Advances in computational intelligence and robotics book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 179 - 200
Published: Sept. 20, 2024
This
study
examines
the
profound
influence
of
artificial
intelligence
(AI)
on
sports
industry,
including
its
effects
games,
training
methods,
fan
involvement,
and
player
well-being.
text
explores
how
is
transforming
several
aspects
industry
by
analysing
current
trends
future
predictions.
AI-powered
intelligent
referees
are
being
developed
to
enhance
fairness
accuracy
refereeing,
while
personalised
experiences
created
increase
spectator
engagement.
Furthermore,
implementation
health
aid
virtual
reality
environments
expected
performance
raise
safety
standards.
The
integration
technology
athleticism
in
has
potential
revolutionise
field
AI,
creating
a
mutually
beneficial
connection
between
innovation
human
accomplishment.
will
ultimately
improve
whole
experience
for
everyone
involved.
Advanced Functional Materials,
Journal Year:
2024,
Volume and Issue:
unknown
Published: June 8, 2024
Abstract
Diverging
from
air
breakdown‐based
triboelectric
nanogenerators
(TENGs),
recent
TENG
designs
present
high
output
power
density
without
requiring
precise
control
over
discharge
channels.
However,
existing
researches
predominantly
ascribe
its
direct
current
to
electrostatic
induction,
disregarding
the
critical
factor
of
charge
leakage.
This
oversight
hampers
efforts
improve
device
performance,
especially
in
material
selection
and
optimization.
Here,
generation
signals
ultimately
stems
leakage
spatial
induction
is
illustrated.
Through
theoretical
analysis,
visualization,
experimental
measurement
four
phenomena
device,
a
quadruple‐effect
mechanoelectrical
conversion
mechanism
established
refine
rule.
Under
this
guideline,
increased
by
34.42%
contrast
TENG.
For
practical
applications,
management
circuit
utilized
boost
device's
charging
rate
up
18
times.
Furthermore,
voltage
can
activate
discharge‐type
UV
tubes,
demonstrating
great
potential
developing
self‐powered
wastewater
treatment
systems.
The
multiple
behaviors
proposed
work,
along
with
rule,
lay
solid
foundation
for
achieving
TENGs.
Nature Communications,
Journal Year:
2025,
Volume and Issue:
16(1)
Published: Jan. 27, 2025
The
takeover
issue,
especially
the
setting
of
time
budget,
is
a
critical
factor
restricting
implementation
and
development
conditionally
automated
vehicles.
general
fixed
budget
has
certain
limitations,
as
it
does
not
take
into
account
driver's
non-driving
behaviors.
Here,
we
propose
an
intelligent
assistance
system
consisting
all-round
sensing
gloves,
behavior
identification
module,
determination
module.
All-round
gloves
based
on
triboelectric
sensors
seamlessly
detect
delicate
motions
hands
interactions
between
other
objects,
then
transfer
electrical
signals
to
which
achieves
accuracy
94.72%
for
six
Finally,
combining
result
its
corresponding
minimum
obtained
through
our
dynamically
adjusts
current
behavior,
significantly
improving
performance
in
terms
safety
stability.
Our
work
presents
potential
value
application
In
this
work,
authors
develop
electronic
Conditionally
Automated
Vehicles
that
adjust
drivers
have
control
real-time
behaviours
Advanced Functional Materials,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 19, 2025
Abstract
With
rapid
advancement
in
the
field
of
smart
technology,
reshapeable
devices
have
garnered
widespread
interest.
Liquid‐free
flexible
materials
eliminate
risk
leakage
thus
enhancing
user
safety
along
with
being
recyclable.
However,
poor
network
fluidity
and
difficulty
fully
disconnecting
cross‐links
limited
its
potential
as
a
device.
In
this
work,
silver
nanoparticles
(AgNPs)
are
doped
into
physically
cross‐linked
dynamic
linear
polydimethylsiloxane
(PIAU)
to
develop
closed‐loop
recyclable
high‐dielectric
nanocomposite.
This
nanocomposite
exhibits
moderate
elastoviscosity‐transition
temperature
spatial
remodelability
based
on
multiple
types
reversible
hydrogen
bonds
S─Ag
bonds.
AgNPs
sprayed
surface
form
conductive
coating
stabilized
by
at
polymer‐nano
interface.
Based
refined
assembly,
an
antibacterial
triboelectric
nanogenerator
(TENG)
is
developed
applied
high‐precision
insole.
The
insole
16
TENG
sensors,
resulting
simplified
system
that
employs
machine
learning
(ML)
for
personalized
motion
monitoring,
including
recognition
gait
classification.
Five
algorithm
models
ensure
high
accuracy
enable
it
further
expand
abnormal
alarm
system.
work
presents
new
reliable
environmentally
friendly
strategy
design
high‐performance
sustainable
devices.
physica status solidi (a),
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 23, 2025
Gait
tracking
plays
a
crucial
role
in
postoperative
rehabilitation
training
by
facilitating
the
assessment
of
recovery
progress
and
ensuring
timely
interventions
to
improve
outcomes.
Herein,
flexible
wearable
droplet‐solid‐mode
triboelectric
foot
sensor
(DTFS)
array
is
reported
for
monitoring
training.
The
conventional
solid–solid
contact
interface
replaced
with
solid–liquid
interface,
avoiding
material
wear
degradation
output.
Additionally,
three
interconnected
DTFS
cells
are
integrally
molded
using
3D
printing
technology.
Results
demonstrate
that
DTFS's
output
voltage
amplitude
varies
applied
frequency
acceleration,
providing
reliable
stable
responses
external
stimuli.
When
attached
heel
an
insole,
array,
its
compact
design
configuration,
produces
distinct
electrical
signals
under
different
gaits
enhanced
data
collection
efficiency.
Using
artificial
intelligence
algorithms
analysis,
system
enables
real‐time
automated
gait
high
recognition
accuracy
exceeding
96%.
This
innovative
solution
holds
promise
continuous
tracking,
supports
doctors’
decision‐making
data‐driven
insights,
paves
way
patients’
home
healthcare
through
integration
wireless
transmission
systems
near
future.
