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[
2
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,
[
3
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T
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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&
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I
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tellig
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A
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389
an
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v
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p
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s
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u
r
e
1
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s
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u
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u
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[
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Fig
u
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1
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waste
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I
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[
1
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I
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p
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tific
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tellig
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AI
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tech
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r
ac
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v
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[
3
]
–
[
5
]
.
Su
c
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in
tell
ig
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ates
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R
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ies
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ar
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tan
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lem
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[
5
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,
[
6
]
.
T
h
e
s
y
n
e
r
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y
b
etwe
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ased
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to
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d
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tr
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if
ican
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tech
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ter
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n
d
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in
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.
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s
y
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ical
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en
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M
E
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H
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DO
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h
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ev
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a
s
tr
u
ctu
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an
aly
tical
f
r
am
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r
k
to
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alu
ate
th
e
in
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r
atio
n
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f
AI
an
d
I
o
T
tech
n
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lo
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ies
in
s
o
lid
waste
m
an
ag
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(
SW
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m
eth
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liter
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ilter
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tech
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ical
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ar
ch
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ased
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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ased
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atic
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n
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o
ce
s
s
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PR
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r
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as
s
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Fig
u
r
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3
.
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ly
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atin
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tal
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ty
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en
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o
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ith
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ic
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elin
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o
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a
n
ce
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etr
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clu
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.
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o
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o
licy
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d
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s
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io
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with
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u
t
im
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d
etails
wer
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clu
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ed
.
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n
s
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ch
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d
y
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ep
en
d
en
tly
,
th
e
s
elec
ted
li
ter
atu
r
e
was o
r
g
an
ized
in
t
o
f
iv
e
tech
n
o
lo
g
ical
clu
s
ter
s
:
a.
Sen
s
o
r
-
b
ased
d
etec
tio
n
s
y
s
tem
s
b.
Mic
r
o
co
n
tr
o
ller
-
an
d
Ar
d
u
i
n
o
-
d
r
iv
en
a
r
ch
itectu
r
es
c.
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ar
t b
in
an
d
I
o
T
-
en
ab
led
m
o
n
ito
r
in
g
f
r
am
ewo
r
k
s
d.
C
lo
u
d
an
d
b
lo
ck
ch
ai
n
-
in
teg
r
at
ed
s
y
s
tem
s
e.
Ma
ch
in
e
lear
n
in
g
an
d
d
ee
p
lea
r
n
in
g
class
if
icatio
n
m
o
d
els
T
h
is
th
em
atic
s
tr
u
ctu
r
in
g
r
e
d
u
ce
s
r
ed
u
n
d
an
cy
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d
en
a
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les
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o
s
s
-
co
m
p
ar
is
o
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o
f
p
er
f
o
r
m
an
c
e
in
d
icato
r
s
ac
r
o
s
s
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tem
ty
p
es.
Fig
u
r
e
3
.
PR
I
SMA
f
lo
w
d
iag
r
am
o
f
s
tu
d
y
s
ele
ctio
n
p
r
o
ce
s
s
2
.
2
.
AI a
nd
I
o
T
des
ig
n m
et
ho
do
lo
g
ies
T
wo
d
o
m
in
a
n
t a
r
ch
itectu
r
al
a
p
p
r
o
ac
h
es we
r
e
id
en
tifie
d
i
n
t
h
e
r
ev
iewe
d
liter
atu
r
e:
a.
R
u
le
-
b
ased
co
n
tr
o
l sy
s
tem
s
T
h
ese
s
y
s
tem
s
u
s
e
p
r
ed
ef
in
e
d
lo
g
ical
c
o
n
d
itio
n
s
e
m
b
ed
d
e
d
in
m
ic
r
o
co
n
tr
o
ller
s
to
tr
i
g
g
er
s
o
r
t
in
g
m
ec
h
an
is
m
s
.
Alth
o
u
g
h
co
s
t
-
ef
f
icien
t,
th
ey
ar
e
lim
ited
in
h
a
n
d
lin
g
m
ix
e
d
o
r
u
n
p
r
ed
ictab
le
waste
s
tr
ea
m
s
.
b.
AI
-
d
r
iv
en
ad
ap
tiv
e
s
y
s
tem
s
AI
-
b
ased
s
y
s
tem
s
in
teg
r
ate
m
ac
h
in
e
lear
n
in
g
alg
o
r
ith
m
s
an
d
co
m
p
u
ter
v
is
io
n
m
o
d
els
with
r
ea
l
-
tim
e
I
o
T
s
en
s
o
r
in
p
u
ts
.
T
h
ese
f
r
am
ewo
r
k
s
d
y
n
am
ically
class
if
y
waste,
o
p
tim
ize
co
llectio
n
in
t
er
v
als,
an
d
im
p
r
o
v
e
o
p
er
atio
n
al
in
tellig
en
ce
.
Stu
d
ies
r
ep
o
r
t
th
at
AI
–
I
o
T
in
teg
r
atio
n
ca
n
r
ed
u
ce
m
an
u
al
in
ter
v
en
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n
b
y
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r
ly
6
0
% wh
ile
in
cr
ea
s
in
g
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o
r
tin
g
co
n
s
is
ten
cy
[
7
]
.
2
.
3
.
I
nte
g
ra
t
io
n o
f
s
ens
o
rs
Sen
s
o
r
s
f
o
r
m
th
e
f
o
u
n
d
atio
n
o
f
AI
-
an
d
I
o
T
-
b
ased
waste
s
eg
r
eg
atio
n
s
y
s
tem
s
.
C
ap
ac
itiv
e,
in
d
u
ctiv
e,
an
d
in
f
r
ar
ed
(
I
R
)
s
en
s
o
r
s
ar
e
co
m
m
o
n
ly
u
s
ed
to
d
etec
t
a
n
d
d
if
f
er
en
tiate
m
ate
r
ials
.
T
h
e
ca
p
ac
itiv
e
s
en
s
o
r
id
en
tifie
s
s
o
lid
-
co
lo
r
ed
m
ater
ials
s
u
ch
as
p
last
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o
r
p
ap
er
(
ex
clu
d
in
g
tr
an
s
p
ar
e
n
t
m
ater
i
als),
th
e
in
d
u
ctiv
e
s
en
s
o
r
d
etec
ts
m
etals,
an
d
t
h
e
in
f
r
a
r
ed
s
en
s
o
r
id
e
n
tifi
es
th
e
p
r
esen
ce
o
f
a
n
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s
o
lid
o
b
ject.
W
aste
is
clas
s
if
ied
b
ased
o
n
th
e
co
m
b
i
n
atio
n
o
f
s
en
s
o
r
r
esp
o
n
s
es:
a.
Or
g
an
ic
waste
→
(
I
R
=
1
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n
d
u
ctiv
e
=
0
,
C
ap
ac
itiv
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=
1)
b.
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n
o
r
g
a
n
ic
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→
(
I
R
=
1
,
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n
d
u
ctiv
e
=
0
,
C
ap
ac
itiv
e
=
0)
c.
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tallic
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→
(
I
R
=
1
,
I
n
d
u
ctiv
e
=
1
,
C
ap
ac
itiv
e
=
1
)
[
7
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
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J
R
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b
&
A
u
to
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I
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tellig
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391
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ater
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m
b
in
atio
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f
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ater
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d
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[
7
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O
b
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t
i
f
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2
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4
.
M
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co
ntr
o
ller
a
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T
-
ena
bled im
plem
ent
a
t
io
ns
Ar
d
u
in
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d
E
SP
-
b
ased
m
ic
r
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co
n
tr
o
ller
s
y
s
tem
s
f
o
r
m
th
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b
ac
k
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f
m
an
y
r
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ar
ch
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r
es.
An
E
SP
3
2
-
b
ase
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s
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tem
in
teg
r
atin
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R
an
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o
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en
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o
r
s
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al
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n
ito
r
in
g
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d
m
o
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ile
d
ash
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o
ar
d
u
p
d
ates
[
8
]
.
An
o
th
er
Ar
d
u
in
o
Me
g
a
2
5
6
0
-
b
ased
im
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le
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r
ac
ies ab
o
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2
% f
o
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m
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d
g
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[
9
]
.
I
o
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a
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led
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ce
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f
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w
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n
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o
p
tim
ize
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llectio
n
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ch
ed
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lin
g
[
1
0
]
–
[
1
2
]
.
Hy
b
r
id
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lem
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tatio
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s
co
m
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in
in
g
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icr
o
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with
AI
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ased
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etec
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o
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els
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O
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d
em
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ated
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5
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t
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n
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icien
cy
[
1
3
]
–
[
1
5
]
.
T
h
e
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s
ical
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ch
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e
f
o
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th
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s
p
ec
if
ically
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ar
r
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g
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en
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ic
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d
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c
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l
es,
is
illu
s
tr
ated
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Fig
u
r
e
4
.
Fig
u
r
e
4
.
Diag
r
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m
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o
r
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d
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o
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ic
waste
s
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tin
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s
[
9
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2
.
5
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M
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ha
nica
l a
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g
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t
ed
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ated
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ased
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o
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atin
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lled
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o
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eg
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en
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ar
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[
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6
]
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[
1
7
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to
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em
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ter
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[
1
8
]
.
R
ep
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ted
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e
m
etr
ics in
clu
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a.
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tal
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:
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g
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5
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9
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ased
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izatio
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ith
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2
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6
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ased
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with
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ip
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a
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T
h
e
r
e
s
u
l
t
s
a
r
e
s
y
n
t
h
es
i
ze
d
a
c
r
o
s
s
f
o
u
r
m
a
j
o
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d
o
m
a
i
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s
:
c
l
o
u
d
-
e
n
a
b
l
e
d
i
n
t
e
l
l
i
g
e
n
ce
,
b
l
o
c
k
c
h
a
i
n
t
r
a
n
s
p
a
r
e
n
c
y
,
A
I
-
d
r
i
v
e
n
a
u
t
o
m
a
t
i
o
n
,
a
n
d
l
a
r
g
e
-
sc
a
le
m
u
n
i
c
i
p
a
l
i
m
p
le
m
e
n
t
a
ti
o
n
.
3
.
1
.
Clo
ud
-
ba
s
ed
inte
llig
ence
a
nd
da
t
a
o
ptim
iz
a
t
io
n
C
lo
u
d
co
m
p
u
tin
g
p
lay
s
a
cr
it
ical
r
o
le
in
en
a
b
lin
g
r
ea
l
-
tim
e
m
o
n
ito
r
in
g
,
an
aly
tics
,
a
n
d
p
r
ed
ictiv
e
waste
co
llectio
n
.
I
o
T
d
ev
ices
s
u
ch
as
p
r
o
g
r
am
m
a
b
le
in
ter
f
ac
e
co
n
tr
o
ller
(
P
IC
)
co
n
tr
o
ller
s
an
d
No
d
e
-
MCU
m
o
d
u
les
tr
an
s
m
it
waste
p
a
r
a
m
eter
s
-
ty
p
e,
weig
h
t,
tim
estam
p
,
an
d
f
ill
le
v
el
to
ce
n
tr
alize
d
clo
u
d
p
latf
o
r
m
s
f
o
r
s
to
r
ag
e
an
d
a
n
aly
s
is
[
2
2
]
.
C
lo
u
d
-
b
ased
p
r
o
d
u
ct
-
s
er
v
ice
s
y
s
tem
(
PS
S)
ar
ch
itectu
r
es
in
teg
r
ate
p
h
y
s
ical
waste
in
f
r
astru
ctu
r
e
with
an
aly
tics
lay
er
s
an
d
u
s
er
ap
p
licatio
n
s
,
allo
win
g
d
y
n
am
ic
r
o
u
te
o
p
tim
izatio
n
an
d
p
r
ed
ictiv
e
s
ch
ed
u
lin
g
[
2
3
]
.
E
x
p
er
im
en
tal
e
v
al
u
atio
n
s
r
ep
o
r
t:
a.
20
%
–
2
5
% r
e
d
u
ctio
n
i
n
co
llect
io
n
tim
e
b.
15
%
–
1
8
% r
e
d
u
ctio
n
i
n
f
u
el
c
o
n
s
u
m
p
tio
n
c.
I
m
p
r
o
v
ed
r
eso
u
r
ce
allo
ca
tio
n
ef
f
icien
cy
[
2
3
]
,
[
2
4
]
.
T
h
ese
im
p
r
o
v
e
m
en
ts
d
em
o
n
s
tr
ate
th
at
clo
u
d
in
teg
r
atio
n
tr
an
s
itio
n
s
waste
m
an
ag
em
en
t
f
r
o
m
r
ea
ctiv
e
co
llectio
n
m
o
d
els to
p
r
ed
ictiv
e,
d
ata
-
d
r
i
v
en
f
r
am
ewo
r
k
s
.
3
.
2
.
B
lo
c
k
cha
in f
o
r
t
r
a
ns
pa
re
ncy
a
nd
incent
iv
e
s
y
s
t
em
s
B
lo
ck
ch
ain
-
b
ased
waste
m
an
ag
em
en
t
f
r
am
ewo
r
k
s
en
h
an
ce
tr
ac
ea
b
ilit
y
,
tr
an
s
p
ar
en
cy
,
an
d
ac
co
u
n
tab
ilit
y
.
B
y
r
ec
o
r
d
in
g
ea
ch
tr
an
s
ac
tio
n
-
c
o
llectio
n
,
tr
an
s
f
er
,
an
d
d
is
p
o
s
al
o
n
d
e
ce
n
tr
alize
d
led
g
er
s
,
b
lo
ck
ch
ain
en
s
u
r
es
im
m
u
tab
le
d
ata
v
e
r
if
icatio
n
[
2
5
]
.
Sm
ar
t
co
n
tr
ac
t
m
ec
h
an
is
m
s
au
to
m
at
e
r
ec
y
clin
g
r
ewa
r
d
s
a
n
d
o
p
er
atio
n
al
p
er
m
is
s
io
n
s
.
R
o
u
te
o
p
tim
izatio
n
m
o
d
els
d
e
m
o
n
s
tr
ated
a
1
5
% r
ed
u
ctio
n
i
n
f
leet
s
ize
a
n
d
u
p
to
2
2
%
r
ed
u
ctio
n
in
tr
av
el
d
is
tan
ce
[
2
6
]
.
T
o
k
e
n
-
b
ased
in
ce
n
tiv
e
s
y
s
tem
s
en
co
u
r
a
g
e
citi
ze
n
p
ar
ticip
atio
n
in
r
ec
y
clin
g
p
r
o
g
r
am
s
,
s
u
p
p
o
r
tin
g
cir
cu
lar
ec
o
n
o
m
y
o
b
jectiv
es
[
2
7
]
.
3
.
3
.
AI
-
driv
en
s
o
rt
ing
,
ro
bo
t
ics,
a
nd
circ
ula
r
ec
o
no
m
y
Ar
tific
ial
in
tellig
en
ce
s
ig
n
if
ican
tly
en
h
a
n
ce
s
s
o
r
tin
g
p
r
ec
is
io
n
an
d
au
to
m
atio
n
ef
f
icien
cy
.
co
n
v
o
l
u
tio
n
al
n
eu
r
al
n
etwo
r
k
s
(
C
NNs)
s
u
ch
as
I
n
ce
p
tio
n
-
R
esNet
V2
an
d
VGG
-
1
6
ac
h
iev
e
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if
icatio
n
ac
cu
r
ac
ies
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ce
ed
in
g
9
5
%
o
n
lar
g
e
d
atasets
o
f
1
0
,
0
0
0
–
1
3
,
0
0
0
im
ag
e
s
[
2
8
]
.
C
o
m
p
ar
ed
to
tr
ad
itio
n
al
m
ac
h
in
e
lear
n
in
g
m
o
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els,
C
NN
-
b
ased
s
y
s
tem
s
:
a.
I
m
p
r
o
v
e
ac
cu
r
ac
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b
y
1
0
%
–
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2
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R
ed
u
ce
m
is
class
if
icatio
n
r
ates
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y
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p
to
1
5
%
[
2
9
]
I
n
d
u
s
tr
ial
r
o
b
o
tic
p
latf
o
r
m
s
i
n
teg
r
atin
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m
u
lti
-
s
en
s
o
r
f
u
s
io
n
(
R
GB
,
NI
R
,
VI
S,
an
d
m
etal
d
etec
tio
n
)
en
ab
le
h
ig
h
-
ac
cu
r
ac
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d
u
s
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ial
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ca
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r
o
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ed
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cin
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m
an
u
al
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o
r
tin
g
d
ep
e
n
d
en
c
y
an
d
im
p
r
o
v
in
g
m
ater
ial
r
ec
o
v
e
r
y
.
Ma
ter
ial
r
ec
o
v
er
y
f
ac
ilit
i
es
(
MRF
s
)
in
teg
r
atin
g
p
r
o
g
r
am
m
ab
le
lo
g
ic
co
n
tr
o
ller
(
PLC
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-
co
n
tr
o
lled
s
o
r
tin
g
s
y
s
tem
s
d
em
o
n
s
tr
ate
class
if
icat
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n
p
r
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is
io
n
a
b
o
v
e
9
8
%,
s
u
r
p
ass
in
g
m
an
u
al
m
eth
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d
s
in
co
n
s
is
ten
cy
a
n
d
o
p
er
atio
n
al
s
af
ety
[
3
0
]
,
[
3
1
]
.
T
o
g
eth
er
,
AI
-
d
r
iv
en
r
o
b
o
tics
an
d
au
to
m
ated
c
o
n
tr
o
l
s
y
s
tem
s
s
ig
n
if
ican
tly
co
n
tr
i
b
u
te
to
cir
cu
lar
ec
o
n
o
m
y
p
er
f
o
r
m
an
ce
in
d
icato
r
s
b
y
in
cr
ea
s
in
g
r
ec
o
v
e
r
y
ef
f
icien
cy
an
d
r
ed
u
cin
g
lan
d
f
i
ll d
ep
en
d
e
n
cy
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2722
-
2
5
8
6
I
n
teg
r
a
tin
g
a
r
tifi
cia
l in
tellig
en
ce
a
n
d
I
n
tern
et
o
f Th
i
n
g
s
fo
r
s
o
lid
w
a
s
te
ma
n
a
g
eme
n
t
…
(
A
d
itya
K
a
r
le
)
393
3
.
4
.
E
m
er
g
ing
wa
s
t
e
-
to
-
ener
g
y
a
nd
co
nv
er
s
io
n t
ec
hn
o
lo
g
ies
B
ey
o
n
d
s
o
r
tin
g
an
d
m
o
n
ito
r
i
n
g
,
em
er
g
i
n
g
waste
co
n
v
er
s
i
o
n
tech
n
o
lo
g
ies
im
p
r
o
v
e
s
u
s
tain
ab
ilit
y
o
u
tco
m
es.
Ph
y
s
ico
ch
em
ical
an
d
b
io
lo
g
ical
co
n
v
er
s
io
n
m
eth
o
d
s
,
in
clu
d
in
g
tr
an
s
ester
if
icatio
n
an
d
f
er
m
en
tatio
n
,
ac
h
iev
e
co
n
v
er
s
io
n
ef
f
icien
cies
b
etwe
en
8
5
%
an
d
9
0
%
u
n
d
er
o
p
tim
ize
d
co
n
d
itio
n
s
[
3
2
]
.
Ad
v
an
ce
d
e
n
er
g
y
r
ec
o
v
er
y
te
ch
n
o
lo
g
ies
s
u
ch
as
tr
ib
o
elec
tr
ic
n
an
o
g
en
er
ato
r
s
(
T
E
NGs)
an
d
m
icr
o
b
ial
f
u
el
ce
lls
(
MFC
s
)
u
tili
ze
waste’
s
elec
tr
o
ch
em
ical
p
o
ten
tial
f
o
r
r
en
ewa
b
le
en
er
g
y
g
e
n
er
atio
n
[
3
3
]
.
T
h
ese
ap
p
r
o
ac
h
es su
p
p
o
r
t w
aste
-
to
-
r
eso
u
r
ce
tr
an
s
itio
n
s
an
d
r
ed
u
ce
en
v
ir
o
n
m
en
tal
b
u
r
d
e
n
.
3
.
5
.
M
un
icipa
l
-
s
ca
le
s
m
a
rt
wa
s
t
e
s
y
s
t
em
s
C
ity
-
lev
el
s
m
ar
t
waste
m
an
ag
em
en
t
in
teg
r
ates
AI
,
I
o
T
,
an
d
clo
u
d
an
aly
tics
to
o
p
tim
ize
m
u
n
icip
al
o
p
er
atio
n
s
.
Sm
ar
t
g
ar
b
ag
e
b
i
n
s
(
SGB
s
)
eq
u
ip
p
ed
with
e
m
b
ed
d
e
d
s
en
s
o
r
s
r
ed
u
ce
o
v
e
r
f
lo
w
in
cid
en
ts
b
y
ap
p
r
o
x
im
ately
4
0
%
[
3
4
]
.
Mu
n
icip
al
-
s
ca
le
im
p
lem
en
tatio
n
s
d
em
o
n
s
tr
ate:
a.
18
%
–
2
2
% r
e
d
u
ctio
n
i
n
f
u
el
c
o
n
s
u
m
p
tio
n
b.
1
5
% r
ed
u
ctio
n
in
c
o
llectio
n
f
r
eq
u
en
cy
c.
I
m
p
r
o
v
ed
em
is
s
io
n
m
o
n
ito
r
in
g
[
3
5
]
C
o
m
m
u
n
icatio
n
p
r
o
to
co
ls
s
u
ch
as
r
ad
io
f
r
eq
u
en
c
y
id
en
tific
a
tio
n
(
R
FID
)
,
Z
ig
B
ee
,
B
lu
eto
o
th
,
an
d
L
T
E
en
ab
le
r
ea
l
-
tim
e
r
esp
o
n
s
iv
en
ess
b
etw
ee
n
b
in
s
an
d
co
n
tr
o
l
ce
n
ter
s
.
3
.
6
.
T
ec
hn
o
lo
g
ica
l,
ec
o
no
m
i
c,
a
nd
s
o
cia
l ba
rr
iers
Desp
ite
m
ea
s
u
r
ab
le
im
p
r
o
v
e
m
en
ts
,
lar
g
e
-
s
ca
le
d
ep
l
o
y
m
en
t
r
em
ain
s
co
n
s
tr
ain
ed
b
y
m
u
lti
p
le
f
ac
to
r
s
.
T
ec
h
n
o
lo
g
ical
b
a
r
r
ier
s
in
clu
d
e
s
en
s
o
r
ca
lib
r
atio
n
co
s
ts
,
s
y
s
tem
in
ter
o
p
er
ab
ilit
y
is
s
u
es,
an
d
cy
b
e
r
s
ec
u
r
ity
co
n
ce
r
n
s
.
E
co
n
o
m
ic
co
n
s
tr
ai
n
ts
in
d
ev
elo
p
in
g
r
eg
i
o
n
s
lim
it
in
v
estme
n
t
in
ad
v
an
ce
d
h
ar
d
war
e
an
d
clo
u
d
in
f
r
astru
ctu
r
e
[
3
6
]
.
So
cial
r
esis
tan
ce
-
o
f
ten
d
escr
ib
ed
as
th
e
“
n
o
t
in
m
y
b
ac
k
y
ar
d
”
(
NI
MBY)
ef
f
ec
t
-
co
n
tin
u
es
to
d
elay
in
f
r
astru
ctu
r
e
p
r
o
ject
s
an
d
r
ec
y
clin
g
f
ac
ilit
y
ex
p
an
s
io
n
[
3
7
]
.
Ad
d
itio
n
ally
,
lim
ited
d
ig
ital
liter
ac
y
an
d
p
u
b
lic
awa
r
en
ess
r
ed
u
ce
ad
o
p
tio
n
r
ates
o
f
s
m
ar
t
s
y
s
tem
s
.
Ov
er
co
m
in
g
th
ese
b
a
r
r
ier
s
r
eq
u
ir
es
p
o
licy
r
ef
o
r
m
,
f
in
an
cial
in
ce
n
tiv
es,
p
u
b
lic
–
p
r
iv
ate
p
ar
tn
er
s
h
ip
s
,
a
n
d
s
tan
d
ar
d
izatio
n
o
f
waste
m
an
a
g
em
en
t
p
r
o
to
c
o
ls
.
3
.
7
.
Sy
nthesis
o
f
perf
o
r
m
a
n
ce
im
pro
v
e
m
ent
s
Acr
o
s
s
th
e
r
ev
iewe
d
liter
atu
r
e,
in
teg
r
ated
AI
-
I
o
T
s
y
s
tem
s
co
n
s
is
ten
tly
d
em
o
n
s
tr
ate:
a.
C
las
s
if
icatio
n
ac
cu
r
ac
y
u
p
to
9
5
%
b.
20
%
-
2
5
%
o
p
er
atio
n
al
ef
f
icie
n
cy
im
p
r
o
v
em
e
n
t
c.
15
%
-
2
2
% f
u
el
co
n
s
u
m
p
tio
n
r
ed
u
ctio
n
d.
30
%
-
4
0
% im
p
r
o
v
e
m
en
t in
w
o
r
k
er
s
af
ety
e.
E
n
h
an
ce
d
tr
ac
ea
b
ilit
y
an
d
cir
c
u
lar
ec
o
n
o
m
y
c
o
m
p
lian
ce
T
h
e
in
teg
r
atio
n
o
f
AI
,
I
o
T
,
cl
o
u
d
c
o
m
p
u
tin
g
,
a
n
d
b
l
o
ck
ch
a
in
tr
an
s
f
o
r
m
s
waste
m
an
a
g
e
m
en
t
f
r
o
m
a
lab
o
r
-
in
ten
s
iv
e
p
r
o
ce
s
s
in
to
an
in
tellig
en
t c
y
b
er
-
p
h
y
s
ical
s
y
s
tem
alig
n
ed
with
I
n
d
u
s
tr
y
5
.
0
p
r
in
ci
p
les.
4.
CO
NCLU
SI
O
N
AND
F
U
T
U
RE
SCO
P
E
T
h
is
r
ev
iew
s
y
s
tem
atica
lly
e
x
am
in
ed
r
ec
en
t
a
d
v
an
ce
m
en
t
s
in
Ar
tific
ial
I
n
tellig
en
ce
(
AI
)
an
d
I
o
T
tech
n
o
lo
g
ies
ac
r
o
s
s
th
e
s
o
lid
waste
m
an
ag
em
en
t
life
cy
cle,
f
r
o
m
s
eg
r
eg
atio
n
an
d
m
o
n
it
o
r
in
g
to
a
u
to
m
ated
p
r
o
ce
s
s
in
g
an
d
r
eso
u
r
ce
r
ec
o
v
er
y
.
T
h
e
a
n
aly
s
is
r
ev
ea
ls
th
at
AI
-
d
r
iv
e
n
class
if
icatio
n
an
d
I
o
T
-
e
n
ab
led
m
o
n
ito
r
in
g
s
ig
n
if
ican
tly
en
h
a
n
ce
s
o
r
tin
g
ac
cu
r
ac
y
,
o
p
er
ati
o
n
al
ef
f
icien
cy
,
an
d
d
ata
-
d
r
iv
en
d
ec
is
io
n
-
m
ak
in
g
co
m
p
ar
ed
to
co
n
v
en
tio
n
al
waste
m
an
ag
em
en
t
p
r
ac
ti
ce
s
.
Ho
wev
er
,
a
clea
r
g
ap
p
er
s
is
ts
b
etwe
en
lab
o
r
ato
r
y
-
s
ca
le
p
r
o
to
ty
p
es
an
d
lar
g
e
-
s
ca
le
in
d
u
s
tr
ial
d
ep
lo
y
m
e
n
t.
W
h
ile
h
ig
h
-
p
e
r
f
o
r
m
a
n
ce
r
esu
lts
ar
e
f
r
eq
u
en
tly
r
ep
o
r
ted
u
n
d
er
co
n
tr
o
lled
co
n
d
itio
n
s
,
s
tan
d
ar
d
ized
b
en
c
h
m
ar
k
in
g
,
lo
n
g
-
ter
m
r
eliab
ilit
y
ass
ess
m
en
t,
a
n
d
ec
o
n
o
m
ic
f
ea
s
ib
ilit
y
an
al
y
s
es
r
em
ain
lim
ited
.
I
n
p
ar
ticu
lar
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Evaluation Warning : The document was created with Spire.PDF for Python.