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G
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ased
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O
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Wo
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T
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b
ac
k
w
ar
d
,
lef
t
a
n
d
r
i
g
h
t.[
1
3
]
T
h
e
p
r
o
p
o
s
ed
s
y
s
te
m
also
h
as
au
to
s
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n
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p
ab
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lli
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it
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s
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s
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th
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at
h
u
s
i
n
g
i
n
f
r
ar
e
d
s
e
n
s
o
r
[
1
0
]
.
A
p
ar
t
f
r
o
m
th
e
s
e
s
m
ar
t
m
o
v
e
m
e
n
t
co
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tr
o
l
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e
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air
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as
e
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ed
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ed
GP
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m
o
d
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le
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a
t t
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ates c
an
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to
m
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th
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cu
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en
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ca
tio
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.
2.
L
I
T
E
R
AT
U
RE
SU
RVE
Y
A
d
y
n
a
m
ic
v
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s
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r
(
DV
S)
d
etec
ts
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f
b
r
ig
h
t
n
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s
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tatic
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r
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f
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m
e.
[
9
]
I
t
ca
lcu
late
s
th
e
ac
c
u
r
ate
d
is
ta
n
ce
in
r
ea
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ti
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e
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l
y
w
it
h
s
p
a
tial
in
f
o
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m
at
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n
o
f
t
h
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r
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fl
ec
t
io
n
.
T
h
e
p
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p
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s
ed
d
esig
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ca
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eli
m
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ate
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y
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atter
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atch
in
g
b
ased
o
n
ti
m
e
-
d
o
m
ain
an
al
y
s
is
[
1
]
.
Au
to
m
a
tic
V
id
eo
-
B
ased
H
u
m
an
Mo
tio
n
an
a
l
y
ze
r
f
o
r
co
n
s
u
m
er
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llan
ce
s
y
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te
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d
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es
a
f
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x
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f
r
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o
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k
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s
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an
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m
a
n
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eh
a
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n
ce
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eo
,
ca
p
tu
r
ed
b
y
a
co
n
s
u
m
er
ca
m
er
a
[
1
2
]
.
Su
cc
e
s
s
f
u
l
tr
aj
ec
to
r
y
e
s
ti
m
atio
n
a
n
d
h
u
m
a
n
-
b
o
d
y
m
o
d
ellin
g
f
ac
ili
tate
t
h
e
s
e
m
a
n
tic
a
n
al
y
s
i
s
o
f
h
u
m
an
ac
tiv
itie
s
an
d
e
v
en
t
s
in
v
id
eo
s
e
q
u
en
ce
s
[
2
]
.
Ob
s
tacle
Dete
ctio
n
f
o
r
Vis
u
a
ll
y
I
m
p
air
ed
[
1
1
]
Usi
n
g
R
as
p
b
er
r
y
P
i
an
d
Ultr
aso
n
ic
Sen
s
o
r
s
is
a
w
ea
r
ab
le
d
ev
ice
in
th
e
f
o
r
m
o
f
a
w
ais
t
b
elt
t
h
at
h
as
u
ltra
s
o
n
ic
s
e
n
s
o
r
s
an
d
r
asp
b
er
r
y
p
i
in
s
ta
lled
,
d
etec
ts
o
b
s
tacle
s
ar
o
u
n
d
th
e
u
s
er
u
p
to
5
0
0
cm
i
n
th
r
ee
d
ir
ec
tio
n
s
i.e
.
f
r
o
n
t,
lef
t
a
n
d
r
ig
h
t
u
s
in
g
a
n
et
w
o
r
k
o
f
u
ltra
s
o
n
ic
s
e
n
s
o
r
s
[
3
]
.
A
u
to
n
o
m
o
u
s
C
ar
,
b
u
ild
i
n
g
a
m
o
n
o
cu
lar
v
is
io
n
a
u
to
n
o
m
o
u
s
ca
r
p
r
o
t
o
ty
p
e
u
s
i
n
g
R
asp
b
er
r
y
P
i
as
a
p
r
o
ce
s
s
in
g
ch
ip
.
An
HD
ca
m
er
a
alo
n
g
w
it
h
an
u
ltra
s
o
n
ic
s
e
n
s
o
r
is
u
s
ed
to
p
r
o
v
id
e
n
ec
es
s
ar
y
d
ata
f
r
o
m
t
h
e
r
ea
l
wo
r
ld
to
th
e
ca
r
.
Ma
n
y
e
x
is
tin
g
alg
o
r
ith
m
s
li
k
e
lan
e
d
etec
tio
n
,
o
b
s
tacle
d
etec
tio
n
ar
e
co
m
b
i
n
ed
to
g
eth
er
to
p
r
o
v
id
e
th
e
n
ec
es
s
ar
y
co
n
tr
o
l to
th
e
ca
r
[
4
]
.
S
m
ar
t
S
u
r
v
e
illa
n
ce
S
y
s
te
m
m
o
d
el
d
escr
ib
es
a
s
m
a
ll
p
o
r
tab
le
m
o
n
ito
r
i
n
g
s
y
s
te
m
f
o
r
h
o
m
e
an
d
o
f
f
ice
s
ec
u
r
it
y
,
u
s
es
R
a
s
p
b
er
r
y
p
i
(
m
o
d
el
B
)
,
G
y
r
o
s
e
n
s
o
r
an
d
R
asp
b
er
r
y
p
i
ca
m
er
a
to
m
o
n
ito
r
w
h
en
m
o
tio
n
d
etec
ted
,
th
e
R
asp
b
er
r
y
P
i
w
il
l
co
n
tr
o
l
th
e
R
asp
b
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r
y
P
i
ca
m
er
a
to
tak
e
a
p
ictu
r
e
an
d
s
e
n
t
o
u
t
an
aler
t
em
ai
l
w
it
h
t
h
e
i
m
a
g
e
to
th
e
u
s
er
ac
co
r
d
in
g
to
th
e
p
r
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g
r
a
m
w
r
i
tten
in
p
y
t
h
o
n
en
v
ir
o
n
m
e
n
t
[
5
]
.
A
n
d
r
o
id
B
ased
H
o
m
e
Au
to
m
a
tio
n
s
y
s
te
m
d
escr
ib
es
co
n
ce
p
t
o
f
Ho
m
e
Au
to
m
atio
n
v
ia
A
n
d
r
o
id
d
ev
ice
u
s
i
n
g
W
i
-
Fi
a
s
co
m
m
u
n
icatio
n
p
r
o
to
co
l
an
d
R
asp
b
er
r
y
P
i
as
s
er
v
er
s
y
s
te
m
.
T
h
e
s
er
v
er
is
in
ter
f
ac
ed
w
it
h
a
r
ela
y
cir
c
u
it
b
o
ar
d
th
at
co
n
tr
o
ls
th
e
ap
p
lian
ce
s
r
u
n
n
i
n
g
i
n
Ho
m
e.
T
h
e
co
m
m
u
n
icatio
n
w
it
h
s
er
v
er
allo
w
s
th
e
u
s
er
to
s
elec
t
th
e
ap
p
r
o
p
r
iate
d
ev
ice
[
6
]
.
D
y
n
a
m
ic
u
ltra
s
o
n
ic
h
y
b
r
id
l
o
ca
lizatio
n
s
y
s
te
m
f
o
r
in
d
o
o
r
m
o
b
ile
r
o
b
o
ts
p
r
o
p
o
s
es
au
to
n
o
m
o
u
s
n
av
i
g
atio
n
o
f
i
n
d
o
o
r
m
o
b
ile
r
o
b
o
ts
u
s
in
g
m
u
ltip
le
u
ltra
s
o
n
i
c
d
is
tan
ce
m
ea
s
u
r
e
m
e
n
ts
a
n
d
an
ex
te
n
d
ed
Kal
m
a
n
f
ilter
(
E
KF)
.
T
h
e
u
ltra
s
o
n
ic
s
e
n
s
o
r
s
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b
s
y
s
te
m
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m
p
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o
f
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tter
s
(
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x
s
)
attac
h
ed
to
th
e
ce
ilin
g
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k
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w
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p
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s
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an
d
s
ev
er
al
u
ltra
s
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ic
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er
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eq
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ilater
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ca
ted
o
n
th
e
to
p
o
f
th
e
m
o
b
ile
r
o
b
o
t
[
7
]
.
W
ir
eless
in
ter
f
ac
i
n
g
o
f
R
a
s
p
b
er
r
y
P
i
u
s
i
n
g
B
lu
eto
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d
escr
ib
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s
m
ar
t
p
h
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e
b
ased
r
e
m
o
te
co
n
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to
co
m
m
u
n
icate
w
it
h
R
a
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p
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er
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P
i,
v
ia
d
esig
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g
a
n
An
d
r
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id
B
lu
eto
o
th
ap
p
licatio
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f
r
o
m
w
h
ic
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t
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ec
ts
w
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asp
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P
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s
B
lu
eto
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f
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n
n
ec
t
w
it
h
R
a
s
p
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P
i [
8
]
.
3.
P
RO
P
O
SE
D
M
O
DE
L
T
h
e
p
r
o
p
o
s
ed
s
y
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te
m
i
s
an
i
n
telli
g
e
n
t
v
e
h
icle
f
o
r
d
is
ab
led
/eld
er
ly
p
eo
p
l
e
w
h
ic
h
u
s
es
an
ar
r
ay
o
f
s
en
s
o
r
s
to
h
elp
w
i
th
th
e
m
o
v
e
m
en
t
o
f
th
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v
e
h
icle
w
i
th
m
i
n
i
m
al
h
u
m
a
n
i
n
ter
ac
tio
n
.
T
h
i
s
is
d
o
n
e
u
s
i
n
g
a
R
A
SP
B
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R
R
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w
h
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ac
ts
as
th
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h
ea
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a
n
d
co
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tr
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le
s
y
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m
ce
n
tr
all
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T
h
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m
icr
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-
co
n
tr
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is
r
esp
o
n
s
ib
le
f
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th
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ta
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to
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r
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t
b
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e
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y
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li
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co
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m
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B
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to
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f
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ess
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tat
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m
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ed
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r
th
er
th
e
f
u
n
ct
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ies
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
R
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N:
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4864
S
ma
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V
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fo
r
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)
85
p
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p
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ed
s
y
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m
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ex
ten
d
ed
b
y
u
p
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atin
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c
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r
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lo
ca
ti
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f
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co
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ted
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.
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h
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tio
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d
etail
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th
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ated
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1
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m
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tes u
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cr
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ip
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I
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ad
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th
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ab
les
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S
OS
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g
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a
l
b
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tto
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r
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ic
b
u
tto
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g
w
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o
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ca
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d
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tr
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d
d
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f
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k
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u
s
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g
th
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m
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m
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in
p
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to
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ap
a
p
ath
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to
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at
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m
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v
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en
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v
e
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ic
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h
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m
ain
a
s
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t
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p
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ed
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t
h
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co
s
t
o
f
p
r
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ctio
n
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a
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g
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f
s
m
ar
t
w
h
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c
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air
w
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n
ct
i
o
n
alities
s
i
m
ilar
to
t
h
e
o
n
e
p
r
o
p
o
s
ed
in
th
e
s
y
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te
m
s
tar
ts
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o
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n
d
1
lak
h
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u
p
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w
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r
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ad
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it
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b
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o
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s
.
2
0
,
0
0
0
w
h
ich
ca
n
en
ab
le
p
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p
le
o
f
lo
w
er
in
co
m
e
g
r
o
u
p
s
to
u
s
e
a
n
d
w
it
n
ess
h
i
g
h
en
d
tech
n
o
lo
g
y
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d
e
n
g
i
n
ee
r
in
g
at
a
n
a
f
f
o
r
d
ab
le
p
r
ice.
Ob
j
ec
tiv
es o
f
s
y
s
te
m
d
esi
g
n
:
1.
I
f
Dis
ta
n
ce
b
et
w
ee
n
a
o
b
s
tacle
an
d
v
eh
ic
le
less
t
h
a
n
th
er
s
h
o
l
d
v
alu
e
s
to
p
th
e
v
e
h
icle.
Ma
th
e
m
atica
ll
y
,
I
f
D
obstacle
<
T
h
r
esh
o
ld
=>
Sto
p
Veh
icle
2.
I
f
th
e
co
lo
r
d
etec
ted
b
y
w
eb
ca
m
er
a
is
r
ed
(
i.e
.
tr
af
f
ic
li
g
h
t i
s
r
ed
)
s
to
p
th
e
v
eh
icle
I
f
C
o
lo
r
traffic
lig
ht
=
R
ed
=>
Sto
p
Veh
icle
B
lo
ck
Dia
g
r
a
m:
Fig
u
r
e
4
.
S
y
s
te
m
De
s
ig
n
Fig
u
r
e
5
.
C
o
m
p
o
n
e
n
ts
Deta
i
ls
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4
864
I
J
R
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V
o
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6
,
No
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2
,
J
u
l
y
2
0
1
7
:
8
2
–
8
7
86
C
o
mp
o
n
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n
t
U
se
d
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o
r
P
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e
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t
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h
e
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l
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h
a
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r
M
o
t
o
r
M
o
t
o
r
u
se
d
t
o
mo
v
e
t
h
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w
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l
c
h
a
i
r
w
i
t
h
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u
t
a
n
y
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x
t
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r
n
a
l
h
e
l
p
C
o
n
n
e
c
t
e
d
t
o
p
i
n
1
t
h
r
o
u
g
h
a
R
EL
A
Y
o
f
1
2
V
U
l
t
r
a
so
n
i
c
S
e
n
so
r
D
e
t
e
c
t
a
n
y
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st
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l
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n
p
a
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h
C
o
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n
e
c
t
e
d
t
o
p
i
n
2
G
r
e
e
n
L
ED
S
y
st
e
m i
n
d
i
c
a
t
i
o
n
d
i
s
p
l
a
y
C
o
n
n
e
c
t
e
d
t
o
p
i
n
7
R
e
d
L
ED
S
y
st
e
m i
n
d
i
c
a
t
i
o
n
d
i
s
p
l
a
y
C
o
n
n
e
c
t
e
d
t
o
p
i
n
5
B
l
u
e
t
o
o
t
h
mo
d
u
l
e
Est
a
b
l
i
s
h
i
n
g
a
c
o
n
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e
c
t
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o
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b
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t
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d
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d
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p
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d
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p
i
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3
3
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3
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L
E
D
D
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sp
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c
t
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d
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o
p
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1
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3
0
a
n
d
8
-
10
4.
RE
SU
L
T
S AN
D
AN
AL
Y
SI
S
T
h
e
S
m
ar
t
A
s
s
is
ted
Veh
ic
le
f
o
r
Dis
ab
led
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er
l
y
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u
p
p
o
s
ed
to
b
e
eq
u
ip
p
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w
it
h
a
m
p
le
o
f
s
en
s
o
r
s
w
h
ic
h
w
ill
h
elp
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s
er
s
to
co
m
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en
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ate
t
h
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lack
o
f
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en
s
es.
P
r
o
p
o
s
ed
w
h
ee
lc
h
air
is
eq
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ip
p
ed
w
i
th
u
ltra
s
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n
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en
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r
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t
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b
s
tacle
s
in
th
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p
at
h
,
w
it
h
o
u
t
u
s
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’
s
i
n
ter
v
e
n
tio
n
.
W
h
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lc
h
ai
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eq
u
ip
p
ed
w
it
h
ca
m
er
a
w
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ize
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al
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co
r
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.
W
eb
ca
m
er
a
w
h
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u
s
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ti
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l
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n
d
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ter
s
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t th
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icle
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c
o
r
d
in
g
l
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h
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lch
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w
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o
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latest
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e
r
s
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n
o
f
R
a
s
p
b
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i
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w
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m
ai
n
tai
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w
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k
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f
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.
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asp
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lu
eto
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to
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h
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n
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ted
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m
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f
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m
An
d
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id
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m
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s
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y
ca
n
t
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k
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s
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m
il
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n
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ter
f
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le
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ate
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its
r
a
d
ar
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eq
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ip
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w
ith
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ic
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u
tto
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s
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m
m
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t h
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s
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ith
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u
l
tr
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en
s
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m
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s
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asp
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k
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ap
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p
p
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:
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u
l
f
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Dis
ab
led
to
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v
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m
e
th
e
ir
li
m
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.
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u
l
f
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ld
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ly
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h
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ap
p
.
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p
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b
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titl
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p
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k
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f
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e
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etc.
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m
ar
t p
an
ic
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CO
NCLU
SI
O
N
P
r
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p
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h
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lc
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eq
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ip
p
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ltra
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ter
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,
w
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ill
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.
RE
F
E
R
E
NC
E
S
[1
]
Ja
e
-
Ye
o
n
W
o
n
,
H
y
u
n
su
rk
R
y
u
,
To
b
i
De
lb
ru
c
k
,
F
e
ll
o
w
,
IEE
E,
Ju
n
Ha
e
n
g
L
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e
,
a
n
d
Jia
n
g
Hu
,
S
e
n
io
r
M
e
m
b
e
r,
IEE
E
"
P
ro
x
im
it
y
S
e
n
sin
g
Ba
s
e
d
o
n
a
D
y
n
a
m
ic
V
isio
n
S
e
n
so
r
f
o
r
M
o
b
il
e
De
v
ice
s
"
.
IEE
E
T
ra
n
sa
c
ti
o
n
s
on
In
d
u
stria
l
El
e
c
tro
n
ics
,
V
o
l
.
6
2
,
N
o
.
1
,
Ja
n
u
a
ry
2
0
1
5
.
[2
]
P
e
ter
H.N.
d
e
a
n
d
W
.
L
a
o
,
J.
Ha
n
W
it
h
,
“
A
u
to
m
a
ti
c
v
id
e
o
b
a
se
d
h
u
m
a
n
m
o
ti
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n
a
n
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ly
z
e
r
f
o
r
c
o
n
su
m
e
r
su
rv
e
il
lan
c
e
s
y
ste
m
”
,
IEE
E
T
ra
n
s Co
n
su
m E
lec
tro
n
,
Vo
l.
5
5
,
No
.
2
,
p
p
.
5
9
1
-
5
9
8
,
2
0
0
9
.
[3
]
Ay
u
sh
W
a
tt
a
l,
As
h
u
to
s
h
Ojh
a
,
M
a
n
o
j
Ku
m
a
r
.
“
Ob
sta
c
le
De
tec
ti
o
n
fo
r
V
isu
a
ll
y
Imp
a
ire
d
Us
in
g
Ra
sp
b
e
rr
y
Pi
a
n
d
Ultra
so
n
ic
S
e
n
so
rs
”
.
Na
ti
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l
Co
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f
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re
n
c
e
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n
P
ro
d
u
c
t
De
sig
n
(NC
P
D
2
0
1
6
)
,
Ju
ly
2
0
1
6
.
[4
]
G
u
rjas
h
a
n
S
in
g
h
P
a
n
n
u
,
M
o
h
a
m
m
a
d
Da
w
u
d
A
n
sa
ri,
P
rit
h
a
G
u
p
ta
.
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De
sig
n
a
n
d
I
m
p
le
m
e
n
tatio
n
o
f
A
u
to
n
o
m
o
u
s
Ca
r
u
sin
g
Ra
sp
b
e
rry
P
i"
.
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Co
m
p
u
ter
A
p
p
l
ica
ti
o
n
s
(0
9
7
5
-
8
8
8
7
)
V
o
l
u
m
e
1
1
3
-
No
.
9
,
M
a
rc
h
2
0
1
5
[5
]
R.
Ch
a
n
d
a
n
a
,
Dr.S
.
A
.
K.Jilan
i,
M
r
.
S
.
Ja
v
e
e
d
Hu
ss
a
in
.
"
S
m
a
rt
S
u
rv
e
i
ll
a
n
c
e
S
y
ste
m
u
sin
g
T
h
in
g
S
p
e
a
k
a
n
d
Ra
sp
b
e
rry
P
i"
.
I
n
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
A
d
v
a
n
c
e
d
Res
e
a
rc
h
in
Co
mp
u
ter
a
n
d
Co
mm
u
n
ica
ti
o
n
E
n
g
i
n
e
e
rin
g
.
V
o
l
.
4
,
Iss
u
e
7
,
Ju
ly
2
0
1
5.
[6
]
S
h
a
ij
u
P
a
u
l,
A
sh
li
n
A
n
to
n
y
,
A
s
w
a
th
y
B
.
"
A
n
d
ro
id
Ba
se
d
Ho
m
e
A
u
to
m
a
ti
o
n
Us
in
g
Ra
sp
b
e
rry
P
i
"
.
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Co
m
p
u
ti
n
g
a
n
d
T
e
c
h
n
o
lo
g
y
(
IJ
CAT
)
.
Vo
lu
m
e
1
,
Iss
u
e
1
,
F
e
b
r
u
a
ry
2
0
1
4
.
[7
]
S
.
J.
Kim
a
n
d
B.
K.
Ki
m
,
“
D
y
n
a
m
ic
u
lt
ra
so
n
ic
h
y
b
rid
lo
c
a
li
z
a
ti
o
n
sy
ste
m
f
o
r
in
d
o
o
r
m
o
b
il
e
ro
b
o
t
s,”
IEE
E
T
ra
n
s.
In
d
.
El
e
c
tro
n
.
,
v
o
l.
6
0
,
n
o
.
1
0
,
p
p
.
4
5
6
2
-
4
5
7
3
,
Oc
t.
2
0
1
3
.
[8
]
Bh
a
v
in
i
M
.
Ch
a
u
d
h
a
ri,
Ne
h
a
l
G
.
c
h
it
a
li
y
a
.
"
De
sig
n
o
f
W
irele
ss
M
o
d
u
le
f
o
r
In
terf
a
c
in
g
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sp
b
e
rry
P
i
W
it
h
Blu
e
to
o
th
"
.
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
In
n
o
v
a
ti
v
e
Res
e
a
rc
h
in
Co
m
p
u
ter
a
n
d
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mm
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n
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ti
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n
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n
g
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n
e
e
rin
g
.
A
n
IS
O
3
2
9
7
:
2
0
0
7
Ce
rti
f
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Org
a
n
iza
ti
o
n
)
V
o
l
.
4
,
Iss
u
e
2
,
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e
b
r
u
a
ry
2
0
1
6
.
[9
]
S
tep
h
a
n
S
c
h
ra
m
l,
A
h
m
e
d
Na
b
il
B
e
lb
a
c
h
ir,
Ho
rst
Bisc
h
o
f
,
"
A
n
Ev
e
n
t
-
Driv
e
n
S
tere
o
S
y
st
e
m
f
o
r
Re
a
l
-
T
i
m
e
3
-
D
3
6
0
°
P
a
n
o
ra
m
ic
V
isio
n
"
,
In
d
u
str
ia
l
El
e
c
tro
n
ics
IEE
E
T
r
a
n
s
a
c
ti
o
n
s
o
n
,
v
o
l
.
6
3
,
p
p
.
4
1
8
-
4
2
8
,
2
0
1
6
,
IS
S
N
0
2
7
8
-
0
0
4
6
.
[1
0
]
Jo
a
n
n
a
M
.
Na
ss
a
r,
M
a
rlo
n
C.
Dia
z
,
M
u
h
a
m
m
a
d
M
.
Hu
ss
a
in
,
"
Af
f
o
rd
a
b
le
d
u
al
-
se
n
sin
g
p
r
o
x
i
mity
se
n
so
r
fo
r
to
u
c
h
les
s in
ter
a
c
ti
v
e
sy
ste
ms
"
,
De
v
ice
Re
se
a
rc
h
Co
n
f
e
re
n
c
e
(DRC)
2
0
1
6
7
4
th
A
n
n
u
a
l
,
p
p
.
1
-
2
,
2
0
1
6
.
[1
1
]
J.
Ko
n
sta
n
ti
n
o
v
a
,
A
.
S
ti
ll
i,
A
.
F
a
ra
g
a
ss
o
,
K.
A
lt
h
o
e
f
e
r,
"
Fi
n
g
e
rt
ip
p
ro
x
imi
ty
se
n
so
r
wit
h
re
a
l
ti
m
e
v
isu
a
l
-
b
a
se
d
c
a
li
b
ra
t
io
n
"
,
I
n
telli
g
e
n
t
Ro
b
o
ts
a
n
d
S
y
ste
m
s
(IROS)
2
0
1
6
IE
EE
/RS
J
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
,
p
p
.
1
7
0
-
1
7
5
,
2
0
1
6
,
IS
S
N
2
1
5
3
-
0
8
6
6
.
[1
2
]
P
.
P
e
e
r
a
n
d
F
.
S
o
l
in
a
,
“
P
a
n
o
ra
m
ic
d
e
p
t
h
im
a
g
in
g
:
S
in
g
le
sta
n
d
a
r
d
c
a
m
e
ra
a
p
p
ro
a
c
h
,
”
I
n
t.
J
.
Co
m
p
u
t.
Vi
s
.
,
v
o
l.
4
7
,
n
o
.
1
-
3
,
p
p
.
1
4
9
-
1
6
0
,
A
p
r.
2
0
0
2
.
[1
3
]
Y.
W
a
n
g
,
B.
M
.
Ng
u
y
e
n
,
H.
F
u
ji
m
o
to
,
a
n
d
Y.
Ho
ri,
“
M
u
lt
irate
e
sti
m
a
ti
o
n
a
n
d
c
o
n
tr
o
l
o
f
b
o
d
y
slip
a
n
g
le f
o
r
e
lec
tri
c
v
e
h
icle
s b
a
se
d
o
n
o
n
b
o
a
rd
v
isio
n
s
y
ste
m
,
”
IEE
E
T
ra
n
s.
I
n
d
.
El
e
c
tro
n
.
,
v
o
l.
6
1
,
n
o
.
2
,
p
p
.
1
1
3
3
-
1
1
4
3
,
F
e
b
.
2
0
1
4
.
[1
4
]
S
u
rv
e
y
g
ra
p
h
s
b
a
se
d
o
n
th
e
d
a
ta
f
ro
m
th
e
f
o
ll
o
w
in
g
li
n
k
:
h
tt
p
:/
/t
h
e
q
u
a
n
t
u
m
lea
p
.
c
o
m
/
w
p
-
c
o
n
ten
t/
u
p
lo
a
d
s/
2
0
1
6
/
0
7
/W
h
e
e
lch
a
ir
-
u
se
rs
-
su
rv
e
y
.
p
d
f
,
M
a
y
2
0
1
6
.
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