Advances in business strategy and competitive advantage book series,
Год журнала:
2024,
Номер
unknown, С. 413 - 444
Опубликована: Сен. 27, 2024
This
chapter
examines
the
intersection
of
technology
and
employment,
focusing
on
how
to
use
technological
advances
overcome
inherent
employment
biases.
It
deeply
biases
that
impact
decision-making
organizational
culture,
presenting
innovative
solutions
such
as
artificial
intelligence,
machine
learning,
data
analytics
help
identify
mitigate
these
biases,
ideas,
improve
working
conditions.
Additionally,
it
includes
potential
for
future
emerging
products
technologies
drive
innovation
inclusion
in
business.
Advances in mechatronics and mechanical engineering (AMME) book series,
Год журнала:
2024,
Номер
unknown, С. 352 - 383
Опубликована: Июль 26, 2024
Transitioning
to
electric
vehicles
(EVs)
can
significantly
reduce
environmental
and
social
impacts,
improve
air
quality,
enhance
equity,
with
higher
energy
efficiency
when
integrated
renewable
sources.
Electric
urban
quality
by
reducing
pollutants,
respiratory
cardiovascular
diseases,
enhancing
the
of
life
in
areas
through
quieter
operation.
are
gaining
popularity
due
their
benefits,
such
as
improved
public
health,
economic
opportunities,
potential
address
equity
issues.
The
chapter
explores
necessity
charging
infrastructure,
sustainable
battery
materials,
consumer
adoption
barriers
for
transitioning
a
transportation
system,
suggesting
solutions
policies
innovative
technologies.
highlights
transformative
impact
on
sustainability
that
leveraging
advantages
lead
cleaner,
healthier,
more
equitable
future.
Advances in computational intelligence and robotics book series,
Год журнала:
2025,
Номер
unknown, С. 379 - 400
Опубликована: Фев. 7, 2025
The
integration
of
5G
and
cloud
computing
with
electric
vehicles
has
transformative
potential
to
improve
the
energy
efficiency
performance
vehicles.
This
chapter
emphasizes
integrating
high-speed
connectivity
from
vast
computational
power
take
advantage
optimizing
EV
systems
-
focusing
on
real-time
data
analysis,
predictive
maintenance,
dynamic
management.
enables
seamless
communication
between
EVs,
infrastructure,
platforms,
ensuring
efficient
route
planning,
battery
management,
conservation.
By
leveraging
computing,
EVs
can
access
advanced
analytics
machine
learning
algorithms
for
usage,
extending
life,
enhancing
overall
performance.
These
technologies
converge
present
world
smarter,
more
sustainable
options
regarding
mobility,
contributing
conservation
reduced
carbon
emissions.
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 229 - 250
Опубликована: Апрель 4, 2025
The
chapter
presents
a
comprehensive
cybersecurity
framework
for
protecting
connected
vehicles
in
the
context
of
evolving
intelligent
transportation
systems
(ITS).
It
examines
various
cyber-attacks
targeting
vehicle
communication
networks,
autonomous
driving
systems,
and
data
integrity.
This
addresses
risk
management,
encryption
protocols,
authentication
methods,
intrusion
detection
automotive
domain.
also
covers
completeness
integration
Cybersecurity
Measures
within
existing
ITS
infrastructures
provides
recommended
practices
that
enable
secure
exchange
information
over
V2V
networks
V2I
networks.
means
mitigating
emerging
security
risks
providing
healthy,
resilient
environment.
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 579 - 598
Опубликована: Апрель 4, 2025
This
chapter
explores
the
use
of
IoT-enabled
ITS
technologies
to
optimize
urban
transport,
reduce
fuel
consumption,
and
decrease
greenhouse
gas
emissions.
can
enable
dynamic
traffic
management,
predictive
maintenance,
efficient
route
planning
by
using
real-time
data
from
connected
sensors,
vehicles,
infrastructure.
Furthermore,
paper
explains
imminent
innovations
like
autonomous
intelligent
parking,
vehicle-to-everything
(V2X)
communication
how
they'll
contribute
more
sustainable
transportation.
We
also
explore
definition
IoT-ITS
challenges
implementing
IoT-ITS:
security,
interoperability,
scalability,
demonstrate
potential
in
enabling
a
greener
city.
It
focused
on
future
perspectives
some
case
studies
regarding
IoT-ITS,
for
emission
reduction
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 51 - 70
Опубликована: Апрель 4, 2025
AI-powered
smart
traffic
management
changes
the
intelligent
transportation
systems
with
optimized
urban
growth,
reduces
congestion,
and
increases
safety
on
roads
through
adoption
of
advanced
technologies
such
as
machine
learning,
computer
vision,
timing
using
real
internal
data
analysis.
Thus,
AI
provides
dynamic
in
traffic,
prediction
for
maintenance,.
facilitates
effective
incident
response.
The
chapter
explores
integration
into
signal
optimization,
autonomous
vehicle
programming,
adaptive
maneuvers.
It
encompasses
key
highlights,
including
predictive
analytics
forecasting
connected
IoT
devices
that
will
enable
to
communicate
seamlessly
between
businesses
vehicles
well
reduction
emissions
environmentally
friendly
solutions
traffic.
Practical
aspects
challenges
usage
are
brought
case
studies
from
cities
infrastructures.
Advances in mechatronics and mechanical engineering (AMME) book series,
Год журнала:
2024,
Номер
unknown, С. 248 - 281
Опубликована: Июль 26, 2024
Edge
computing
and
machine
learning
technologies
have
significantly
improved
electric
vehicle
(EV)
performance,
enhancing
efficiency,
reliability,
user
experience
by
processing
data
closer
to
the
vehicle,
reducing
latency,
conserving
bandwidth.
In
this
chapter,
algorithms
in
EV
edge
infrastructure
analysis
been
used
for
predictive
analytics
optimization,
predicting
battery
life,
optimizing
energy
consumption,
identifying
potential
failures,
downtime.
This
chapter
also
illustrates
management
systems
(BMS)
using
advanced
techniques
monitor
health,
predict
degradation,
optimize
charging
cycles,
enable
real-time
decision-making
autonomous
driving,
safety
preventing
overcharging.
The
practical
challenges
of
integrating
ML
vehicles
(EVs),
highlighting
privacy,
security,
requirements,
are
elaborated
improve
performance.
Advances in mechatronics and mechanical engineering (AMME) book series,
Год журнала:
2024,
Номер
unknown, С. 157 - 178
Опубликована: Июль 26, 2024
The
global
EV
market
is
rapidly
expanding
due
to
technological
advancements,
environmental
concerns,
and
changing
consumer
preferences.
This
chapter
examines
behavior,
focusing
on
factors
like
awareness,
economic
considerations,
affinity.
Consumers
prioritize
sustainability,
with
cost,
government
incentives,
fuel
savings
driving
adoption.
Technological
advancements
enhance
battery
efficiency
charging
infrastructure.
explores
demographic
differences
in
adoption,
highlighting
younger,
tech-savvy
consumers,
urban
dwellers'
higher
adoption
rates,
while
also
examining
the
impact
of
social
norms
peer
behavior.
marketing
strategies
for
market,
benefits,
cost
savings,
digital
platforms,
discussing
future
challenges
opportunities.
Advances in mechatronics and mechanical engineering (AMME) book series,
Год журнала:
2024,
Номер
unknown, С. 384 - 414
Опубликована: Июль 26, 2024
The
automotive
and
energy
industries
will
undergo
a
revolution
with
the
integration
of
edge
computing,
storage
systems,
grid
in
electric
vehicles
(EVs)
to
improve
efficiency
sustainability.
In
(EVs),
computing
improves
data
processing
by
cutting
down
on
latency
bandwidth
utilization,
allowing
for
real-time
management
decision-making,
optimizing
battery
consumption
distribution.
Energy
systems
(ESS),
which
provide
flexibility
bidirectional
flow,
are
essential
EV
management.
V2G
technology
supports
stability
streamlines
exchange
procedures
integrating
ESS
infrastructure.
this
chapter,
strategic
advantages
EVs
examined,
an
emphasis
practical
applications'
cost
savings,
environmental
effects,
operational
efficiency.
Advances in civil and industrial engineering book series,
Год журнала:
2024,
Номер
unknown, С. 27 - 54
Опубликована: Авг. 26, 2024
The
application
of
the
Internet
Things
(IoT)
and
machine
learning
to
enhance
intelligent
discovery
procedures
in
IoT-enabled
environments
has
been
covered
this
chapter.
It
draws
attention
how
algorithms
would
address
these
issues
shows
traditional
approaches
are
inefficient
when
dealing
with
massive
amounts
data
created
by
IoT
devices
sensors.
also
highlights
crucial
feature
engineering,
model
selection,
assessment
metrics
development
learning-driven
systems.
privacy,
algorithm
bias,
security
flaws
have
described.
chapter
covers
real-world
use
ML
sectors
including
manufacturing,
transportation,
healthcare,
agriculture.
integration
infrastructure
discussed
new
possibilities
for
innovation,
optimization,
decision-making.
Advances in civil and industrial engineering book series,
Год журнала:
2024,
Номер
unknown, С. 99 - 130
Опубликована: Авг. 26, 2024
Efficiency,
security,
and
transparency
have
been
improved
by
the
smart
grid
energy
management
system's
combination
of
IoT
blockchain
technologies.
Real-time
data
is
collected
devices,
safe
transactions
are
recorded
in
a
decentralized
ledger
using
blockchain.
In
this
chapter,
important
elements
discussed
with
distributed
ledgers,
meters,
sensors.
Demand
response,
integration
renewable
sources,
resilience
enhanced
successful
implementations.
Issues
related
to
interoperability,
privacy,
scalability
tackled.
The
use
AI
ML
management,
demand
forecasting,
anomaly
detection
also
described
chapter.
