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Science
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2
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A
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20
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927
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se
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we
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th
a
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2
.
6
m
e
ters
.
K
ey
w
o
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d
s
:
B
L
E
p
o
s
itio
n
in
g
T
r
ilater
atio
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W
ir
eles
s
p
o
s
itio
n
in
g
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
A
b
d
Sh
u
k
u
r
J
a’
af
ar
C
en
ter
f
o
r
T
elec
o
m
m
u
n
icatio
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R
esear
ch
&
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n
n
o
v
atio
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Facu
lty
o
f
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lectr
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an
d
C
o
m
p
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ter
E
n
g
in
ee
r
in
g
,
Un
iv
e
r
s
iti T
ek
n
ik
al
Ma
lay
s
ia
Me
lak
a
Han
g
T
u
ah
J
ay
a,
7
6
1
0
0
Du
r
ia
n
T
u
n
g
g
al,
Me
lak
a,
Ma
lay
s
ia
E
m
ail: sh
u
k
u
r
@
u
tem
.
ed
u
.
m
y
1.
I
NT
RO
D
UCT
I
O
N
Po
s
itio
n
in
g
s
y
s
tem
h
as
b
ee
n
a
p
ar
t
o
f
p
r
im
ar
y
elem
en
t
in
h
u
m
a
n
d
aily
ac
tiv
ities
to
d
ay
.
T
h
e
d
ev
elo
p
m
e
n
t
o
f
p
o
s
itio
n
in
g
s
y
s
tem
is
o
n
e
o
f
t
h
e
ess
en
tial
f
o
r
th
e
d
e
v
elo
p
m
e
n
t
o
f
civ
ilizatio
n
s
o
f
h
u
m
a
n
as
it
ca
n
b
e
u
s
ed
in
m
an
y
s
ec
to
r
s
lik
e
s
ec
u
r
ity
,
m
ilit
ar
y
,
lo
g
is
ti
cs,
m
o
n
ito
r
in
g
,
tr
ac
k
i
n
g
,
h
ea
l
th
ca
r
e,
s
p
o
r
t,
an
d
en
ter
tain
m
en
t.
GPS
is
a
s
atellite
n
a
v
ig
atio
n
s
y
s
tem
u
s
ed
to
d
eter
m
in
e
th
e
g
r
o
u
n
d
p
o
s
itio
n
o
f
a
n
o
b
ject,
esp
ec
ially
f
o
r
o
u
t
d
o
o
r
en
v
ir
o
n
m
en
t
wh
ile
in
d
o
o
r
p
o
s
itio
n
i
n
g
s
y
s
tem
(
I
PS
)
is
m
o
s
t
c
o
m
m
o
n
u
s
ed
in
in
s
id
e
b
u
ild
in
g
o
r
in
d
o
o
r
en
v
ir
o
n
m
e
n
t.
I
PS
is
d
em
an
d
h
i
g
h
er
ac
c
u
r
ac
y
co
m
p
a
r
e
th
an
GPS.
I
n
d
o
o
r
p
o
s
itio
n
in
g
s
y
s
tem
(
I
PS
)
ca
n
class
if
y
in
to
th
r
ee
m
ajo
r
g
r
o
u
p
s
wh
ich
ar
e
n
et
wo
r
k
-
b
ased
s
y
s
tem
s
,
in
er
tial
s
y
s
tem
s
,
an
d
h
y
b
r
id
s
y
s
tem
s
[
1
]
.
I
PS
is
th
e
s
y
s
tem
th
at
r
ep
lace
GPS
tech
n
o
lo
g
y
to
l
o
ca
te
th
e
p
o
s
itio
n
lo
ca
tio
n
o
f
a
u
s
er
o
r
a
d
ev
ice
in
in
d
o
o
r
en
v
ir
o
n
m
e
n
t
[
2
]
.
Netwo
r
k
b
ased
s
y
s
tem
is
k
n
o
wn
as
a
r
ad
io
f
r
eq
u
e
n
cy
-
b
ased
s
y
s
tem
wh
ic
h
b
u
ild
with
th
e
wir
eless
tech
n
o
lo
g
y
,
u
tili
ze
th
e
wir
eless
s
ig
n
al
to
d
eter
m
in
e
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
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4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
2
,
Au
g
u
s
t
20
21
:
927
-
9
3
7
928
p
o
s
itio
n
s
u
ch
as
wir
eless
-
f
id
e
lity
(
WI
-
FI
)
b
ased
p
o
s
itio
n
in
g
s
y
s
tem
,
B
L
E
b
ea
co
n
s
b
ased
in
d
o
o
r
p
o
s
itio
n
in
g
s
y
s
tem
,
R
FID
in
d
o
o
r
p
o
s
itio
n
in
g
s
y
s
tem
,
an
d
o
th
e
r
wir
eless
tech
n
o
lo
g
y
s
y
s
tem
.
I
n
er
tial
b
ased
s
y
s
tem
is
u
s
e
s
elf
-
co
n
tain
ed
s
en
s
o
r
o
r
in
er
ti
al
s
en
s
o
r
s
to
esti
m
ate
th
e
lo
ca
tio
n
o
f
u
s
er
[
3
]
.
T
h
e
h
y
b
r
i
d
s
y
s
tem
is
th
e
s
y
s
tem
wh
ich
co
m
b
in
e
two
o
r
m
o
r
e
m
eth
o
d
o
r
tec
h
n
iq
u
e
to
m
ea
s
u
r
e
th
e
u
s
er
p
o
s
itio
n
[
4
]
.
T
h
e
s
y
s
tem
u
s
es
s
ev
er
al
d
if
f
er
en
t
wir
eless
co
m
m
u
n
ica
tio
n
tech
n
o
l
o
g
ies
in
o
n
e
s
y
s
tem
to
esti
m
ate
u
s
er
’
s
p
o
s
itio
n
,
s
u
ch
as
h
y
b
r
id
in
d
o
o
r
p
o
s
itio
n
in
g
th
at
em
p
l
o
y
s
b
o
th
W
i
-
Fi an
d
b
lu
eto
o
th
[
5
]
.
B
lu
eto
o
th
l
o
w
en
er
g
y
tech
n
o
lo
g
y
is
a
n
ew
s
tan
d
ar
d
f
o
r
wir
eless
p
er
s
o
n
al
ar
ea
n
etwo
r
k
tech
n
o
lo
g
y
d
ev
elo
p
e
d
b
y
b
lu
eto
o
th
s
p
ec
ia
l
in
ter
est
g
r
o
u
p
(
SIG
)
[
6
]
.
D
u
e
to
th
e
lo
w
c
o
s
t,
lo
w
p
o
wer
co
n
s
u
m
p
tio
n
,
ea
s
y
-
to
-
d
ep
lo
y
s
o
lu
tio
n
an
d
th
e
v
a
s
t
m
ajo
r
ity
o
f
p
o
r
tab
le
d
ev
ice
s
in
t
h
e,
B
L
E
b
ea
co
n
h
as
b
e
en
u
s
ed
f
o
r
in
d
o
o
r
lo
ca
lizatio
n
[
7
]
.
B
L
E
b
ea
co
n
is
lo
w
p
o
wer
co
n
s
u
m
p
tio
n
d
e
v
ice
an
d
its
co
v
er
ag
e
ar
ea
wi
ll
b
ec
o
m
e
s
m
aller
co
m
p
ar
ed
t
o
W
I
-
FI
d
u
e
to
s
h
o
r
t
s
ig
n
al
r
ea
ch
ab
le
d
is
tan
ce
[
8
]
.
T
h
e
b
ea
co
n
s
ca
n
b
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p
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at
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io
u
s
p
lace
s
d
u
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to
its
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m
all
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im
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n
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io
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[
9
]
.
B
L
E
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ea
co
n
o
p
er
ate
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n
2
.
4
G
h
z
f
r
eq
u
e
n
cy
wh
ich
is
s
am
e
with
class
ic
B
lu
eto
o
th
an
d
b
o
th
tech
n
o
lo
g
ies ap
p
ly
s
im
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m
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latio
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s
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em
e
wh
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is
g
au
s
s
ian
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cy
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h
if
t k
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R
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ila
ter
atio
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eth
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ig
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ly
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ely
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el
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e
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itter
also
k
n
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th
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ef
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en
c
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p
o
in
t
[
1
0
]
,
[
1
1
]
.
T
r
ilater
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tech
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iq
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e
is
ap
p
lied
to
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tili
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th
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t
o
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ter
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m
ed
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les
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s
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th
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id
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th
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ex
ac
t
p
o
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[
1
2
]
,
[
1
3
]
.
Dis
tan
ce
th
at
is
ca
lcu
lated
b
y
u
s
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g
p
ath
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s
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el
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lay
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t
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le
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esti
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atin
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th
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er
[
1
4
]
,
[
1
5
]
.
T
h
e
I
PS
u
s
in
g
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tech
n
iq
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e
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ea
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to
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ild
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t
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tem
as
th
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R
S
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tr
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eiv
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[
1
6
]
,
[
1
7
]
.
T
h
e
ac
cu
r
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th
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I
PS
u
s
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g
th
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eth
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e
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e
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co
m
b
in
ed
with
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t
h
er
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ith
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r
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iq
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e
.
Fazli
Su
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h
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t
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g
an
d
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n
[
1
8
]
,
[
1
9
]
.
B
lu
eto
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th
USB
d
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n
g
les
was
u
s
ed
as
f
ix
ed
r
ef
e
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en
ce
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o
d
e
wh
ile
No
k
ia
m
o
b
ile
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e
v
ices w
as u
s
ed
as r
ec
eiv
er
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co
llect
R
SS
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d
ata
[
2
0
]
.
T
h
is
ex
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im
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n
t c
o
llects th
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R
SS
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in
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6
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B
esid
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C
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Pater
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m
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in
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r
p
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g
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y
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[
2
1
]
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h
e
esti
m
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e
r
r
o
r
f
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th
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ir
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s
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M
E
T
H
O
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G
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ased
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n
R
SS
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ata
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tr
ac
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tech
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ig
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d
ev
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ased
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r
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u
r
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r
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Fig
u
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f
p
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s
et
o
f
n
o
d
e
MCU
E
SP
3
2
co
n
n
ec
ted
with
L
o
R
a
n
o
d
e
.
T
h
e
L
o
R
a
n
o
d
e
in
h
er
e
will
r
ec
eiv
e
th
e
R
SS
I
d
ata
th
at
s
en
t
b
y
L
o
R
a
n
o
d
e
f
r
o
m
th
e
u
s
er
.
T
h
en
th
e
n
o
d
e
MCU
E
SP
3
2
at
r
ec
eiv
er
is
co
n
n
ec
te
d
to
th
e
lap
to
p
f
o
r
co
m
m
u
n
icate
wit
h
Py
th
o
n
b
ased
co
d
e
to
co
ll
ec
t
im
p
o
r
tan
ce
p
ar
am
eter
s
u
ch
as
b
lu
eto
o
th
’
s
R
SS
I
an
d
UUI
D.
Fig
u
r
e
3
(
a
)
an
d
3
(
b
)
is
b
ei
n
g
a
s
r
esp
ec
tiv
ely
s
h
o
ws
a
tr
an
s
ce
iv
er
E
SP
3
2
-
L
o
R
A
(
with
3
B
L
E
b
ea
co
n
s
in
ex
p
er
im
e
n
t)
an
d
a
r
ec
eiv
e
r
L
o
R
A
n
o
d
e
co
n
n
ec
ted
t
o
a
lap
to
p
.
(
a)
(
b
)
Fig
u
r
e
3
.
T
h
ese
f
ig
u
r
es a
r
e
;
(
a
)
tr
an
s
ce
iv
er
E
SP
3
2
-
L
o
R
a
with
B
L
E
b
ea
co
n
s
an
d
(
b
)
L
o
R
a
r
ec
eiv
e
r
co
n
n
ec
ted
t
o
a
lap
to
p
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
2
,
Au
g
u
s
t
20
21
:
927
-
9
3
7
930
2.
2
.
Dis
t
a
nce
e
s
t
ima
t
io
n
Af
ter
co
llectin
g
th
e
R
SS
I
,
th
e
d
is
tan
ce
is
est
im
ated
.
Prio
r
to
ca
lcu
latin
g
th
e
d
is
tan
ce
,
two
p
ar
am
eter
s
will
b
e
u
s
ed
in
th
e
lin
ea
r
r
e
g
r
ess
io
n
m
eth
o
d
to
d
ete
r
m
in
e
t
h
e
m
(
g
r
ad
ien
t)
an
d
c
(
in
ter
ce
p
t)
v
alu
es
f
o
r
ea
ch
B
L
E
b
ea
co
n
.
T
h
e
f
ir
s
t
p
ar
a
m
eter
is
th
e
R
S
SI
co
llected
at
ea
ch
r
ef
er
en
ce
p
o
in
t
(
b
lack
d
o
t
)
,
th
e
s
ec
o
n
d
is
th
e
d
is
tan
ce
b
etwe
en
ea
ch
b
e
ac
o
n
an
d
ea
ch
r
ef
er
en
ce
p
o
in
t
(
b
lac
k
d
o
t)
,
wh
ich
is
ca
lcu
lated
u
s
i
n
g
th
e
f
o
r
m
u
la
(
1
)
.
=
√
(
−
)
2
+
(
−
)
2
(
1
)
T
h
e
esti
m
ate
d
is
tan
ce
will
b
e
d
eter
m
in
ed
u
s
in
g
th
e
(
2
)
[
7
]
,
b
u
t
we
co
u
ld
co
n
v
e
r
t
th
is
f
o
r
m
u
la
eq
u
atio
n
to
a
s
lo
p
e
-
in
ter
ce
p
t f
o
r
m
u
la
e
q
u
ati
o
n
in
th
is
s
ec
tio
n
(
3
)
.
=
10
(
(
−
)
(
10
∗
)
⁄
)
(
2
)
l
og
=
1
10
(
(
)
−
(
)
)
(
3
)
All
th
e
p
ar
am
eter
in
f
o
r
m
u
la
(
2
)
will
b
e
s
ep
ar
ate
an
d
it
will
h
av
e
4
p
a
r
am
eter
s
an
d
ea
ch
o
f
th
em
will
co
n
v
er
t
to
th
e
v
a
r
iab
les
an
d
p
ar
am
eter
s
o
f
s
lo
p
e
f
o
r
m
u
la
eq
u
atio
n
[
2
2
]
.
T
h
e
p
a
r
am
eter
s
o
f
1
10
an
d
m
ea
s
u
r
ed
p
o
wer
ar
e
th
e
c
o
n
s
tan
t
v
alu
e,
it
ca
n
b
e
r
ep
lace
d
as
m
(
g
r
a
d
ien
t)
an
d
c
(
in
ter
ce
p
t)
a
n
d
u
s
in
g
s
lo
p
e
eq
u
atio
n
f
o
r
m
u
la
to
f
in
d
th
em
.
R
SS
I
ar
e
th
e
d
ata
th
at
is
co
llec
ted
an
d
lo
g
d
is
tan
ce
is
th
e
es
tim
ate
d
d
is
tan
ce
.
In
(
4
)
as
s
h
o
ws
in
th
e
f
o
r
m
u
la
to
esti
m
ate
th
e
d
is
tan
ce
.
=
(
)
+
(
4
)
2
.
3
.
P
a
rt
icle
f
ilte
r
T
h
er
e
ar
e
f
i
v
e
cr
itical
s
tep
s
in
th
e
p
ar
ticle
f
ilter
in
g
p
r
o
c
ess
wh
ich
ar
e
:
a)
g
en
er
ate
a
b
u
n
ch
o
f
p
ar
ticles,
b
)
p
r
ed
ict
s
tep
,
c)
u
p
d
ate
s
tep
,
d
)
r
esam
p
le,
an
d
e
)
co
m
p
u
te
esti
m
ate.
Step
b
til
l
s
tep
e
o
f
p
ar
ticle
f
ilter
will
r
u
n
in
lo
o
p
wh
i
ch
c
o
n
v
er
g
e
as
n
ea
r
as
p
o
s
s
ib
le
to
th
e
tr
u
e
tar
g
et
s
tate
b
y
iter
a
tiv
ely
s
am
p
lin
g
th
e
p
ar
ticles with
th
e
co
n
tr
ac
ted
s
ea
r
ch
s
co
p
e
[
2
3
]
,
[
2
4
]
.
a)
Gen
er
ate
a
b
u
n
ch
o
f
p
ar
ticles
E
ac
h
p
a
r
ticle
h
as
an
ass
o
ciate
d
weig
h
t
t
h
at
r
e
p
r
esen
ts
th
e
p
r
o
b
ab
ilit
y
o
f
t
h
at
p
a
r
tic
le
b
ein
g
th
e
tr
u
e
p
o
s
itio
n
o
f
th
e
u
s
er
.
C
r
ea
te
a
c
o
llectio
n
o
f
p
ar
ticles u
s
in
g
th
i
s
eq
u
atio
n
{
}
=
1
an
d
s
et
th
e
weig
h
t
f
o
r
ea
ch
p
ar
ticle
to
1
.
b)
Pre
d
ict
s
tep
No
is
e
m
u
s
t
b
e
ad
d
e
d
t
o
th
e
p
ar
ticle'
s
m
o
v
em
en
ts
in
o
r
d
e
r
to
h
av
e
r
ea
s
o
n
a
b
le
ch
a
n
ce
o
f
p
r
e
d
ictin
g
th
e
u
s
er
'
s
ac
tu
al
p
o
s
itio
n
.
W
ith
o
u
t
s
y
s
tem
m
o
d
el
u
n
ce
r
tain
ty
,
t
h
e
p
ar
ticle
f
ilter
will
f
ail
to
a
cc
u
r
ately
m
o
d
el
th
e
p
r
o
b
ab
ilit
y
d
is
tr
ib
u
tio
n
o
f
o
u
r
b
elief
ab
o
u
t th
e
u
s
er
'
s
p
o
s
itio
n
.
c)
Up
d
ate
s
tep
T
h
e
p
r
o
b
a
b
ilit
y
th
at
ass
ig
n
ed
to
ea
ch
p
o
s
itio
n
is
c
alled
as
p
r
io
r
(
c
u
r
r
e
n
t
p
r
o
b
a
b
ilit
y
o
f
th
i
s
p
o
s
itio
n
b
ei
n
g
th
e
tr
u
e
p
o
s
itio
n
)
,
b
u
t
wh
en
a
n
ew
R
SS
I
s
’
m
ea
s
u
r
em
en
t
is
c
o
m
in
g
i
n
,
th
e
p
r
i
o
r
n
ee
d
t
o
m
u
ltip
ly
with
th
e
lik
elih
o
o
d
(
p
r
o
b
ab
ilit
y
o
f
th
e
m
ea
s
u
r
ed
d
is
tan
ce
b
ein
g
s
am
e
as th
e
d
is
tan
ce
o
f
p
a
r
ticle
to
t
h
e
b
ea
co
n
)
:
Poste
r
ior
=
l
ik
e
l
ihood
×
pr
io
r
n
or
m
a
l
iza
tion
P
(
x
|
z
)
=
P
(
z
|
x
)
×
P
(
x
)
P
(
z
)
(
5
)
E
ac
h
p
ar
ticle
h
as
p
o
s
itio
n
a
n
d
weig
h
t
wh
ich
ass
ess
e
s
h
o
w
well
it
m
atch
es
th
e
m
ea
s
u
r
em
en
t.
Nex
t,
n
o
r
m
alizin
g
th
e
weig
h
ts
to
let
it
s
u
m
u
p
t
o
o
n
e
an
d
tu
r
n
t
h
em
in
to
a
p
r
o
b
ab
ilit
y
d
is
t
r
ib
u
tio
n
wh
er
e
th
e
p
ar
ticles
th
at
clo
s
est
to
th
e
tr
u
e
p
o
s
itio
n
n
o
r
m
ally
will
h
av
e
a
h
ig
h
er
weig
h
t
co
m
p
ar
ed
to
t
h
e
p
ar
ticles
f
ar
f
r
o
m
th
e
tr
u
e
p
o
s
itio
n
.
d)
R
esam
p
le
Par
ticles
with
ex
tr
em
ely
lo
w
p
r
o
b
ab
ilit
y
will
b
e
d
is
ca
r
d
e
d
an
d
r
ep
lace
th
em
with
n
e
w
p
ar
ticles
with
h
ig
h
er
p
r
o
b
ab
ilit
y
.
I
f
n
o
n
ew
m
ea
s
u
r
em
en
ts
ar
e
r
ec
eiv
ed
d
u
r
in
g
o
n
e
o
f
th
e
ep
o
ch
s
,
it
is
d
eter
m
in
ed
wh
en
to
r
esam
p
le
b
y
ca
lcu
latin
g
w
h
at
m
an
y
r
ef
e
r
to
as
th
e
ef
f
e
ctiv
e
N,
wh
ich
ap
p
r
o
x
im
ates
th
e
n
u
m
b
er
o
f
p
ar
ticles th
at
tr
u
ly
co
n
tr
ib
u
te
t
o
th
e
p
r
o
b
ab
ilit
y
d
is
tr
ib
u
tio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
I
n
d
o
o
r
p
o
s
itio
n
in
g
u
tili
z
in
g
b
l
u
eto
o
th
lo
w
en
erg
y
R
S
S
I
o
n
L
o
R
a
s
ystem
(
K
a
ve
th
a
S
u
s
ee
n
th
ir
a
n
)
931
e)
C
o
m
p
u
te
esti
m
ate
T
h
e
m
ea
n
o
f
th
e
esti
m
ate
as
t
h
e
s
u
m
o
f
th
e
weig
h
ted
v
alu
e
s
o
f
th
e
5
0
0
0
p
a
r
ticles
will
b
e
ca
lcu
lated
.
T
h
e
eq
u
atio
n
f
o
r
th
is
is
:
μ
=
1
N
∑
w
i
x
i
N
1
=
1
(
6
)
T
h
e
is
r
ep
r
esen
t th
e
ℎ
n
u
m
b
er
o
f
p
ar
ticles.
2
.
4
.
T
rila
t
er
a
t
io
n
T
h
er
e
ar
e
two
in
f
o
r
m
atio
n
t
h
at
n
ec
ess
ar
y
to
b
e
u
s
ed
,
f
ir
s
t
is
p
o
s
itio
n
o
f
B
L
E
b
ea
co
n
s
(
co
o
r
d
in
ates
p
o
in
t)
an
d
th
e
esti
m
ate
d
is
tan
ce
s
.
T
h
e
esti
m
ate
d
is
tan
ce
s
h
er
e
ar
e
ca
lcu
late
d
b
y
u
s
in
g
f
o
r
m
u
la
(4
)
with
co
llected
R
SS
I
.
Nex
t,
b
o
th
d
at
a
will b
e
u
s
ed
in
tr
ilater
atio
n
t
o
esti
m
ate
th
e
p
o
s
itio
n
f
o
r
u
s
e
r
[
2
5
]
.
T
r
ilater
atio
n
f
o
r
m
u
la
e
q
u
atio
n
is
ca
lcu
late
d
in
m
atr
ix
f
o
r
m
an
d
tr
ilater
a
tio
n
alg
o
r
ith
m
is
ex
p
r
ess
ed
b
y
th
e
f
o
llo
win
g
(
7
)
an
d
(
8
)
:
=
[
−
2
(
1
−
)
−
2
(
1
−
)
⋮
⋮
⋮
⋮
−
2
(
−
1
−
)
−
2
(
−
1
−
)
]
,
=
[
]
,
(
7
)
=
[
(
1
2
−
2
)
−
(
1
2
−
2
)
−
(
1
2
−
2
)
(
2
2
−
2
)
−
(
2
2
−
2
)
−
(
2
2
−
2
)
⋮
⋮
(
−
1
2
−
2
)
−
(
−
1
2
−
2
)
−
(
−
1
2
−
2
)
]
(
8
)
T
h
e
v
ar
iab
les
x
a
n
d
y
s
h
o
wn
in
th
e
alg
o
r
it
h
m
ab
o
v
e
r
ep
r
esen
ts
th
e
p
o
s
itio
n
o
f
e
ac
h
b
ea
co
n
(
co
o
r
d
i
n
ate
p
o
in
t
v
al
u
e)
a
n
d
t
h
e
d
ar
e
r
e
p
r
esen
tin
g
th
e
esti
m
ate
d
is
tan
ce
th
at
is
ca
lcu
late
d
u
s
in
g
(
4
)
.
T
h
u
s
,
th
e
esti
m
ated
p
o
s
itio
n
co
o
r
d
in
ate
o
f
u
s
er
s
ca
n
b
e
s
o
lv
ed
u
s
in
g
(
9
)
:
=
−
1
(
9
)
Af
ter
esti
m
atin
g
p
o
s
itio
n
s
with
an
d
with
o
u
t
th
e
p
ar
ticle
f
i
lter
,
th
e
d
if
f
er
en
ce
o
f
d
is
tan
ce
b
etwe
en
th
ese
esti
m
ated
p
o
s
itio
n
an
d
ac
tu
al
p
o
s
itio
n
will
b
e
ca
lcu
lated
.
T
h
e
d
if
f
e
r
en
ce
o
f
th
e
d
i
s
tan
ce
is
ca
lled
as
er
r
o
r
wh
ic
h
will b
e
u
s
ed
to
ca
lcu
late
th
e
r
o
o
t
m
ea
n
s
q
u
a
r
e
er
r
o
r
(
R
MSE
)
b
y
u
s
in
g
th
e
(
1
0
)
:
R
M
SE
=
√
∑
(
(
x
−
x
̃
)
2
−
(
y
−
y
̃
)
2
)
n
n
i
=
1
(
1
0
)
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
E
x
plo
ring
cha
ra
ct
er
is
t
i
cs o
f
B
L
E
bea
co
n
T
h
er
e
ar
e
3
ty
p
e
s
o
f
B
L
E
b
ea
co
n
s
in
itially
th
at
h
a
s
b
ee
n
s
elec
ted
to
u
s
e
in
th
is
s
y
s
tem
.
A
m
o
n
g
th
em
ar
e
Ap
r
il
b
ea
co
n
s
en
s
o
r
N0
1
,
b
lu
eto
o
th
B
L
E
b
ea
co
n
E
E
K
-
N,
B
L
E
m
icr
o
co
n
tr
o
ller
N
R
F5
2
8
1
0
wh
er
e
all
th
ese
ar
e
B
L
E
b
ea
c
o
n
s
.
T
h
e
s
en
s
itiv
ity
o
f
B
L
E
b
ea
co
n
in
d
o
o
r
p
o
s
itio
n
in
g
h
as
a
m
ajo
r
e
f
f
ec
t
o
n
p
o
s
itio
n
in
g
ac
cu
r
ac
y
.
T
h
e
r
ef
o
r
e,
an
in
v
est
ig
atio
n
is
n
ee
d
ed
to
k
n
o
w
t
h
e
f
ea
tu
r
es a
n
d
ch
ar
ac
te
r
is
tics
o
f
th
ese
B
L
E
b
ea
co
n
s
wh
ich
ar
e
m
o
r
e
s
u
itab
le
ap
p
l
y
in
in
d
o
o
r
p
o
s
itio
n
in
g
s
y
s
tem
.
T
h
e
R
SS
I
th
at
is
tr
an
s
m
itt
ed
b
y
ea
ch
o
f
th
ese
B
L
E
b
ea
co
n
s
will
b
e
co
llecte
d
in
ev
e
r
y
d
if
f
er
e
n
t
p
h
y
s
ical
d
is
tan
ce
.
T
h
e
s
am
p
lin
g
ex
p
er
i
m
en
t
is
o
n
e
v
er
y
1
m
eter
in
th
e
lo
ca
tio
n
en
v
i
r
o
n
m
en
t
[
0
-
1
5
m
]
will
b
e
ca
r
r
ied
o
u
t
an
d
c
o
llect
1
m
in
u
te
f
o
r
e
ac
h
p
o
in
t
in
lin
e
o
f
s
ig
h
t (
L
OS)
co
n
d
itio
n
.
Fro
m
th
e
Fig
u
r
e
4
ab
o
v
e,
it
is
k
n
o
wn
t
h
at
B
L
E
B
ea
co
n
E
E
K
-
N
an
d
Ap
r
il
b
ea
co
n
s
en
s
o
r
N0
1
h
av
e
b
etter
p
er
f
o
r
m
a
n
ce
th
a
n
B
L
E
m
icr
o
co
n
tr
o
ller
NR
F5
2
8
1
0
.
T
h
is
is
b
ec
a
u
s
e
th
e
R
SS
I
f
r
o
m
B
L
E
m
icr
o
co
n
tr
o
ller
NR
F5
2
8
1
0
e
x
tr
em
ely
u
n
s
tab
le
a
n
d
f
lu
ctu
atio
n
to
d
is
tan
ce
m
ea
s
u
r
ed
,
h
en
c
e
ef
f
ec
t
to
lo
we
r
p
o
s
itio
n
in
g
ac
cu
r
ac
y
.
T
h
u
s
,
it
is
d
ec
id
ed
to
u
s
e
b
l
u
eto
o
th
B
L
E
b
ea
co
n
E
E
K
-
N
in
th
is
p
o
s
iti
o
n
in
g
e
x
p
er
im
e
n
t
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
2
,
Au
g
u
s
t
20
21
:
927
-
9
3
7
932
Fig
u
r
e
4.
R
SS
I
in
ten
s
ity
v
er
s
u
s
d
is
tan
ce
f
o
r
3
d
if
f
er
e
n
t BLE
b
ea
co
n
s
3.
2
.
T
esting
s
ce
na
rio
f
o
r
t
he
s
y
s
t
em
T
h
e
s
y
s
tem
is
ev
alu
ated
f
o
r
ac
cu
r
ac
y
in
a
v
ar
iety
o
f
d
i
f
f
er
en
t
s
ized
en
v
ir
o
n
m
en
ts
an
d
d
if
f
er
en
t
alg
o
r
ith
m
s
.
B
ased
o
n
p
r
ev
io
u
s
Fig
u
r
e
4
,
th
e
m
ax
im
u
m
s
ig
n
al
s
tr
en
g
th
d
is
tan
ce
th
at
ca
n
b
e
co
n
s
id
er
ed
f
r
o
m
b
ea
co
n
to
u
s
er
will
b
e
1
5
m
eter
s
.
Mo
r
e
th
an
th
at,
s
ig
n
al
is
to
o
wea
k
an
d
ca
n
n
o
t
b
e
c
o
n
s
id
er
ed
in
p
o
s
itio
n
in
g
.
Fro
m
th
is
,
two
s
ce
n
ar
io
s
ar
e
co
n
s
id
er
ed
with
m
ax
im
u
m
d
is
tan
ce
allo
w
an
d
h
alf
o
f
th
e
m
a
x
im
u
m
d
is
tan
ce
.
All
th
ese
two
s
ce
n
ar
io
s
wer
e
co
n
d
u
cted
in
B
B
NE
T
lab
:
−
Scen
ar
io
1
:
i
n
th
is
s
ce
n
ar
i
o
,
u
s
er
will
s
tan
d
at
f
ix
e
d
p
o
s
itio
n
(
co
o
r
d
in
ate
p
o
in
t:
(
4
,
4
)
)
in
2
d
if
f
er
e
n
ce
s
ize
ar
ea
en
v
ir
o
n
m
en
ts
in
B
B
NE
T
lab
wh
ich
ar
e
7
.
5
m
x
8
m
a
n
d
1
5
m
x
8
m
.
Fo
u
r
B
L
E
b
ea
co
n
s
will
b
e
u
s
ed
an
d
d
ep
lo
y
at
t
h
e
s
am
e
p
o
s
itio
n
o
n
ea
c
h
c
o
r
n
e
r
o
f
th
e
ar
ea
.
T
h
e
o
u
tp
u
t
r
esu
lt
f
r
o
m
th
ese
2
d
if
f
er
en
ce
s
ize
ar
ea
s
will b
e
co
m
p
ar
ed
.
−
Scen
ar
io
2
: 1
5
m
x
8
m
le
n
g
th
ar
ea
in
B
B
NE
T
lab
with
6
b
e
ac
o
n
s
u
s
ed
in
th
is
s
ce
n
ar
io
.
T
h
er
e
ar
e
1
0
f
ix
ed
o
u
tp
u
t
p
o
s
itio
n
r
esu
lt
o
f
th
e
u
s
er
ar
o
u
n
d
th
e
a
r
ea
will
b
e
ta
k
en
a
n
d
all
er
r
o
r
will
b
e
p
r
esen
ted
in
C
DF
f
o
r
b
etter
in
ter
p
r
etatio
n
.
3
.
2
.
1
.
Scena
rio
1
I
n
e
x
p
er
im
en
t
1
r
ef
e
r
r
in
g
to
Fig
u
r
e
5
,
it
is
t
o
o
b
s
er
v
e
th
e
ef
f
ec
t
o
f
d
if
f
e
r
en
ce
s
ize
o
f
ar
ea
to
th
e
ac
cu
r
ac
y
o
f
th
e
s
y
s
tem
.
On
ly
4
B
L
E
b
ea
co
n
s
is
u
s
ed
in
th
is
ex
p
er
im
en
t.
D
u
e
to
m
ax
im
u
m
d
is
tan
ce
v
s
s
ig
n
al
s
tr
en
g
th
m
ea
s
u
r
e
in
Fig
u
r
e
4
is
1
5
m
eter
s
,
two
d
if
f
er
en
t
s
ize
len
g
th
will
b
e
ap
p
lied
h
er
e.
T
h
e
f
ir
s
t
len
g
th
is
m
ax
im
u
m
ca
p
ab
le
d
is
tan
ce
1
5
m
b
y
t
h
e
b
ea
co
n
an
d
h
alf
o
f
t
h
e
m
ax
im
u
m
wh
ich
is
7
.
5
m
l
en
g
th
ch
o
s
en
.
Fig
u
r
e
5.
E
x
p
er
im
e
n
t
s
ce
n
ar
io
1
with
7
.
8
m
an
d
1
5
m
len
g
th
B
ased
o
n
b
l
u
eto
o
th
R
SS
I
d
ata
co
llectio
n
,
two
k
i
n
d
o
f
lo
c
atio
n
esti
m
atio
n
alg
o
r
ith
m
ap
p
lied
.
T
h
e
f
ir
s
t
o
n
e
is
with
p
a
r
ticle
f
ilter
im
p
lem
en
tatio
n
a
n
d
s
ec
o
n
d
w
ith
o
u
t
p
ar
ticle
f
ilter
(
b
asic
tr
il
ater
atio
n
)
.
Fig
u
r
e
6
d
ep
icts
d
is
tr
ib
u
tio
n
o
f
b
o
th
a
lg
o
r
ith
m
in
B
B
NeT
lab
f
o
r
len
g
th
ch
o
s
en
7
.
5
m
wh
ile
Fig
u
r
e
7
s
h
o
ws
th
e
lo
ca
tio
n
esti
m
atio
n
f
o
r
len
g
th
1
5
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
I
n
d
o
o
r
p
o
s
itio
n
in
g
u
tili
z
in
g
b
l
u
eto
o
th
lo
w
en
erg
y
R
S
S
I
o
n
L
o
R
a
s
ystem
(
K
a
ve
th
a
S
u
s
ee
n
th
ir
a
n
)
933
Fig
u
r
e
6
.
E
s
tim
atio
n
o
f
u
s
er
p
o
s
itio
n
d
is
tr
ib
u
tio
n
with
an
d
with
o
u
t
p
ar
ticle
f
ilter
in
ar
ea
7
.
5
m
x
8
m
an
d
1
5
m
x
8
m
Fig
u
r
e
7
.
E
s
tim
atio
n
o
f
u
s
er
p
o
s
itio
n
d
is
tr
ib
u
tio
n
with
an
d
with
o
u
t
p
ar
ticle
f
ilter
in
ar
ea
1
5
m
x
8
m
I
n
ad
d
itio
n
,
T
ab
le
1
as
s
h
o
wn
in
d
ep
icts
th
e
u
s
er
ac
tu
al
p
o
s
itio
n
,
esti
m
ated
p
o
s
itio
n
o
f
th
e
u
s
er
with
an
d
with
o
u
t
th
e
p
a
r
ticle
f
ilter
an
d
t
h
e
r
o
o
t
m
ea
n
s
q
u
ar
e
e
r
r
o
r
(
R
MSE
)
b
ased
o
n
l
o
ca
tio
n
esti
m
atio
n
d
is
tr
ib
u
tio
n
in
Fig
u
r
e
7
an
d
Fi
g
u
r
e
8
.
Acc
o
r
d
in
g
to
t
h
e
lo
ca
ti
o
n
er
r
o
r
R
MSE
,
it
is
o
b
s
er
v
ed
th
at
th
e
m
ax
im
u
m
len
g
th
d
is
tan
ce
1
5
m
g
i
v
e
lo
w
er
ac
cu
r
a
cy
c
o
m
p
a
r
ed
to
le
n
g
t
h
ar
ea
o
f
7
.
5
m
f
o
r
b
o
t
h
with
a
n
d
with
o
u
t p
ar
ticle
f
ilter
im
p
lem
en
tatio
n
.
T
h
is
is
b
ec
au
s
e
th
e
ef
f
ec
tiv
e
co
v
er
a
g
e
r
an
g
e
o
f
B
L
E
b
ea
co
n
s
is
ap
p
r
o
x
im
ately
7
.
5
m
,
th
er
ef
o
r
e
t
h
e
R
SS
I
th
at
is
tr
an
s
m
itted
b
y
B
L
E
b
ea
co
n
s
will
atten
u
ate
with
th
e
in
cr
e
ase
o
f
th
e
d
is
tan
ce
b
etwe
en
tr
an
s
m
itter
(
B
L
E
b
ea
co
n
s
)
an
d
r
ec
eiv
er
(
E
SP
3
2
)
.
B
esid
es
th
at,
d
u
e
to
B
B
NE
T
l
ab
en
v
ir
o
n
m
en
t
f
u
ll
o
f
co
m
p
u
ter
,
o
b
s
tacle
s
,
an
d
f
u
r
n
itu
r
e
ca
u
s
e
th
e
p
r
o
p
ag
atio
n
o
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ig
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a
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itio
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ize
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r
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ea
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ize
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s
tim
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itio
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t p
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Est
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d
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R
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S
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u
r
e
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s
itio
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s
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m
e
n
t o
n
o
v
er
all
lo
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tio
n
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er
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o
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m
an
ce
in
B
B
NeT
lab
3
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2
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2
.
Scena
rio
2
T
h
e
r
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lts
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in
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i
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lt
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x
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m
d
is
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ce
b
etwe
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ea
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n
d
th
e
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s
er
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T
h
e
a
r
e
a
len
g
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t
h
e
lab
is
1
5
m
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s
o
in
th
is
ca
s
e
3
b
ea
co
n
s
n
e
ed
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e
l
o
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ted
to
m
ain
tain
d
is
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ce
g
a
p
o
f
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5
m
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I
n
th
is
ca
s
e,
to
tal
o
f
6
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ea
c
o
n
s
n
ee
d
to
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e
d
ep
l
o
y
ed
to
co
v
er
th
e
a
r
ea
o
f
15
m
x
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in
B
B
NeT
lab
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I
n
th
is
s
ce
n
ar
io
,
th
e
u
s
er
s
tan
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at
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o
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itio
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2
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tes
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o
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n
d
t
h
e
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ar
ea
as
d
ep
ict
ed
in
Fig
u
r
e
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.
T
ab
le
2
d
ep
icts
th
e
R
MSE
r
esu
lt
f
r
o
m
tr
ilater
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d
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ticle
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ilter
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eth
o
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o
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itio
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Acc
o
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tab
le,
m
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s
h
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ar
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ea
co
n
s
co
m
p
ar
ed
t
o
ju
s
t 4
b
e
ac
o
n
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
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J
E
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g
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2
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g
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t
20
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2
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ser
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e
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l
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ased
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p
o
s
itio
n
in
g
er
r
o
r
f
r
o
m
s
ce
n
ar
io
s
ab
o
v
e,
c
o
m
p
ar
is
o
n
h
av
e
b
ee
n
m
ad
e
with
two
alg
o
r
ith
m
s
,
tr
ilater
atio
n
a
n
d
p
ar
ticle
f
ilter
,
with
4
b
ea
co
n
s
an
d
6
b
ea
co
n
s
r
esp
ec
tiv
ely
in
th
e
cu
m
u
lativ
e
d
is
tr
ib
u
tio
n
f
u
n
ctio
n
(
C
DF)
.
Fro
m
Fig
u
r
e
9
s
h
o
ws
th
at
th
e
est
im
ated
p
o
s
itio
n
o
f
th
e
u
s
er
with
th
e
p
ar
ticle
f
ilter
h
as
les
s
er
r
o
r
b
y
r
ely
o
n
6
b
ea
co
n
s
co
m
p
a
r
e
to
4
b
e
ac
o
n
s
.
B
esid
es,
im
p
lem
en
tin
g
p
ar
ticle
f
ilter
g
iv
e
s
ig
n
if
ican
t
im
p
r
o
v
em
e
n
t
to
tr
i
later
atio
n
tech
n
i
q
u
e.
T
h
e
p
ar
ti
cle
f
ilter
m
et
h
o
d
with
6
b
ea
co
n
s
ac
h
iev
es
a
9
0
%
o
f
co
n
f
id
en
t
p
r
o
b
a
b
ilit
y
o
f
lo
ca
tio
n
er
r
o
r
with
in
2
.
6
m
eter
s
wh
ile
b
asic
tr
ilater
atio
n
g
iv
es
co
n
f
id
en
t
o
f
6
.
4
m
eter
s
(
6
b
ea
co
n
s
)
.
Ov
er
all
p
ar
ticle
f
ilter
g
iv
es
4
4
.
4
4
%
im
p
r
o
v
em
e
n
t
o
v
er
th
e
tr
ilater
ati
o
n
m
eth
o
d
(
6
.
4
m
)
.
B
y
r
ely
in
g
o
n
6
b
ea
co
n
s
with
7
.
5
m
ap
a
r
ts
,
th
e
im
p
r
o
v
e
m
en
t
o
f
C
DF
is
4
7
.
1
7
%
co
m
p
ar
ed
to
ju
s
t
u
s
e
4
b
ea
co
n
s
with
1
5
m
ap
a
r
ts
.
Fig
u
r
e
9.
C
DF f
o
r
with
a
n
d
wi
th
o
u
t p
ar
ticle
f
ilter
4.
CO
NCLU
SI
O
N
B
ased
o
n
th
e
p
r
o
ject
ca
r
r
ied
o
u
t,
an
in
d
o
o
r
p
o
s
itio
n
in
g
s
y
s
tem
h
as
b
ee
n
s
u
cc
ess
f
u
lly
d
e
v
elo
p
ed
t
o
esti
m
ate
u
s
er
p
o
s
itio
n
u
tili
zin
g
R
SS
I
th
at
tr
an
s
m
itted
f
r
o
m
th
e
B
L
E
b
ea
co
n
s
wh
ich
d
ep
lo
y
ed
in
B
B
NeT
lab
.
A
tr
an
s
ce
iv
er
with
E
SP
3
2
is
s
u
cc
ess
f
u
lly
d
ev
elo
p
ed
wh
ich
co
llect
th
e
B
lu
eto
o
th
R
SS
I
an
d
tr
an
s
m
it
th
r
o
u
g
h
L
o
R
a
to
an
o
th
er
L
o
R
a
r
ec
ei
v
er
.
L
o
ca
tio
n
esti
m
atio
n
alg
o
r
ith
m
u
tili
zin
g
R
SS
I
d
ata
f
r
o
m
B
L
E
b
ea
co
n
s
s
u
cc
ess
f
u
lly
d
e
s
ig
n
ed
b
ased
o
n
tr
ilater
atio
n
an
d
p
a
r
ticle
f
ilter
im
p
lem
en
tatio
n
.
B
ased
o
n
R
MSE
r
esu
lt
s
,
h
alf
o
f
th
e
m
a
x
im
u
m
d
is
tan
ce
g
i
v
e
b
etter
p
o
s
itio
n
in
g
ac
c
u
r
ac
y
co
m
p
a
r
ed
to
m
ax
im
u
m
d
is
tan
ce
allo
w
b
y
t
h
e
b
ea
co
n
its
elf
.
B
ased
o
n
th
is
,
a
s
im
p
le
g
u
id
elin
e
ca
n
b
e
tak
e
n
in
s
tr
ateg
y
to
d
ep
lo
y
e
d
b
ea
co
n
in
B
B
NeT
lab
.
Fin
ally
,
th
e
p
o
s
itio
n
in
g
alg
o
r
ith
m
ac
cu
r
ac
y
in
ter
m
o
f
R
MSE
an
d
C
DF
h
av
e
b
ee
n
elab
o
r
ated
wh
er
e
th
e
p
o
s
itio
n
in
g
al
g
o
r
ith
m
with
im
p
lem
en
tatio
n
o
f
p
ar
ticle
f
ilter
g
iv
e
ac
cu
r
ac
y
o
f
er
r
o
r
less
th
a
n
2
.
6
m
f
o
r
9
0
%
o
f
th
e
tim
e
with
im
p
r
o
v
em
e
n
t
o
f
4
4
.
4
4
%
th
an
ju
s
t
b
asic
tr
ilater
atio
n
.
Par
ticle
f
ilter
with
6
b
ea
co
n
s
also
s
h
o
w
s
ig
n
if
ican
t
im
p
r
o
v
em
en
t
b
y
4
7
.
1
7
%
co
m
p
ar
ed
to
ju
s
t
4
b
e
ac
o
n
s
.
Fu
tu
r
e
d
ev
elo
p
m
en
t
o
f
th
is
p
r
o
ject
ca
n
b
e
in
teg
r
ated
with
I
o
T
p
latf
o
r
m
a
s
p
ar
t o
f
to
s
u
p
p
o
r
t th
e
lo
ca
tio
n
-
b
ased
s
er
v
ices (
L
B
S).
ACK
NO
WL
E
DG
E
M
E
NT
S
T
h
e
au
th
o
r
s
wo
u
ld
lik
e
to
th
a
n
k
th
e
Un
i
v
er
s
iti
T
ek
n
ik
al
Ma
lay
s
ia
Me
lak
a
(
UT
eM
)
,
UT
e
M
Z
am
alah
Sch
em
e
f
o
r
s
p
o
n
s
o
r
in
g
th
is
r
e
s
ea
r
ch
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
I
n
d
o
o
r
p
o
s
itio
n
in
g
u
tili
z
in
g
b
l
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eto
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th
lo
w
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erg
y
R
S
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o
n
L
o
R
a
s
ystem
(
K
a
ve
th
a
S
u
s
ee
n
th
ir
a
n
)
935
RE
F
E
R
E
NC
E
S
[
1
]
A
.
A
.
K
a
l
b
a
n
d
h
e
a
n
d
S
.
C
.
P
a
t
i
l
,
"
I
n
d
o
o
r
P
o
s
i
t
i
o
n
i
n
g
S
y
s
t
e
m
u
s
i
n
g
B
l
u
e
t
o
o
t
h
L
o
w
E
n
e
r
g
y
,
"
2
0
1
6
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
C
o
m
p
u
t
i
n
g
,
A
n
a
l
y
t
i
c
s
a
n
d
S
e
c
u
r
i
t
y
T
r
e
n
d
s
(
C
A
S
T
)
,
C
o
l
l
e
g
e
o
f
E
n
g
i
n
e
e
r
i
n
g
P
u
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e
,
I
n
d
i
a
,
2
0
1
6
,
p
p
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4
5
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4
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o
i
:
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0
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1
1
0
9
/
C
A
S
T
.
2
0
1
6
.
7
9
1
5
0
1
1
.
[2
]
N.
P
o
d
e
v
ij
n
,
e
t
a
l
.
,
"
P
e
rfo
rm
a
n
c
e
Co
m
p
a
riso
n
o
f
RS
S
Alg
o
r
it
h
m
s
fo
r
I
n
d
o
o
r
L
o
c
a
li
z
a
ti
o
n
i
n
Larg
e
Op
e
n
En
v
ir
o
n
m
e
n
ts,
"
2
0
1
8
I
n
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
In
d
o
o
r
P
o
siti
o
n
in
g
a
n
d
In
d
o
o
r
N
a
v
ig
a
ti
o
n
(IP
IN)
,
2
0
1
8
,
p
p
.
1
-
6
,
d
o
i:
1
0
.
1
1
0
9
/IP
IN.
2
0
1
8
.
8
5
3
3
6
9
5
.
[3
]
K.
Ech
ize
n
n
y
a
a
n
d
K.
Ko
n
d
o
,
"
E
stim
a
ti
o
n
o
f
in
d
o
o
r
p
o
siti
o
n
a
n
d
m
o
ti
o
n
d
irec
ti
o
n
f
o
r
sm
a
rtp
h
o
n
e
s
u
sin
g
DN
N
to
BLE
b
e
a
c
o
n
si
g
n
a
l
stre
n
g
th
,
"
2
0
2
0
IE
EE
I
n
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
Co
n
su
me
r
El
e
c
tro
n
ics
-
T
a
iwa
n
(ICCE
-
T
a
iwa
n
)
,
2
0
2
0
,
p
p
.
1
-
2
,
d
o
i:
1
0
.
1
1
0
9
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-
Taiwa
n
4
9
8
3
8
.
2
0
2
0
.
9
2
5
8
2
8
2
.
[4
]
D.
G
io
v
a
n
e
ll
i,
E.
F
a
re
ll
a
,
D.
F
o
n
t
a
n
e
ll
i
,
a
n
d
D.
M
a
c
ii
,
"
B
lu
e
to
o
t
h
-
Ba
se
d
In
d
o
o
r
P
o
sit
io
n
in
g
Th
r
o
u
g
h
To
F
a
n
d
RS
S
I
Da
ta
F
u
sio
n
,
"
2
0
1
8
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
I
n
d
o
o
r
Po
si
ti
o
n
i
n
g
a
n
d
In
d
o
o
r
N
a
v
ig
a
ti
o
n
(IP
IN)
,
2
0
1
8
,
p
p
.
1
-
8
,
d
o
i:
1
0
.
1
1
0
9
/IP
IN.
2
0
1
8
.
8
5
3
3
8
5
3
.
[5
]
P
.
Ba
rso
c
c
h
i,
A.
Criv
e
ll
o
,
M
.
G
iro
lam
i,
F
.
M
a
v
il
ia
,
a
n
d
F
.
P
a
lu
m
b
o
,
"
Oc
c
u
p
a
n
c
y
d
e
tec
ti
o
n
b
y
m
u
lt
i
-
p
o
we
r
b
lu
e
t
o
o
t
h
lo
w
e
n
e
r
g
y
b
e
a
c
o
n
in
g
,
"
2
0
1
7
I
n
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
In
d
o
o
r
Po
si
ti
o
n
in
g
a
n
d
I
n
d
o
o
r
Na
v
i
g
a
ti
o
n
(IP
IN)
,
2
0
1
7
,
p
p
.
1
-
6
,
d
o
i
:
1
0
.
1
1
0
9
/IP
IN.
2
0
1
7
.
8
1
1
5
9
4
6
.
[6
]
G
.
P
ip
e
li
d
is,
N.
Tsiam
it
r
o
s,
C.
G
e
n
tn
e
r,
D.
B.
Ah
m
e
d
,
a
n
d
C.
P
re
h
o
fe
r,
"
A
No
v
e
l
Li
g
h
twe
ig
h
t
P
a
r
ti
c
le
F
il
ter
fo
r
In
d
o
o
r
L
o
c
a
li
z
a
ti
o
n
,
"
2
0
1
9
I
n
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
In
d
o
o
r
Po
siti
o
n
i
n
g
a
n
d
In
d
o
o
r
Na
v
i
g
a
t
i
o
n
(IP
IN)
,
2
0
1
9
,
p
p
.
1
-
8
,
d
o
i:
1
0
.
1
1
0
9
/IP
IN.
2
0
1
9
.
8
9
1
1
7
4
4
.
[7
]
N.
A.
Az
m
i,
S
.
S
a
m
su
l,
Y.
Ya
m
a
d
a
,
M
.
F
.
M
o
h
d
Ya
k
u
b
,
M
.
I.
M
o
h
d
Ism
a
il
,
a
n
d
R.
A.
Dz
iy
a
u
d
d
i
n
,
"
A
S
u
rv
e
y
o
f
Lo
c
a
li
z
a
ti
o
n
u
sin
g
RS
S
I
a
n
d
T
Do
A
Tec
h
n
i
q
u
e
s
in
Wi
re
les
s
S
e
n
so
r
Ne
two
r
k
:
S
y
ste
m
Arc
h
it
e
c
tu
re
,
"
2
0
1
8
2
n
d
In
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
T
e
lem
a
ti
c
s
a
n
d
F
u
tu
re
Ge
n
e
ra
ti
o
n
Ne
two
rk
s
(T
AF
GEN)
,
2
0
1
8
,
p
p
.
1
3
1
-
1
3
6
,
d
o
i:
1
0
.
1
1
0
9
/T
AFG
EN.
2
0
1
8
.
8
5
8
0
4
6
4
.
[8
]
D.
P
lets,
N.
P
o
d
e
v
i
jn
,
J.
Tro
g
h
,
L.
M
a
rten
s
,
a
n
d
W.
J
o
se
p
h
,
"
E
x
p
e
rime
n
tal
P
e
rfo
rm
a
n
c
e
Ev
a
lu
a
ti
o
n
o
f
Ou
t
d
o
o
r
TDo
A
a
n
d
RS
S
P
o
siti
o
n
i
n
g
i
n
a
P
u
b
l
ic
Lo
Ra
Ne
two
rk
,
"
2
0
1
8
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
In
d
o
o
r
Po
siti
o
n
i
n
g
a
n
d
In
d
o
o
r N
a
v
ig
a
ti
o
n
(IP
IN)
,
2
0
1
8
,
p
p
.
1
-
8
,
d
o
i:
1
0
.
1
1
0
9
/IP
IN.
2
0
1
8
.
8
5
3
3
7
6
1
.
[9
]
Z.
Jin
a
n
d
X.
Zen
g
,
"
Re
se
a
rc
h
o
n
a
M
u
lt
i
-
ro
b
o
t
R
o
u
t
in
g
Op
ti
m
iz
a
ti
o
n
M
e
t
h
o
d
Ba
se
d
o
n
Hy
b
r
id
Lo
ra
Lo
c
a
ti
o
n
,
"
2
0
2
0
5
t
h
I
n
ter
n
a
t
io
n
a
l
Co
n
fer
e
n
c
e
o
n
C
o
n
tro
l,
Ro
b
o
ti
c
s
a
n
d
Cy
b
e
rn
e
ti
c
s
(CRC)
,
2
0
2
0
,
p
p
.
2
2
1
-
2
2
5
,
d
o
i:
1
0
.
1
1
0
9
/CRC5
1
2
5
3
.
2
0
2
0
.
9
2
5
3
4
5
4
.
[1
0
]
K.
Lam
,
C.
Ch
e
u
n
g
,
a
n
d
W.
Le
e
,
"
RS
S
I
-
Ba
se
d
Lo
Ra
Lo
c
a
li
z
a
ti
o
n
S
y
ste
m
s
fo
r
Larg
e
-
S
c
a
le
In
d
o
o
r
a
n
d
Ou
t
d
o
o
r
En
v
ir
o
n
m
e
n
ts,
"
i
n
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Ve
h
icu
l
a
r
T
e
c
h
n
o
lo
g
y
,
v
o
l
.
6
8
,
n
o
.
1
2
,
p
p
.
1
1
7
7
8
-
1
1
7
9
1
,
De
c
.
2
0
1
9
,
d
o
i:
1
0
.
1
1
0
9
/T
VT.
2
0
1
9
.
2
9
4
0
2
7
2
.
[1
1
]
W.
Ch
o
i,
Y
.
-
S
.
C
h
a
n
g
,
Y.
J
u
n
g
,
a
n
d
J.
S
o
n
g
,
“
Lo
w
-
P
o
we
r
L
o
Ra
S
ig
n
a
l
-
Ba
se
d
Ou
t
d
o
o
r
P
o
si
ti
o
n
i
n
g
Us
in
g
F
in
g
e
r
p
rin
t
Alg
o
rit
h
m
,
”
IS
PR
S
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
Ge
o
-
In
fo
rm
a
ti
o
n
,
v
o
l.
7
,
n
o
.
1
1
,
p
.
4
4
0
,
No
v
.
2
0
1
8
,
d
o
i:
1
0
.
3
3
9
0
/i
j
g
i7
1
1
0
4
4
0
.
[1
2
]
E.
Essa
,
B.
A.
Ab
d
u
ll
a
h
,
a
n
d
A.
Wah
b
a
,
"
Im
p
ro
v
e
P
e
rfo
rm
a
n
c
e
o
f
In
d
o
o
r
P
o
siti
o
n
i
n
g
S
y
ste
m
u
si
n
g
BLE
,
"
2
0
1
9
1
4
t
h
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Co
m
p
u
ter
En
g
in
e
e
rin
g
a
n
d
S
y
ste
ms
(ICCES
)
,
2
0
1
9
,
p
p
.
2
3
4
-
2
3
7
,
d
o
i:
1
0
.
1
1
0
9
/ICCE
S
4
8
9
6
0
.
2
0
1
9
.
9
0
6
8
1
4
2
.
[1
3
]
H.
Li
a
n
d
H.
M
a
,
"
A
Lo
w
Co
m
p
lex
it
y
Lo
w
P
o
w
e
r
I
n
d
o
o
r
P
o
sit
io
n
in
g
S
y
ste
m
Ba
se
d
o
n
Wi
re
les
s
Re
c
e
iv
e
d
S
ig
n
a
l
S
tren
g
t
h
,
"
2
0
1
8
IE
EE
2
0
t
h
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
e
-
H
e
a
lt
h
Ne
tw
o
rk
in
g
,
A
p
p
l
ica
ti
o
n
s
a
n
d
S
e
rv
ice
s
(He
a
lt
h
c
o
m)
,
2
0
1
8
,
p
p
.
1
-
6
,
d
o
i:
1
0
.
1
1
0
9
/He
a
lt
h
C
o
m
.
2
0
1
8
.
8
5
3
1
1
3
7
.
[1
4
]
M
.
E
.
R
u
sli,
M
.
Ali,
N.
Ja
m
il
,
a
n
d
M
.
M
.
Din
,
"
A
n
Im
p
ro
v
e
d
In
d
o
o
r
P
o
si
ti
o
n
in
g
Alg
o
rit
h
m
B
a
se
d
o
n
RS
S
I
-
Tri
late
ra
ti
o
n
Tec
h
n
i
q
u
e
fo
r
In
t
e
rn
e
t
o
f
T
h
in
g
s
(IOT),
"
2
0
1
6
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
Co
mp
u
ter
a
n
d
Co
mm
u
n
ica
ti
o
n
E
n
g
i
n
e
e
rin
g
(IC
CCE)
,
2
0
1
6
,
p
p
.
7
2
-
7
7
,
d
o
i:
1
0
.
1
1
0
9
/ICCCE
.
2
0
1
6
.
2
8
.
[1
5
]
S
.
Na
g
h
d
i
a
n
d
K.
O’K
e
e
fe
,
"
Tri
late
ra
ti
o
n
Wi
t
h
BLE
RS
S
I
Ac
c
o
u
n
t
in
g
fo
r
P
a
th
l
o
ss
Du
e
to
Hu
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6
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7
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a
v
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th
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b
a
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late
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,
UK
.
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s (
I
o
T),
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lg
o
rit
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m
d
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p
m
e
n
t
wit
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.
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u
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i
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e
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a
c
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tro
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n
g
i
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with
h
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m
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iv
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k
n
i
k
a
l
M
a
lay
sia
M
e
lak
a
(
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M
).
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rre
n
tl
y
p
u
rs
u
in
g
a
t
p
o
stg
ra
d
u
a
te
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l.
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s
p
a
ss
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is wi
th
Bl
u
e
to
o
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o
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a
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g
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h
e
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ter
n
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t
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of
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t
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s (Io
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tec
h
n
o
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g
y
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h
a
m
a
d
Z
o
in
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l
Abi
d
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n
Ab
d
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iz
,
re
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e
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d
b
o
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a
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m
a
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o
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