. Automatic

heating systems, ventilation, power systems, building

insulation, shading systems and network infrastruc-

ture should be set up in a way to fulﬁll the needs of

the facility users (employees) and at the same time to

optimize the energy usage. Therefore, the acquisition

and monitoring of the building information, includ-

ing its usage by employees, is necessary for efﬁcient

facility management.

Typical problems in facility management are over-

heated ofﬁces, big energy loss due to the opened

https://orcid.org/0000-0002-2197-2760

https://orcid.org/0000-0002-8466-7122

https://orcid.org/0000-0002-0303-3284

windows with enabled heating at the same time, im-

proper lighting of the working area and others. In

order to tackle these problems the information about

the building elements and their properties is neces-

sary. The most common methodology for building

data acquisition is the installation of monitoring de-

vices which can automatically monitor electric power

usage, heating status, temperature, air quality, and

other metrics (Amaxilatis et al., 2017; M

att

a et al.,

2017; Sayed and Gabbar, 2018). Many new build-

ings already have these devices installed during con-

struction. However, numerous old buildings would

require additional installation of these devices. The

installation of monitoring devices to existing building

sometimes require invasive operation on walls, elec-

tric cables and other appliances. Additionally, these

devices are not always well accepted by the employ-

ees of a facility. Therefore, traditional data acquisi-

tion by monitoring devices is often not a feasible so-

lution. The alternative methodologies for building in-

formation acquisition include estimation from materi-

als, equipment, or occupancy data (Edirisinghe et al.,

Kán, P., Ferschin, P., Honic, M. and Kovacic, I.

Building Information Monitoring via Gamiﬁcation.

DOI: 10.5220/0010288902610270

In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 1: GRAPP, pages

261-270

ISBN: 978-989-758-488-6

261

Figure 1: WebGL visualization of collected building infor-

mation. Data, collected by our mobile game, can be inter-

actively mapped to 3D BIM model and visualized. Various

properties can be mapped to color coded visualization for

facility management to provide a clear overview of building

behaviour over time.

2017) and interviews with facility staff. A drawback

of these alternative methods is that they provide lim-

ited or subjective information.

In order to address the above mentioned problems

we propose a novel approach for building informa-

tion monitoring based on gamiﬁcation. In our ap-

proach the employees in the building play a competi-

tive mobile game in which they collect points by scan-

ning building elements and reporting their status. At

the end of the game period the team with the high-

est score wins valuable prizes. The critical factor in

data acquisition by humans is motivation. We hypoth-

esize that the gamiﬁcation approach may increase the

motivation of facility employees to provide informa-

tion about the building via their mobile devices. Ad-

ditionally, we introduced advanced challenges in the

game to boost the motivation of users. Our approach

can serve as an alternative methodology for monitor-

ing buildings, energy usage tracking, maintenance re-

porting, construction process tracking, or communi-

cation with users about building changes, problems

and requirements. Moreover, our method is based on

the Building Information Modeling (BIM) and the ac-

quired information is coupled with BIM objects in the

3D model of the building. By this way the changes

in the building and the behaviour data can be tracked

and stored in relation to the 3D positions of respective

building elements and their representations in BIM.

The relation of 3D objects in BIM model and the

collected building information over time can be used

for efﬁcient 3D visualization. We demonstrate an ex-

ample of such visualization on the web where the data

can be quickly and efﬁciently visualized by color cod-

ing on 3D objects (Figure 1). Such a visualization can

be especially useful for overview of building perfor-

mance and for decision making process.

In this paper the results of the ongoing research

project “SCI BIM: Scanning and data capturing for

Integrated Resources and Energy Assessment using

Building Information Modelling” are presented. The

overall aim of the project is to increase resources as

well as energy efﬁciency of buildings by coupling

of various digital technologies and methods. By us-

ing laser scanning and Ground Penetrating Technol-

ogy, a digital twin (BIM model) of an existing build-

ing is generated. Through gamiﬁcation, the users of

the building are integrated into the process of collect-

ing data about the building and the user behavior is

tracked.

Information about building usage and about its

thermal properties over time can lead to lower costs,

efﬁcient utilization of resources and lower ecological

footprint. Therefore, the methods for building infor-

mation acquisition and monitoring are of high impor-

tance. The presented research provides an alterna-

tive methodology to obtain information about exist-

ing building without installation of additional sensors

and therefore can contribute to increasing efﬁciency

of facility management. An additional beneﬁt of our

methodology is increased awareness of users about

energy efﬁciency in their working place. Moreover,

the proposed method can be extended in future to en-

gage users into energy saving by inﬂuencing their be-

havior.

2 RELATED WORK

2.1 Building Monitoring

Several methodologies have been presented in past re-

search to address the problem of building information

monitoring. The most common approach is to install

monitoring devices into the building (Sayed and Gab-

bar, 2018; Zhao et al., 2013; Amaxilatis et al., 2017;

att

a et al., 2017; Coates et al., 2017; Chen Yong-

pan et al., 2010). These methods can record vast va-

riety of data including air quality (Chen et al., 2014),

electric power usage, heating, ventilation, and air con-

ditioning (HVAC) operation, temperature, occupancy

and many others. Occupancy monitoring received

a special attention in previous research because the

GRAPP 2021 - 16th International Conference on Computer Graphics Theory and Applications

262

utilization of building and its equipment can be di-

rectly related to the presence of people. Akkaya et

al. (Akkaya et al., 2015) surveyed monitoring systems

based on internet of things (IoT) devices. Occupancy

can be also estimated in a non-intrusive way from

HVAC systems (Yang et al., 2012) or from utiliza-

tion of computer network infrastructure (Melﬁ et al.,

2011). Alternative methodologies for building infor-

mation monitoring include estimation from materials,

equipment data or maintenance data and interviews

with facility staff (Edirisinghe et al., 2017).

2.2 Building Information Modeling

Deﬁned by National Institute of Building Sci-

ences (of Building Sciences, 2020), BIM is a digital

representation of physical and functional characteris-

tics of a facility. As such it serves as a shared knowl-

edge resource for information about a facility forming

a reliable basis for decisions during its lifecycle from

inception onward. Moreover BIM is “a shared dig-

ital representation of physical and functional char-

acteristics of any built object. . . ” which is created

with object-oriented software, consisting of paramet-

ric objects that represent building components (Volk

et al., 2014; ISO Central Secretariat, 2016). BIM

can stand for the model itself – Building Information

Model or for the process - Building Information Mod-

eling (L

evy, 2011).

2.3 BIM with Temporal Data

BIM models play an important role in the facility

management. Therefore, building monitoring data

can be coupled with BIM representation to achieve

well deﬁned organization of data and its understand-

able visual representation. A framework for build-

ing information management based on BIM was pre-

sented by McArthur (McArthur, 2015) and Demian

and Walters (Demian and Walters, 2014). BIM with

monitoring data can be also utilized to detect failures

in the facility management (Motamedi et al., 2014).

The extension of BIM with structural sensors and col-

lected data was proposed by Rio et al. (Rio et al.,

2013). Visual programming approach for processing

big BIM data, including temporal information, was

presented by Preidel et al. (Preidel et al., 2017).

2.4 Gamiﬁcation

A gamiﬁcation approach for energy conservation in

buildings was proposed by Papaioannou et al. (Pa-

paioannou et al., 2017). The authors created a sys-

tem which monitors the energy utilization by spe-

ciﬁc users and provides personalized recommenda-

tions how to improve energy efﬁciency. Their ap-

proach also utilizes IoT devices. An augmented re-

ality game for educating children how to save energy

was proposed by Osello et al. (Osello et al., 2015).

Similarly to our research the authors used QR codes

to identify the objects. Augmented reality can also be

used as an intuitive interface to building management

systems (Jang et al., 2019). The surveys of gamiﬁ-

cation were presented by Seaborn and Fels (Seaborn

and Fels, 2015), Hamari et al. (Hamari et al., 2014)

and Deterding et al. (Deterding et al., 2011).

3 BUILDING MONITORING BY

CROWDSOURCING

Our methodology utilizes a competitive mobile game

to monitor information about building elements. In

this game the employees of a facility compete with

each other to collect points and win the ﬁnal prize.

All data about building elements need to be coupled

with BIM model of the building to ensure continuous

update. Therefore, the crucial part of the game is the

identiﬁcation of objects in relation to their BIM repre-

sentations. For this purpose we use QR codes which

are printed on a paper and sticked to the elements of

the building. For the target use case in our experiment

we generated 184 QR codes. We developed an auto-

mated approach for QR code generation from BIM

model. This automated QR code generation approach

works as follows: For each element of BIM model

which should be monitored we generate an individual

QR code. The QR code is generated from json repre-

sentation which includes the identiﬁer of object, the

type of object and veriﬁcation string. The veriﬁcation

string serves as a checksum of the other data to verify

authenticity of the QR code. By this way our mobile

application can identify if the QR code was generated

by our software or if it was faked. The example of

QR codes installation in a target room can be seen in

Figure 2.

Once the BIM objects can be identiﬁed in the real

building we need to monitor their states. This is done

by users who are playing our game. We used three

gamiﬁcation strategies in this game:

1. Collections of points

2. Competition with colleagues

3. Advanced challenges

Collection of points motivates users to monitor

building elements by giving them certain amount of

points for each scanned element. Our system allows

a facility manager to set up various point amounts for

Building Information Monitoring via Gamiﬁcation

263

Figure 2: An ofﬁce with installed QR codes for identiﬁca-

tion of objects.

Table 1: Types of target building elements which were mon-

itored during our experiment. The right column indicates

the amount of points which a user earns when reporting the

state of the element.

Building element Points

Window 3

Door 2

Light 1

Desktop computer 1

Laptop 2

Fan 1

Air Condition 1

Printer 1

Window shade 2

different elements (Table 1). This setting can be done

on the server side and it changes the game behavior

in real time. Variable point rewards for different ele-

ments enables on-demand increase of monitoring pri-

ority for speciﬁc building elements. For example if a

heating data is of importance for facility management,

the points for scanning heater can be higher than for

scanning other elements.

Our second gamiﬁcation strategy enables users to

compete with their colleagues. Additional motivation

in this strategy is the ﬁnal prize which the winning

team receives. The users are grouped in the teams of

size three. Assignment to a speciﬁc team is chosen by

each user at the ﬁrst login screen (Figure 3).

The third gamiﬁcation strategy, advanced chal-

lenges, was added in the middle of experiment to ex-

plicitly increase the motivation of users. With ad-

vanced challenges, the users can collect additional

points by scanning multiple items in a given period.

Challenges require scanning of items of speciﬁc type

(e.g. 3 windows, 2 doors etc.) or exactly speciﬁc

items (e.g. door number 3. QR codes also contain

names and IDs of elements). Challenges can be time

limited (e.g. 3 windows in 2 minutes) or time unlim-

ited (in the whole day). Each day a user gets four

daily challenges randomly selected from the pool. In

our experiments we designed 15 challenges in total.

Every time a user reports the state of building el-

ement, the data is sent to the server. Due to the cou-

pling of QR codes with BIM object identiﬁers, the

BIM model can be continuously updated. As all the

data is collected on the server, the building can be

monitored in real time via web interface (Figure 1).

An important aspect of the data collection is privacy

of users. To ensure the maximum privacy the sys-

tem only collects the minimum necessary data. This

includes the ID, type and status of building element,

time stamp and nickname of the user who scanned

the element. The nickname of the user is required

to count her points on the server side. For privacy

reasons our mobile game does not store any photos,

device identiﬁers, location or personal information.

3.1 Temporal BIM Model

In our methodology we enhanced traditional BIM

model of the building with temporal data to enable

coupling of collected monitoring information with 3D

representation of the building. We store temporal data

in a separate ﬁle. The binding of records from this

ﬁle with building elements in BIM model and with

real objects (tagged by QR codes) is achieved by us-

ing uniﬁed building element identiﬁers. These identi-

ﬁers were created manually during the reconstruction

of BIM model. Then, they were propagated into the

QR codes generation and event reporting. The cre-

ation of our temporal BIM model, coupled with real

building, was done in three steps:

1. Manual Remodeling from Point Cloud. We ob-

tained a point cloud model of the building by laser

scanning and photogrammetry methods. Then,

the model was manually remodeled from point

cloud to create its BIM representation (Figure 4).

2. Automatic Generation of QR Codes and Their

Installation in Real Building. QR codes encode

the building element identiﬁers from manual re-

modeling. This way they guarantee the coupling

of real objects with BIM model.

3. Storing Temporal Events Referenced by Build-

ing Element Identiﬁers into External File. Each

record is stored as a separate row in this ﬁle. In

our implementation we read the object identiﬁer

from QR code. Nevertheless, the connection be-

tween temporal data and BIM model can work

also without QR codes and even the traditional

monitoring devices can be used. Example of our

temporal data storage is show in Figure (Figure 4).

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264

Figure 3: The screens of our mobile application for building information monitoring. Login screen is shown to the users only

once at the ﬁrst run of the application. After they pick a user name, it stays the same for the rest of the game.

Figure 4: From top to bottom: Scanned point cloud from

our target use case building, BIM model which was manu-

ally remodeled from point cloud, and temporal data stored

in a spreadsheet and linked to the BIM representation. Item-

Name is the uniﬁed identiﬁer which links the temporal data

to speciﬁc BIM objects.

3.2 Mobile Game

We developed a competitive mobile game to inves-

tigate our methodology for information monitoring.

The main screen of the game shows camera image in

real time to allow user to scan a QR code (Figure 3).

Once the QR code is decoded the mobile application

allows user to select the state of the scanned building

element. The states of various types of objects can

differ. Therefore, we store the object types and their

possible states on the server and load them each time

the application starts or resumes. Every object type

can have its own states. For example the heater can

have the values from 1 to 6 and the window can have

the states open, partially open and closed. When a

user selects the state of scanned object she can press

the submit button and send the data to the server. By

this action the user earns points for given object type.

We used Unity3D to implement our mobile game

and we built it for iOS and Android platforms. The

server side utilizes Google Sheets to store the in-

formation about building elements. The information

is transferred via Google API. Storing information

in Google Sheets enables fast processing by any 3

party software, human readability and interactive vi-

sualization of data.

3.3 Visualization of Crowdsourcing

Data

In order to visualize the collected building informa-

tion we developed a web application which utilizes

WebGL. As the data is coupled with BIM representa-

tion of the building, we can visualize it in 3D. The vi-

sualization shows color coded values on the 3D BIM

model directly to the facility manager. Additionally,

the visualization is interactive and a facility manager

can see various properties mapped on the model. The

web application also contains time axis by which a

manager can control the time period of data to be vi-

sualized. In our implementation data from one week

window (starting with a selected date) are aggregated

Building Information Monitoring via Gamiﬁcation

265

for visualization but this window can be set to arbi-

trary length. The web visualization always works on

the real-time data stored on the server so even new

events can be observed in real time. The screenshot

from our WebGL visualization can be seen in Fig-

ure 1.

4 USE CASE EXPERIMENT

4.1 Experiment Design

The experiment was designed to study the user per-

ception of our gamiﬁcation methodology. Our main

research question was whether our gamiﬁcation ap-

proach is seen by the users as equivalent or better than

traditional building monitoring with sensors in certain

aspects. We used six metrics to compare our method-

ology with traditional sensor-based approach: gen-

eral user preference, practicality, enjoyability, time

demand, privacy, and cost. These metrics were sub-

jectively reported in a ﬁnal post-experiment question-

naire using two-alternative, forced-choice approach.

In this approach the users were instructed to indi-

cate their preferred method of information monitoring

amongst two options: (1) Gamiﬁcation approach and

(2) monitoring sensors. After the general preference

question the users were asked to explain their choice

in an open question. In addition to the general prefer-

ence, the users indicated which method do they con-

sider more practical, more enjoyable, less time con-

suming, better in terms of privacy and better in terms

of costs. If the frequencies of user preferences for our

method are better or comparable to the preferences

for monitoring sensors from certain aspects, we might

consider our approach successful.

Additionally, we studied the motivation factor

for building information monitoring by facility users.

For this purpose we used a four-alternative, forced-

choice approach. The users were asked to indicate

which strategy was the main source of their moti-

vation amongst the following options: Collection of

points, competition with colleagues, advanced chal-

lenges, and other. Finally, we studied the usabil-

ity of our mobile application using system usability

score (SUS) (Brooke, 1996) and we also analyzed the

rate of reported states over time. The user preference

questions, motivation questions and system usability

questions were assembled into ﬁnal post-experiment

questionnaire. The employees of the building who

participated in our game were asked to ﬁll in this

questionnaire at the end of the experiment.

User preference

Practicality

More enjoyable

Less time consuming

Better privacy

Lower costs

Gamification Monitoring sensors

Figure 5: Frequencies of user answers to the preference

questions. Each row indicates the number of users who pre-

ferred our gamiﬁcation approach (dark blue) and the num-

ber of users who preferred monitoring sensors (light blue)

from speciﬁc aspect.

4.2 Target Building

The target use case for our study was a university fa-

cility. The working group had 26 employees in the

time of study. 11 of them participated in our experi-

ment using their personal mobile devices. The users

monitored building information in 13 ofﬁces of the

target building. The types of monitored building el-

ements can be seen in Table 1. We did not monitor

the status of heating because the experiment was con-

ducted in summer.

4.3 Procedure

We studied the proposed gamiﬁcation methodology

in a target use case building in the duration of three

months. In the preparation phase we attached our gen-

erated QR codes to the building elements. During our

experiment, traditional monitoring devices were also

installed in the building so the users could directly

compare using of these devices and our gamiﬁcation

strategy. The employees, working in the use case

building, installed our mobile game on their devices.

We conducted an initial brieﬁng workshop where we

explained how the game works, how is the data col-

lected, which traditional monitoring devices are in-

stalled and what is the purpose of the study. Then,

the competition started. At the end of the study the

users were asked to ﬁll in the post-experiment ques-

tionnaire. The three user groups with the most col-

lected points won the ﬁnal prizes in form of goodies.

5 RESULTS

Eleven participants were playing our game during the

experiment. As the participation in the experiment

was voluntary, only 5 out of 11 participants answered

GRAPP 2021 - 16th International Conference on Computer Graphics Theory and Applications

266

192

13 13

100

150

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Number of records per day

Figure 6: Frequencies of data reporting by our mobile application per day during the experiment. Measured values on the y

axis indicate the amount of scanned QR codes (i.e. reported items). The data labels are only show on the peak days for clarity.

the post-experiment questionnaire (2 females and 3

males, in age from 25 to 31). The users were asked

about their preference between gamiﬁcation and mon-

itoring devices in terms of general judgment, practi-

cality, which one is more enjoyable, less time con-

suming, better in terms of privacy and better in terms

of costs. The resulting frequencies of user preferences

can be seen in Figure 5. In terms of general pref-

erence, the users preferred monitoring devices more

than our gamiﬁcation strategy. As we analyze the spe-

ciﬁc aspects of user preferences we can see that this

preference was based on the users seeing monitoring

sensors more practical and less time consuming than

using gamiﬁcation method. On the other hand, the

participants preferred our gamiﬁcation strategy before

monitoring sensors in terms of enjoyability, privacy

and lower costs.

Our second research aim was to investigate which

of the used gamiﬁcation strategies was the main

source of motivation. Collection of points and com-

petition with colleagues was each chosen by two dis-

tinct users as the main source of their motivation. Sur-

prisingly, the advanced challenges were not stated as

the main source of motivation by any user. Neverthe-

less, it might have motivated users but it was not per-

ceived as more motivating than collections of points

and competition with colleagues.

In order to evaluate usability of our mobile ap-

plication, we utilized SUS questionnaire (Brooke,

1996). The average system usability score, calculated

according to Brooke, was 75.5 in a range from 0 to

100 where 100 means the highest usability score.

The answers to the open question support the pref-

erence votes of participants. The users who pre-

ferred electronic sensors commented that they have

less work to do. One user, who preferred gamiﬁcation

approach, explained his preference by better privacy

because the monitoring sensors allow certain level of

surveillance.

In order to further analyze the motivation of users

and usage of our mobile application, we plotted the

frequencies of data reporting onto a time axis (Fig-

ure 6). This plot shows the amount of QR codes

scanned by users per each day during the 3 months

period of experiment.

6 DISCUSSION

The main goal of our experiment was to validate the

proposed gamiﬁcation strategy for building monitor-

ing in a real scenario. Eleven people used our ap-

plication during 3 months on a voluntary basis. 943

records about states of building elements were gath-

ered during this period. The distribution of report-

ing activity can be seen in Figure 6. As we can ob-

serve in this ﬁgure, some days were populated by high

activity while some others report no scanning at all.

During our experiment as well as after data analysis

we found that motivation plays a critical point in our

gamiﬁcation strategy. The initial motivation was very

high, leading to the peak of 192 records per day, be-

cause all users were interested in the application and

they were eager to compete with each other. How-

ever, after one week, the number of records per day

dropped rapidly. The second version of the applica-

tion, containing advanced challenges, was released on

22.7.2019. The activity was again partially increased

after this release. There were also additional unre-

lated peaks of activity during the whole period of ex-

periment. We should note that the experiment was

conducted during the summer time while some of the

users might have been on holidays for part of the time.

Moreover, the data reporting by our mobile applica-

tion was not part of the work duties of employees. We

hypothesize that the motivation could be higher if data

collection was done by facility staff, like security and

cleaning personal, as part of their work responsibili-

ties. As our application was accepted and regularly

used by our participants, our experiment suggests that

Building Information Monitoring via Gamiﬁcation

267

gamiﬁcation strategy can be a valid tool for building

monitoring. However, the motivation plays an impor-

tant role in this process and the results are highly de-

pendent on human factor. During the experiment, we

also motivated participants extrinsically by the reward

for the three best user groups with the highest number

of collected points. At the end of the experiment the

winners obtained the prizes in form of goodies.

We used the post-experiment questionnaire to

compare our method with monitoring devices in terms

of user preference and to study the main source of

motivation for data collection by users. In terms of

general preference monitoring devices were preferred

more by users. The main reason for this preference

was that with monitoring devices, the users had no

additional workload for collecting the building infor-

mation. On the other hand, the gamiﬁcation approach

was judged by the users as more enjoyable, with bet-

ter privacy and lower costs. From the answers to open

question and from personal discussions with users we

saw that people would like to secure their privacy.

They felt uncomfortable with having installed mon-

itoring sensors because they were afraid of unwanted

surveillance. On the other hand they trusted our mo-

bile application because we informed them during

bootstrapping meeting that we do not collect any per-

sonal data, any location information or any occupancy

information.

Based on the results from the study and frequen-

cies of data records we hypothesize that gamiﬁcation

approach could serve as a complementary approach to

traditional building monitoring, especially in places

where the motivation of users could be extrinsically

increased. It could be particularly utilized in buildings

where installation of sensors is not practical, where

the amount of users is high and where the rate of data

capturing is not of highest importance.

We did not evaluate the statistical signiﬁcance of

our ﬁndings because the sample size was too small to

infer any general conclusions. Instead, we see our re-

sults as user-based indications about acceptance, va-

lidity and usage of our gamiﬁcation approach.

Finally, an interesting option to note is the data

collection by manual user reporting to Excel sheet or

paper. Two employees, working in the target use case,

explicitly asked for this option because they did not

have appropriate mobile device, they wanted to par-

ticipate in the data collection and they considered the

option of direct data entering as more efﬁcient. We al-

lowed them to collect data this way during the time of

experiment. However, in contrast to their assumption

of higher efﬁciency, they entered only 21 records and

they reported states of building elements only three

days out of total duration of the experiment. The sam-

ple size is too small to draw any conclusions in this

case, however we hypothesize that efﬁciency of using

mobile application is higher than with manual report-

ing.

6.1 Limitations and Future Work

Despite the acceptance of our gamiﬁcation strategy

by participants, our investigation had several limita-

tions. One of the main constraints and critical point of

the proposed methodology is the motivation of users.

As we can observe in frequencies of data reporting

per day (Figure 6), some days are not covered by

data. Therefore, the motivation would need to be in-

creased to increase frequency of scanning and thus

cover the required data rate. Both extrinsic and intrin-

sic principles can be used to increase motivation in

this case. Moreover, an important point in bootstrap-

ping the data collection is to motivate more people

to install the application and join the data collection.

In our experiment 11 out of 26 employees agreed to

participate. If this number was higher, the data rate

coverage might have been higher too. The resulting

guideline for future experiments with gamiﬁcation in

building information acquisition is to invoke a strong

extrinsic motivation at the bootstrapping of the data

collection to increase the amount of participants. Ad-

ditionally, other gamiﬁcation aspects can be added to

the application in the future to increase motivation.

These strategies may include levels, personalized pro-

ﬁles, special skills or new measurement features (e.g.

sound loudness measurement, illumination measure-

ment, etc.).

The main limitation of our post-experiment evalu-

ation was small amount of participants who ﬁlled the

questionnaire. Our sample size for this questionnaire

was only ﬁve people. For this reason conclusions

about statistical signiﬁcance of our results could not

be drawn. In future work we aim at repeating this

study with improved version of our mobile applica-

tion, bigger user group and stronger emphasis on mo-

tivation of participants.

In this paper we did not evaluate the quality of

gathered monitoring data. In the future we plan to

compare the frequency and quality of our collected

data to sensor data. We expect this comparison to

reveal additional insights on practicality of our ap-

proach for building monitoring. We hypothesize that

more users would help to increase monitoring fre-

quency and data quality.

One of the avenues for prospective future work is

the usage of mobile application to not only collect in-

formation about the building but to also actively af-

fect the energy efﬁciency of the building by actions

GRAPP 2021 - 16th International Conference on Computer Graphics Theory and Applications

268

of users. For this purpose gamiﬁcation can be again

used in form of collection of points for actions which

positively affect energy status (e.g. closing windows

while air condition is on). In this case the application

can provide the users with hints how their behavior

can efﬁciently improve their working environments.

7 CONCLUSION

In this paper we have presented a novel approach for

building information monitoring via crowdsourcing

and gamiﬁcation. The core of our methodology is

the mobile application which allows employees of the

building to use their mobile devices as sensors and re-

port the information about building elements in time.

The users can then collect points for information re-

porting and compete with each other to win the prize.

We enhanced the 3D BIM model of a building with

temporal data to store the gathered monitoring infor-

mation. On top of data model in our method we built a

webGL application to visualize collected data in real

time on the 3D model. We conducted a three-months

experiment in the use case building and we evalu-

ated our gamiﬁcation approach using post-experiment

questionnaire.

The ﬁndings from our experiment indicate that

while monitoring devices are preferred way for build-

ing information collection, our gamiﬁcation approach

can be also accepted and valid methodology for this

task. The main beneﬁts of our method in compari-

son to monitoring devices is higher privacy and en-

joyment factor. One of our main ﬁndings is that mo-

tivation is a critical aspect in user-oriented data col-

lection and it needs to be speciﬁcally addressed from

the very beginning of the project. A vital future uti-

lization of gamiﬁcation in facility management could

be to not only passively monitor data but to actively

inﬂuence energy efﬁciency by user actions. As future

outlook, the proposed concept will enable the main-

tenance of digital twins throughout the life cycle of

buildings (the structural changes of building elements

are automatically adopted in the BIM model). We be-

lieve that continuation of research on this topic will

allow alternative building monitoring approaches, like

gamiﬁcation, to be more practical and closer to the de-

ployment in real-world scenario.

ACKNOWLEDGEMENTS

We would like to thank the participants of our study

for their dedication in using our mobile application

for data collection and for their patience with imper-

fections in our implementation. This research was

funded by Austrian Ministry for Transport, Innova-

tion and Technology through the Austrian research

promotion agency FFG under grant no. 867314.

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