Mood Board: An IoT based Group Mood

Evaluation Tool
Shikhar Makhija Bimlesh Wadhwa
Electronics and Communication Engineering Department School of Computing
Netaji Subhas University of Technology National University of
Delhi, India Singapore
shikharm.ec@nsit.net.in Singapore
bimlesh@nus.edu.sg
Abstract—The proposed tool, Mood Board extends the Mood ability to recognize, understand and manage emotions [3].
Meter, a tool for social and emotional learning, by offering a platform SEL, is one of vital yet neglected role in student’s
for group’s mood evaluation. Mood Board is a portable and
independent hardware evaluation unit for real-time evaluation of development. [7] details that emotional tendencies vitally
group mood. This tool finds imminent application in schools to aid impact apart from the learning styles, in students’ academic
educators in cultivating better learning environment and inculcating and workplace performance. Mood Meter is a self-evaluation
emotional literacy among students.
tool for SEL which can be used in a guided (classroom or
Index Terms—mood, social and emotional learning, group
behavior, IoT, embedded systems, human computer interface workplace) or unguided (self-development) environment to
gauge one’s emotional patterns and create a general emotional
awareness [3], [8].
This tool aids educators in developing their students
I. INTRODUCTION
Emotional Intelligence (EI) and understand how and which
emotions affect creativity, learning and quality decision
Creativity, learning capability and academic or workplace
making.
performance of students and groups are affected by emotional
The four quadrants are based on two axis of core values,
intelligence, mood, emotions and sentiments [1], [2].
which are: valence (Pleasantness, represented by the X axis)
Therefore, for applications ranging from improving team
and arousal (Energy, represented by the Y axis) [3]. The
dynamics to effective learning environments, a requirement of
overall emotional spectrum can be represented by hundred
tapping into each individual’s emotional spectrum in his work
values, which implies x ∈ [−5,5] and y ∈ [−5,5]. Moreover, the
space, and in general cannot be disregarded.
value ranges are distinctly defined for emotional spectrum’s
To quantify this emotional space and imbibe Social and
Happy (x ∈ [−5,0), y ∈ (0,5] i.e. Istquadrant), Angry (x ∈
Emotional Learning (SEL), [3] proposed an Emotional Index
[−5,0), y ∈ (0,5] i.e. IIndquadrant), Sad (x ∈ [−5,0), y ∈ (0,5]
(EI) ruler, commonly referred to as the Mood Meter. It is
i.e. IIIrdquadrant) and Calm (x ∈ [−5,0), y ∈ (0,5] i.e.
based on two psychometric parameters, namely Energy and
IVthquadrant), based on these core values. Refer 1 for values
Pleasantness to determine the emotional status (mood) of an
individual in the emotional space into hundred definite values. assigned to each sub-emotion in every emotional spectrum.
Moreover, these values are distributed in four quadrants each Thus, for example one is feeling Joyful, this implies x = 2 and
emulating four broad emotional patterns namely Angry, y = 2 and similarly, if we consider Enraged x = −5 and y = 5.
Happy, Sad and Calm, thus harboring twenty-five sub- Mood Meter, is a quality tool for SEL, yet it suffers some
emotions in them. In a setup such as classroom or work-group, inherit disadvantages, such as:
the academic performance or work-efficiency, is not just 1) Lacks ability to indicate overall group emotion, to the
dependent on an individual but also to the overall group’s educator/manager.
mood or emotion. [4], [5] supports these claims by indicating 2) Observation of each student needs to be taken manually
that individual temperament’s at different instances add up by the educator if he/she intends recording the group’s
and are the critical influencers that effect the group mood. emotional expression. Also, no absolute reference
Even vital processes like group decision making, are affected system exists for analysis.
by current mood of each individual [6] in the group. Thus, for 3) No inherit systematized record, for student’s emotional
improving work-group’s performance, there is a compelling distribution, leading to improper teaching or supervision
need for a method to be developed for evaluation and analysis method adopted.
of group emotion. In order to solve these problems, an 4) For accessing students input, the educator is required
interactive IoT based application to evaluate group - mood is
proposed in this literature, named Mood Board, which further
extends the domain of Mood Meter.
II. BACKGROUND
Social and Emotional Learning, accounts for developing
social and emotional literacy, which broadly super sets one’s

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 (LCD) is attached which
displays the current most
entry, overall group mood
and entries corresponding
to each emotional
quadrant. The input to the
Mood Board is given
through a Mood Board
App [9] via. Bluetooth. 2
presents the proposed
model of the Mood Board
Tool, designed on
TinkerCAD [10].

B. Evaluation of
Group Dynamics
The group mood value
is calculated using the
vector decomposition of
the data entries existing on
the Mood Board. As, each
Fig. 1: Mood Meter Cartesian Representation data entry on the mood
Adopted from: Copyright 2008 Emotionally Intelligent Schools, LLC. meter is based on two core
parameters, Pleasantness
to access a
standalone
software
application.
Thus, there
is no
hardware
that the
educator can
observe at
glance while
teaching/edu
cating which
can improve
Fi classroom
g. efficiency.
2: To cater to
M the needs
o above, Mood
o Board, an
d IoT tool for
B evaluation of
oa group
rd dynamics
: has been
C developed.
A
D III. MO
M OD
o BO
de AR
l D

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and Energy [3], they can be 1 f
considered as the projections on ) o
the X and Y axis, respectively. i u
Based on these arguments, the = r
0
overall group mood can be �
equivalently understood as the � 3
vector addition of the all the data �
points on the Argand Plane. As, � ×
the summation can be �
equivalently represented as the �
3
addition of all the abscissa and
the ordinate values, it can be = m
represented in an equation form a
as follows: ∑ t
� r
�
� i
X � c
� i e
� s
(
= 2 o
) f
∑ i
= L
X 0
E
where, N = Total Entries and (xi, yi)
i D
are the co-ordinates of the ’
( ithentry. s
A. Introduction ,
The
r
Mood
e
Board
p
is a
r
portab
e
le
s
hardw
e
are
n
tool
t
that
i
extend
n
s
g
Mood
Meter
t
with
h
the
e
enhan
ced
f
ability
o
to
u
calcul
r
ate the
curren
e
t
m
group
o
mood.
t
It
i
consis
o
ts of
978-1-7281-1253-4/19/$31.00 © 2019 IEEE
nal
spectr
ums
of the
Mood
Meter,
which
with
aid of
distinc
t
refere
nce
patter
ns
emula
te the
twent
y-five
sub-
emoti
ons.
Moreo
ver, a
Liquid
Crysta
l
Displa
y

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C. Algorithm respectivel is v ilable at
ic Work y blink a a [9].
Flow alternative Fig. one
ly. An LED minute
example Patterns , the
of this is connec
given in 1) At tion is
6d. If both Powe droppe
XG and YG r-ON, d.
are zero, the Howe
then all Blueto ver, if
quadrants oth a input
Modul is
light up, e is receiv
initiali ed the
indicating zed, current
the an data
Fig. 3:
empty entries
Proposed
Algorithm net- data are
emotional record appen
spectrum is ded.
create 3) Interm
as neutral d and ediate
Moreover, (XG,Y State:
number G) →−
After
(0,0). this,
of entries the
2) Follo
correspon current
wing
ding entry
this, if
to is
a displa
Blueto yed on
each oth
emotional spectrum the
conne LCD
equivalent quadrant is ction
displayed on the LCD. screen
is and
7) A hardware reset option is establi pattern
present, as a button on the shed corres
Mood Board, as shown in with pondin
the CAD Model in 2 (the the g to 4
orange button), pressing Mood is
which the Mood Board Board, displa
comes to the initial state a yed in
and the data record is timer the
emptied. is quadra
initiali nt
D. Technical Details zed. If corres
The current prototype is based no pondin
on Arduino Nano data g to
(ATmega328P), 16 × 2 LCD, stream entere
HC-05 (Bluetooth trans- receiver) is d
and nine LED’s of color’s Red, receiv emotio
Yellow, Blue and Green. The ed n.
schematic layout utilized for from 4) The
prototyping the Mood Board is the Blueto
presented in 5. To input data to Mood oth
Mood Board, an android Board connec
application was developed on app tion is
APP Inventor platform [11], and for droppe
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 d after this, clearing way for which
other devices. The internal E. Application Demonstration
inputs s
interrupt for a new Input (xval, yval) (XG, YG) Quadrant can be u
Bluetooth connection is HYPER (1,4) (1,4) HAPPY given c
enabled. DESOLATE (−3,−5) (−2,−1) SAD from the h
5) If no interrupt observed, PEEVED (−1,1) (−3,0) ANGRY/SAD
Mood
new values of XG and YG are TABLE I: Sequential inputs to Board a
calculated from (1) and (2), Mood Board (top to bottom) App. s
respectively. These s
6) Static State: The quadrant in 6a represents the initial state inputs are c
which the XG and YG lies, the of the Mood Board. Three mathematic h
nine LED’s light up. inputs HYPER, DESOLATE and ally o
However, if (1) or (2) are PEEVED were given to the Mood decomposed o
zero then the quadrants Board sequentially. to evaluate l
which align with YG and For these and s
XG , inputs, their indicate a
corresponding location on EI the n
Ruler, calculated values of XG group’s d
and YG and quadrant in which overall
they belong are shown in the I. mood. This
The intermediate state for the tool is
first entry HYPER is shown in
6b. Static state results of the extremely
Mood Board to DESOLATE and simple to
PEEVED, are shown in 6c and 6d use, thus,
respectively. finding an
rd: Schematic imminent
Layout application
in platforms

(a) Mood
Board at (c) Static
initiation State:
Intermediate DESOLATE
State:
HYPER State:
F PEEVED
i
Fig
g
. 6:
. Mo
od
5 Bo
: ard
Ap
M plic
o atio
o n
De
d mo
nstr
B atio
o n
a
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 work groups to gauge the group [8] http://ei.y
IV. CONCL ale.edu/m
dynamics and thus, improve ood-
USION creativity, learning and overall meter-
Work group’s performance performance. app/
(retrieve
depends on a myriad of factors V. FUTURE d
such as emotional intelligence, SCOPE January
sentiments, moods and emotions 23,
Extended features for pushing 2019)
than just the bounds of adopting
the database entries from the [9] https://g
effective team work-flow oo.gl/kk
Mood Board to a cloud, for a
balancing methods. Moreover, uX7c
comprehensive record-based (retrieve
majorly the overall performance analysis can be constructed in d
accounts on the group’s mood January
future. Moreover, the proposed
remark during different tasks, as 20,
tool is currently in a prototype 2019)
the underpinning to evaluate the
stage and requires further [10] https://w
overall performance. Thus, there is evaluation and testing in ww.tinke
a need for an application that rcad.com
schools/work-groups.
enables quantification and (retrieve
mapping of individual to group d
R January
mood. In this paper, we have E
22,
F
presented a novel IOT based group 2019)
E
mood evaluation tool, that further [11] http://ai2
R
.appinve
extends the domains and reach of E
ntor.mit.
the Social and Emotional N
edu
C
Intelligence Learning. The E
(retrieve
principle of this tool is based on d
S
January
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