►
Description
Date: 05/04/18
Presenter: Jen Duthie
Institution: City of Austin, TX
South Big Data Hub
A
And
we'll
start
off
with
talk
here
from
Jim
Duffy
nun
Jennifer
a
few
years
now.
She
originally
was
at
the
Center
for
transportation
research
here
at
the
University
of
Texas
in
Austin,
where
we
did
a
lot
of
interesting
things,
both
with
traffic
flow
simulated
as
well
as
beginning
to
build
what
she
called
the
dinner
rodeo
for
all
the
different
data
and
transportation
entities
here
in
the
city
who
hopefully
someday,
pull
all
the
data
together
and
make
make
for
a
more
unified
and
more
data-driven
system.
A
B
B
So
part
of
that
is
just
a
caveat
that
some
of
what
I'll
talk
about
today.
It's
only
a
small
sampling
of
the
stuff
that
we're
doing
in
this
space,
and
it
definitely
has
a
perspective
coming
from
signal
systems,
because
that's
that's
what
I've
been
working
on.
Mostly,
we
have
a
ton
of
smart
mobility
efforts
happening
in
Austin.
We
just
hired
an
executive
position
in
smart
mobility.
We
just
created
at
the
department
level
a
group
that
will
focus
on
data
and
IT.
B
B
So
we
have
over
400
cameras
around
town,
but
you
know
we
can
only
keep
our
eyes
on
so
many
at
a
time
with
just
a
handful
of
operators
and
we
have
sensors-
and
you
know
it's
a
whole
thing
to
get
the
data
coming
in
and
then
a
whole
other
thing
to
be
able
to
use
the
data.
So
this
is
a
picture
of
the
place
we
like
to
take
people
when
they
come
yeah.
B
So
I
want
to
talk
about
I'll
focus
on
two
things
today.
One
is
the
electronic
tracking
of
assets
and
workflows,
because
that's
an
example
of
how
we're
moving
toward
I
mean
basically
moving
away
from
spreadsheets,
moving
away
from
somebody
filling
out
a
form
by
hand
and
having
technicians
dispatched
electronically
tracking
our
assets
electronically-
and
this
has
been
you
know-
John's
big
effort,
I
guess
over
the
last
year,
I've
been
highly
successful.
B
So
this
is
just
a
snapshot
of
our
data
and
performance
hub.
This
is
public
facing
I
mean
to
the
extent
that
we
can.
We
make
things,
make
data
open
or
open
by
default.
So
you
can
go
here.
It's
transportation,
Austin
Texas,
that
I
go
I.
Think
I
showed
the
link
in
the
next
slide
and
this
changes
and
grows.
You
know
every
every
month,
if
not
every
day,
where
we
add
new
categories
or
refine
new
categories
and
new
tools
within
data
tracker.
B
So
John
I
stole
this
from
one
of
your
slides.
I
hope,
that's
okay,
but
this
is
a
just
basically
how
how
the
system
works.
So
it
has
GIS
components.
It's
linked
to
our
open
data
portal,
there's
the
open
data
and
and
performance
hub
and,
as
I
said,
all
of
this
is
evolving
and
changing,
but
there's
there's
kind
of
two
pieces
to
what
John's
created.
There's
the
open
data
and
performance
hub
and
then
there's
the
the
data
tracker
and
we
can
talk
about
those
systems
in
in
more
detail.
B
But
the
idea
is
that
these
systems
are
providing
value
to
staff
and
that's
really
been
our
focus
is
just
helping
staff
be
more
efficient
and
that's
you
know
not
necessarily
the
the
sexiest
smart
city
application,
but
we
find
a
lot
of
value
in
it.
I'm
just
making
our
staff
having
our
staff,
spend
less
time,
processing,
paperwork
and
scanning
and
really
being
able
to
focus
on
the
job.
They
were
hired
to
do.
B
So
just
some
idea
of
what
we
have
in
terms
of
assets
that
are
generating
data
or
not
generating
data.
We
have
about
a
thousand
traffic
signals
and
most
of
those
we
have
communication
to
so
we
can.
We
communicate
with
them
in
real
time
and
know
if
they're
operating
as
we
expect
them
to
and
if
not,
we
can
diagnose
the
problems
near
sixty
three
pedestrian
signals
over
four
hundred
traffic
monitoring
cameras
that
stream
into
our
traffic
management
center
travel.
B
Sensors
can
be
most
of
those
are
either
Bluetooth
sensors,
where
we
can
get
travel
times
or
radar
sensors
for
getting
traffic
counts.
Those
are,
are
great.
I
can't
say
that
we're
using
that
data
a
lot
yet,
but
but
we
have
those
things
grid.
Smart
is
a
type
of
vehicle
detection,
where
it's
a
fisheye
camera
where
it
helps
our
signal
systems
know
how
many
vehicles
are
approaching
each
leg
of
the
intersection
and
can
adjust
the
signal
timing
accordingly
and
crit
smart
and
there
are
other
vendors
out
there.
B
So
just
one
example
of
one
of
the
dashboards
weary
time
about
a
third
of
our
signals
every
year,
and
so
this
is
a
way
for
public
council
members
leadership
to
look
at
ok.
What
signals
are
we
be
timing
this
year?
Our
main
performance
metric
for
signal.
Retiming
is
change
in
travel
time
and
we
can
have
a
whole
other
webinar.
Just
about
that,
and
you
know
why
that's
not
a
good
performance
metric.
Maybe
it
was
30
years
ago,
but
it's
it's
just
not
anymore.
B
Just
end-to-end
on
the
corridor.
Vehicles
travel
time,
but
anyway,
that's
our
metric
and
the
cities
are
kind
of
slow
to
to
change.
So
we'll
work
on
changing
that,
but
a
lot
of
this
type
of
information,
whether
it's
signal
timing
or
something
else
used
to
live
in
a
spreadsheet
that
was
buried
in
a
file
server
somewhere,
that
only
one
person
knew
how
to
access
or
how
to
interpret.
B
B
We
have
a
relationship
now
with
INRIX.
There
are
a
bunch
of
providers
of
travel
time.
Data
in
Rix's
is
one
of
them.
There's
there's
a
bunch
of
others.
We
ended
up
procuring
in
Rix.
This
is
not
their
interface.
Actually,
they
have
a
very
nice
interface,
where
it's
very
easy
I'm
sitting
in
a
meeting
and
somebody's
talking
about
5th
Street
was
a
big
topic.
The
other
day
we're
talking
about
putting
a
transit
only
lane
on
Fifth,
Street
and
I
was
able
to
just
go
in
and
in
30
seconds,
pull
up.
B
B
You
know
a
lot
of
times,
I
think
we
make
decisions
in
transportation,
probably
many
other
fields.
You
know
without
a
lot
of
just
baseline
data
or
performance
metrics,
so
really
trying
to
kind
of
shift
our
department
to
to
get
there
so
we're
using
this
data
to
analyze
the
impact
of
our
signal
timing
work
we're
using
it
to
look
at
the
impacts
of
special
events.
We
have
a
special
event
just
about
every
day
in
Austin,
it
seems
so
didn't
know
you
know.
Okay,
we
made
a
timing.
Change
was
was
that
impactful?
B
We
did
something
differently
during
South
by
Southwest
this
year
than
last
year.
You
know,
there's
there's
rarely
some
kind
of
control
reality
before
and
after
or
these
kind
of
comparisons
are
difficult,
but
we
found
the
data
very
useful
to
be
able
to
look
at
how
trends
are
changing
over
time
and
try
to
correlate
that
to
certain
causes.
B
So
this
is
just
an
example
of
showing
some
of
the
data
that
can
come
out
of
this
type
of
source
where
we
have
your
number
of
trips
and
we
can
show
how
that
varies
over
different
time
periods
and
then
also
travel
time,
and
we
have
radar
sensors
around
town
like
I
mentioned
before
these.
Are
you
know,
actual
hardware
that
we
have
to
install
whereas
interests
in
Rick's?
It's
just
a
purchase
for
the
hardware.
You
know
we
have
to
install
these.
We
have
to
maintain
these
and
so
I
think.
B
We
haven't
found
a
great
use
case
for
in
the
traffic
management
center,
but
we're
working
with
our
traffic
engineering
group,
who
does
studies
for
new
developments
coming
into
town
new,
like
a
new,
a
new
Walmart,
is
kind
of
a
classic
example
or
any
kind
of
new
high-rise
or
residential
building.
They
have
to
do
a
study
of
what
would
be
the
impact
on
traffic
and
they
need
to
know,
counts
and
so
they're
very
interested
in
us
installing
more
of
these
around
towns.
B
So
we
can
just
have
a
continuous
baseline
of
counts
and
the
alternative
being
somebody
going
out
on
the
roadway
and
either
laying
down
tubes
or
manually
collecting
turning
movement
counts.
So
the
manual
travel
data
collection
is
still
very
much
present
in
the
transportation
engineering
field,
even
for
travel
time.
You
know
we
still
in
some
cases
will
have
somebody
go
drive
a
corridor
up
and
down,
and
that's
that's,
not
uncommon.
That's
not
unique
to
Austin,
so
we're
trying
to
figure
out
how
we
can
move
towards
some
of
these
other
data
sources.
B
Behind
it,
you
want
to
know
exactly
how
it's
done
and
that's
you
know
it's
just
not
always
gonna
be
the
case,
so
there's
some
trade-offs
there,
but
I
think
you
know.
The
data
is
just
so
rich
that,
as
we
establish
that
trust
over
time
with
these
data
sources,
that
will
definitely
be
moving
toward
more
third-party
collection
of
data,
yeah,
so
again
kind
of
comparing
different
time
periods.
What
are,
what
are
the
counts,
or
what
are
the
speeds
and-
and
that
can
be-
can
be
very
useful
for
us.
B
Vehicle
detection
I
mentioned
our
grid,
smart
cameras,
so
we've
been
moving
away
from
loops
in
the
ground
and
moving
toward
aerial
detection.
So
cameras
in
the
air
that
detect
vehicle
movement-
you
know
loops
are
very
high-performing,
except
when
there's
construction,
which
happens
all
the
time
you
know
utility
goes
in
and
digs
it
up
and
it's
hard
to
it-
we're
not
always
quick
to
repair
it.
So
we've
been
doing
more
of
these
video
detection
systems,
so
the
grid
smart,
one
of
the
interesting
things
about
them
is
we
can
get
turning
movement
counts.
B
B
We
also
have
Texas
Advanced
Computing
Center,
you
one
of
Niles
colleagues,
way
Josue
working
with
us
on
alternative
ways
to
get
data
from
our
traffic
monitoring
cameras,
so
these
grid
smart
systems,
are
pretty
expensive
they're
about
eighteen
thousand
dollars,
apiece
our
normal
traffic
monitoring
cameras
are
closer
to
a
thousand
dollars.
So
if
we
can
be
pulling
data
just
from
our
normal
traffic
monitoring
cameras
and
getting
counts
or
near
misses
from
those,
then
we
could
potentially
save
a
lot
of
money.
B
B
It's
surprisingly
difficult,
I'm
curious
to
hear
about
Boston,
but
for
us
to
store
data
in
the
cloud
John
who's
who's
lurking
on
the
call
has
designed
or
architected
a
solution
with
with
Amazon
Web
Services,
which
is
to
the
city
works
with
we're.
Also
looking
at
storing
some
data
at
tag,
Texas
Advanced,
Computing
Center,
but
it's
it's
an
ongoing
process
just
trying
to
work
with
our
our
security
groups
and
and
everybody
to
figure
out
something,
a
solution
that
everyone
is
is
comfortable
with
so
I'm
curious.
A
B
That's
a
great
question:
I
mean
so
what
weird
interoperability
at
the
data
I?
Don't
there
aren't
a
lot
of
and
I
might
not
be
right.
I
mean
there's
standards
around
some
of
the
data
where
we
have
we're
part
of
the
waste
connected
citizens
program.
Something
I
didn't
talk
about,
but
we
want
to
where
they
gather
lane
closure
information.
So
you
know
we
don't
do
a
good
job,
putting
out
where
our
lane
closures
happening
or
road
closures.
You
know
some
of
those
are
planned
special
events.
B
Some
of
those
are
unplanned,
like
a
water
main
lane,
water
main
breaks
or
there's
construction.
We
never
know
when
construction
is
actually
going
to
start
when
it's
actually
going
to
end
in
ways
that
come
up
with
a
standard
for
that
data.
That's
quickly
becoming
the
standard,
so
you
know
we
all
will
definitely
share
data
in
that
standard.
B
As
far
as
sharing
some
of
this
other
data
with
other
cities,
I,
don't
I
mean
we're
really
trying
to
wrap
our
brains
around
even
sharing
it
with
ourselves.
To
be
honest,
but
I
think
those
are
conversations
that
that
need
to
happen,
especially
if
we
want
to
be
able
to
collaborate
on
things
like
video.
B
Know
we're
funding
a
project
for
someone
to
look
at.
How
do
we
use
our
CCTV
cameras
to
extract
data
from
you
know?
That's
something
that's
interesting
to
probably
every
city
in
the
country.
So
if
there's
some
ways
that
we
can
be
going
about
it
that
are
standardized
and
cross
municipality,
you
know
we
need
to
start
having
those
those
conversations
with
our
our
partner
cities.
So
I
don't
have
a
good
answer,
but
it's
a
good
question
so.
A
Just
how
you
can
again
that's
I,
guess
more
for
the
interoperability
is
to
make
sure
that
people
are
using
similar
languages,
vocabularies
and
then
the
relationships
between
those
but
I
think
you
know,
I
I
know
you
guys
are
sort
of
still
getting
to
the
point
where
interoperability
of
even
the
same
data
is
more
is
difficult.
Much
less
trying
to
link
other
data
yeah.
B
And
I
think
part
of
the
challenge
is
just
a
lack
of
expertise
on
the
city
side,
especially
within
transportation
departments.
So
we
were
fortunate
to
have
a
staff
member
who
is
conversant
in
this
and
can
help
us
build
solutions,
we're
fortunate
to
have
a
partnership
with
a
university
that
can
help
us.
B
B
Are
happening
in
an
in
a
black
box
and
know
that
you
know
from
a
perspective
of
interoperability
right
so
but
it's
something
as
an
industry
we
need
to
think
about.
If,
if
we
want
to
move
toward
something
a
more
interoperable
environment
for
sharing
our
data,
then
we
need
to
figure
out
how
to
pool
our
expertise,
or
you
know,
set
up
some
kind
of
I
mean
is
probably
just
because
we're
in
the
beginning
stages
of
we
move
slowly,
beginning
stages
of
smart
mobility
and
and
thinking
about
big
data
or
data
at
all
in
transportation.