Advances in computer and electrical engineering book series,
Год журнала:
2024,
Номер
unknown, С. 383 - 414
Опубликована: Окт. 23, 2024
This
chapter
explores
how
AI
and
smart
technologies
could
altogether
be
integrated
to
bring
revolutionary
change
in
the
fields
of
disaster
forecasting
management.
It
will
try
analyze
through
advanced
algorithms
IoT
sensors
these
can
potentially
advance
a
disaster-related
prediction
along
with
accuracy
timeliness.
Important
applications
real-time
data
collection,
predictive
modeling,
automated
alerts
collectively
enhance
response
strategies
as
well
resource
allocation.
chapter's
discussion
promise
merged
technologies—improved
predictiveness,
faster
times,
better
risk
assessment—perhaps
weighs
potential
liabilities
limitations
such
applications,
including
privacy
issues
infrastructures
sturdy
enough
host
system.
draws
on
case
studies
continuing
research
into
use
AI-driven
systems
disasters
present
insights
about
they
are
changing
practices
management
outline
future
directions
for
emerging
field.
Advances in computer and electrical engineering book series,
Год журнала:
2024,
Номер
unknown, С. 79 - 110
Опубликована: Окт. 23, 2024
This
chapter
investigates
the
integration
aspects
between
Internet
of
Things
and
deep
learning
technologies
in
efforts
directed
toward
advancing
food
quality
monitoring,
thus
enhancing
issues
safety
freshness
supply
chain.
IoT
sensors
capture
real-time
data
with
regard
to
environmental
conditions
including
temperature,
humidity,
gas
composition
all
through
production
process.
Such
is
analyzed
by
algorithms
detect
any
kind
anomalies
predict
potential
hazards
enable
proactive
actions
timely
intervention.
The
deals
some
devices
used
for
namely
smart
wearable
technologies,
while
comparing
application
models
predictive
pattern
recognition
analytics.
Case
studies
underscore
this
integrated
approach
reducing
spoilage,
increasing
shelf
life,
meeting
requirements
put
forth
today's
standards.
Advances in medical technologies and clinical practice book series,
Год журнала:
2024,
Номер
unknown, С. 25 - 60
Опубликована: Сен. 14, 2024
The
chapter
discusses
the
integration
of
artificial
intelligence
(AI)
in
healthcare,
highlighting
its
potential
drug
discovery
and
development.
It
emphasizes
AI-driven
methodologies
for
target
identification,
compound
screening,
lead
optimization,
while
ensuring
data
security
compliance
with
privacy
regulations.
explores
use
machine
learning
algorithms
like
deep
reinforcement
predicting
efficacy,
safety
profiles,
personalized
treatment,
also
discussing
ethical
challenges
utilizing
vast
datasets
importance
anonymization
techniques.
AI
discovery,
impact
on
time
cost
reduction.
suggests
that
by
balancing
innovation
strict
measures,
can
improve
patient
outcomes
streamline
development
processes.
provides
insights
into
current
trends
future
directions.
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 computational intelligence and robotics book series,
Год журнала:
2024,
Номер
unknown, С. 329 - 366
Опубликована: Сен. 27, 2024
The
chapter
discusses
the
need
for
efficient
energy
consumption
in
high-performance
computing
systems
and
proposes
integration
of
artificial
intelligence
machine
learning
techniques
to
optimize
efficiency.
It
explores
AI-driven
like
reinforcement
learning,
neural
networks,
predictive
analytics
energy-aware
scheduling,
workload
allocation,
adaptive
power
management.
effectiveness
optimization
strategies
real-world
HPC
infrastructures,
highlighting
potential
savings
while
maintaining
computational
performance.
also
future
directions
challenges
AI-enabled
smart
management,
including
algorithm
refinement,
with
emerging
technologies,
scalability
considerations.
holistic
approach
highlights
transformative
impact
AI
ML
creating
sustainable,
energy-efficient
paradigms
within
ecosystems.
Advances in computer and electrical engineering book series,
Год журнала:
2024,
Номер
unknown, С. 351 - 382
Опубликована: Окт. 23, 2024
AI-controlled
robotics
in
smart
agriculture
systems
have
revolutionized
farming
practices
by
improving
precision,
sustainability,
and
productivity,
marking
a
significant
milestone
modern
farming.
AI
allows
real-time
monitoring
decision-making
through
advanced
machine
learning
algorithms,
sensors,
autonomous
to
optimize
resources
like
water,
fertilizers,
pesticides.
AI-based
technologies
are
revolutionizing
precision
agriculture,
reducing
waste
environmental
degradation
while
increasing
yield
quality.
Robotics
is
automating
labor-intensive
tasks
planting,
harvesting,
weeding
not
only
for
efficiency
but
also
reduce
human
intervention.
enables
predictive
analytics
disease
detection
weather
forecasting,
providing
farmers
with
actionable
inputs
at
their
doorstep.
The
chapter
delves
into
the
potential
of
robots
highlighting
improve
food
security,
mitigate
harm,
foster
sustainable
practices.
Advances in computer and electrical engineering book series,
Год журнала:
2024,
Номер
unknown, С. 437 - 466
Опубликована: Дек. 13, 2024
This
chapter
delves
into
how
HPC
can
be
integrated
with
robotics
and
electronics
to
come
up
smarter
food
packaging
systems
that
improve
product
quality
more
efficaciously.
As
consumers
become
ever
demanding
about
freshness
safety,
the
task
facing
traditional
methods
is
monumental
in
maintaining
of
packaged
goods.
The
enormous
amount
data
analyzed
real-time
by
will
subsequently
enhance
processes
while
improving
decision-making.
Robotics
takes
automation
process
a
step
further
packaging,
providing
greater
assurance
now
precision,
speed,
decreased
human
error.
In
addition,
electronic
sensors
advance
sensing
technology
monitor
environmental
conditions
provide
critical
for
optimal
integrity.
synergistic
effect
this
not
only
makes
operations
smoother
but
also
decreases
waste
enhances
sustainability
packaging.
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 chemical and materials engineering book series,
Год журнала:
2024,
Номер
unknown, С. 351 - 379
Опубликована: Июнь 28, 2024
The
increasing
digital
landscape
necessitates
responsible
management
of
electronic
waste
(e-waste),
and
traditional
disposal
methods
pose
environmental
health
risks.
Biomanufacturing,
a
process
using
biological
systems
organisms,
offers
sustainable
alternative
for
managing
e-waste.
By
bio-based
products
from
renewable
resources
like
plant-based
materials
microbial
enzymes,
biomanufacturing
greener
way
to
recycle
repurpose
devices.
This
chapter
explores
e-waste
management,
focusing
on
component
disassembly
separation,
their
effectiveness
in
recovering
metals,
reducing
pollution,
treating
hazardous
contaminants.
study
also
discusses
the
economic
regulatory
implications
adopting
biomanufacturing,
its
feasibility
recycling
infrastructures,
potential
revenue
streams
circular
economy.
Practice, progress, and proficiency in sustainability,
Год журнала:
2024,
Номер
unknown, С. 231 - 262
Опубликована: Июнь 28, 2024
This
chapter
explores
the
relationship
between
digitalization,
IoT,
and
sustainable
energy,
highlighting
their
potential
in
transforming
energy
landscape,
driving
efficiency,
enabling
smarter
management.
It
discusses
role
of
data
analytics,
AI,
machine
learning
optimizing
systems,
enhancing
predictive
maintenance,
demand-side
The
also
addresses
cybersecurity
risks
privacy
concerns
implementing
digital
solutions.
calls
for
collaboration
among
stakeholders
to
foster
innovation
accelerate
solutions
adoption.
policy
frameworks
incentivize
investment
infrastructure
IoT-enabled
devices.
concludes
by
offering
recommendations
policymakers,
industry
leaders,
researchers
utilize
technologies
a
equitable
future.
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.
