Goodmorning everyone
yes, I’m a criminologist I do not know if
he was more afraid of you, me, you
but I will not talk to you about blood today
I will talk to you about the city of the future and
criminology and security
surely we live in the city that I am
smart or they are becoming more
smart but in smart cities
we continue to be afraid and the
crime continues to be there and the
police forces work badly
resources are increasingly scarce
you can do something more than what
we can do in these cities
clever here I am convinced this is
the idea that today I want to transfer you that
smart cities have gods
antibodies against crime the smart
city has antibodies or owes them
develop how to develop them the theme of
I want to talk to you
I have been dealing with it for some years
in my research group about since 2012
2013 and more recently I deal with it
a startup of the University of Trento
that we have built where we do
research on the safety of cities but
let’s take a step back and try
together to answer a question the
crime in cities can be expected
it seems minority report but I assure you
that there is science in the answer to
this question if we look for an answer
port is not given recent Venice
some of you may have read the 15 the
night between 15 and 16 here seems to do
just the criminologist between 15 and 16
November was 3 45 at night
a criminal, a thief with a swag
run away from a hotel there is someone who does it
chase finds a steering wheel ad
catching the flying one was there because
a software had told the police headquarters of
Venice that between 3 and 4 in
that area would have occurred one
crime is not minority report this
software is called hicks files hicks
joke hicks you call it if you go to
seeing him joke is called hicks la
seriousness now is that software is a
Predictive police software that is
been carried out by the police headquarters of
naples with the federal university ii and is
at the head of some Italian police headquarters but
it is not an idea of 2018
and an idea born in the United States
in 2010 where the university of
California researchers have long
worked with the police department
of los angeles and have built a
software called brad paul che
today it is in 60 police districts
of American police in the states
united see here behind me that i
squares are predictions in space
and over time these softwares use the
past crime
past crime data for
predict concentration in the future
of crime in space and in
time where they will come with good
probabilities the crimes in the future we are
talking about grateful urban crimes they have
a dimension usually patrimonial al
maximum of violent urban crime
in los angeles with the use of this
software crime from year to year
from 2018
to date it has been reduced in some years of
20 of 30 percent
the goal of predko this name of the
software is trying to figure out where they go
the crimes
it does so with prediction algorithms it is not
a very ugly statistics name
math so to go and understand
where the crimes will occur in the future
based on the past because the past
teaches the future is the same thing that
he is the software of the Naples police headquarters
of the Venice police headquarters with one
little difference you look at them
seriality of the crime as the crimes
they are often serial to criminals
professionals make more crimes I can
to predict the next crime of one
series on the characteristics of the series
itself so crime can predict
the future crime the data of
crime in the city then make us
learn where crime will occur but
It’s enough today the cities are more
intelligent of only one data
on the crime today the cities have the
big data
if they are intelligent then the idea is
how to use these big data ea
this we started to work
in the university with a project that
we have achieved here quite unique
I would say to the world we have achieved
here where perhaps there is no crime
much even if we should not say
because they are not convinced with Trentini
the police headquarters of trento from 2013 to 2015 e
with the university we as coordinators
with the brown foundation kessler e
above all I want to emphasize the
common because this is a new element
the municipality and the two administrations
questions to understand the idea that I want
transferring the first is this for
predict crime in cities
really only the police data is needed
to understand what will happen to understand
where crime goes will only serve
this data
we have only this data is the second one but
we are sure that building security
in the city it means only avoiding crimes
future means only leaving in a way
more efficient
the territory by the forces of
police
security means only this
security also means feeling
safe security means to feel good and
live the city and often live well
city and not wanting to live it can be
not dependent on objective quantity
of crime but create security
to build urban security means
work with these themes on flights too
these themes means working with i
citizens
it means working with
administrations and this is what we have
done and to do it
we went to imagine a city
future that wants to prevent the
crime and that future city is one
city made of data is a city made of
sensors and a city that sensors in the
territory that has ganglia that can
take information and can take them
even by their own citizens by communicating
with its citizens in constant and
this communication will lead to obtain
lots of data of what kind we forget
for a moment the police data on mine
shoulders
see a rundown of possible data
that today exist in cities that are not
not even so clever because
There are smarter cities than
this that I am going to show you and that there
we are sketching right now
in the traffic data mind
traffic data speak of the
livability of the cities but they also speak
where we go and the places we leave
so they have to deal with
security and have to do with
crime data weather if it rains of
Sunday I’m at home and if I’m home is
very unlikely they come to steal
while I’m there
if instead it does not rain and go away to the sea or
the lake is likely to steal one
stupid example sorry for you to understand
how much climatic conditions
influence crime and the
safety use of public transport one
m full is a place where they happen
many pickpockets is a fact
the closer we are to a market
there are criminal but one opportunities
m full at ten in the evening in the center
city
it means that that city probably
safety
because the city center has lived because
citizens are coming out because there
they believe and therefore they live the city and
therefore the full metro data
and may in some cases also be one
safety data of perception
security depends on how I use it
in traffic parking lots
you remember we do not do it all
enter a city that we do not know
let’s go to the nearest parking with i
available places that the municipality
It has but a full parking lot
outdoor and parking where
they happen can come with more
probable theft of objects from cars
because because the thief lowers and yes
hides between cars and enters
in cars when there are few
machines tell us who will steal in
that moment that does not steal on cars
so the data given that a data that there
it can serve data on the users of the
citizens of light gas and water want
simply say how much we live there
our homes and if we leave uninhabited or
if there are whole neighborhoods and there
I assure you that you can only see with that
given there that they are turned off and if with
Goalkeepers are turned off are disorganized
they are neighborhoods where there is social hardship
where there is disorganization and therefore where
it’s probably safe
that’s who that data is talking about me
another thing mobile data
what that phone obviously I do not know the
gbl the geolocation le
geolocation on
if I had I know where I am if we have it
we are all in this theater
when we walk that datum speaks of
our movements and you know the data
of mobile phones and what he predicts
better than concentration and those
of people who use mobile phones to
crime in the city after crime
imagine yourself the strength of that
given there and if a neighborhood of the city in
center while all others are
lived that neighborhood not to mobile phones
turned on and because people probably
they may be afraid they are not
visiting that part of the center then
that data there today that the telephone
they sell limited let’s do from
part of this thing is an important fact
that can be used
and all the cameras we put
you know that cameras can today
launch alarms count how many people
pass as many cars pass to the guano
intelligent algorithms to identify
characteristics phenomena and those
identified characteristics may
end up in databases
so the digital camera has a
information power that goes beyond use
that we usually think can have
and then our local police records
many police administration
overcome the municipal police not the
police forces
that data is a data on management
of the territory and there are cities
smart from us, for example
who have a lot of information about
local police and social media
today they stole me at home
oh my God, I feel insecure in this city
terrible I just arrived and I do not know
where to go it seems all dark even i
lighting data are important
and there are intelligent cities
the social data is a data of people
that communicate objective security or
subjective security
you just have to know how to look and then
applications in the hands of citizens
why not make an act in which to report
there are reports of crimes reporting in
safety report fear report
disorder that bothers us and receive
reports from our communications
on the safety of ours
administrations because today these
technologies allow that
communication that does not make only the
citizen but those data are given to us
we can use and then the
placement of sensitive objectives
a school an ATM an office
postal
and so on the cases facilitators and that
they have remained unattended as they can
become a place of shop allows
of the places of protection as it may be
a barracks
these influence crime
compared to where they are
or the lack of criminals
the perceptions of security and then all the
data that all the municipalities have unfortunately
always less open even if they should
be open on information data
very demographic social networks I have
probably done a head like that but
think you have all this data a
handy to take them for purposes and
to use them for purposes other than
those for which they were created e
constructed
the purpose for us today is to prevent it
crime and make the cities feel more
secure and citizens safer
then take follow me and imagine
to be in an English room
they would call it because they use these
terms not when it is against the thesis
criminology security control room one
security control room from
that room I’m in connection with
my policemen like the policemen
municipal with my citizens and in
that room is software and that
we have already created it, there is no software
I’m talking about something very distant
called the day before we did with
this startup and I do not know why i
it looks like software is not important
doing what that takes that data
maybe it mixes them with the data of the
police and makes predictions much more
accurate on where the
concentration of crime in the
space and time and make them more accurate
for that it will also combine character data
social social data all data
that I showed you and then they will be
more refined and these forecasts a
trento years ago we made and
they worked a lot is better in the
simple predictive cleaning but then does
one more thing
the answer to that second question that
I tell you that I have told you that we are here
opposites do this and not urban security
is that we gave him predictive ago
feeling close to citizens makes people understand
because of disorder in security
crime makes it clear how to intervene
because today there is a lot of belly in the
urban and non-urban security management
only in the management of an institution with del
crime while serving a little more
head a little more than reason to understand
it means intervening and not just when
we intervene imagine one
mayor can put more lightings
can put the cameras can do more
beautiful the city has many options but
then he does not know if these options work
if those data continue to monitor us
we know if the interventions work
this is the idea of a city
clever than antibodies that you
protects that it is close to the citizens and from
an administration that with the data always
protect privacy
I did not say that but it’s more than obvious
it comes to preventing and fighting e
also to fight crime
making them feel safe at all more
nearby is an idea that seems far away but
I assure you that a close idea with
that start up but we are already building
in a very large Italian city and
we hope to be able to do so soon
other cities thank you for
attention
yes, I’m a criminologist I do not know if
he was more afraid of you, me, you
but I will not talk to you about blood today
I will talk to you about the city of the future and
criminology and security
surely we live in the city that I am
smart or they are becoming more
smart but in smart cities
we continue to be afraid and the
crime continues to be there and the
police forces work badly
resources are increasingly scarce
you can do something more than what
we can do in these cities
clever here I am convinced this is
the idea that today I want to transfer you that
smart cities have gods
antibodies against crime the smart
city has antibodies or owes them
develop how to develop them the theme of
I want to talk to you
I have been dealing with it for some years
in my research group about since 2012
2013 and more recently I deal with it
a startup of the University of Trento
that we have built where we do
research on the safety of cities but
let’s take a step back and try
together to answer a question the
crime in cities can be expected
it seems minority report but I assure you
that there is science in the answer to
this question if we look for an answer
port is not given recent Venice
some of you may have read the 15 the
night between 15 and 16 here seems to do
just the criminologist between 15 and 16
November was 3 45 at night
a criminal, a thief with a swag
run away from a hotel there is someone who does it
chase finds a steering wheel ad
catching the flying one was there because
a software had told the police headquarters of
Venice that between 3 and 4 in
that area would have occurred one
crime is not minority report this
software is called hicks files hicks
joke hicks you call it if you go to
seeing him joke is called hicks la
seriousness now is that software is a
Predictive police software that is
been carried out by the police headquarters of
naples with the federal university ii and is
at the head of some Italian police headquarters but
it is not an idea of 2018
and an idea born in the United States
in 2010 where the university of
California researchers have long
worked with the police department
of los angeles and have built a
software called brad paul che
today it is in 60 police districts
of American police in the states
united see here behind me that i
squares are predictions in space
and over time these softwares use the
past crime
past crime data for
predict concentration in the future
of crime in space and in
time where they will come with good
probabilities the crimes in the future we are
talking about grateful urban crimes they have
a dimension usually patrimonial al
maximum of violent urban crime
in los angeles with the use of this
software crime from year to year
from 2018
to date it has been reduced in some years of
20 of 30 percent
the goal of predko this name of the
software is trying to figure out where they go
the crimes
it does so with prediction algorithms it is not
a very ugly statistics name
math so to go and understand
where the crimes will occur in the future
based on the past because the past
teaches the future is the same thing that
he is the software of the Naples police headquarters
of the Venice police headquarters with one
little difference you look at them
seriality of the crime as the crimes
they are often serial to criminals
professionals make more crimes I can
to predict the next crime of one
series on the characteristics of the series
itself so crime can predict
the future crime the data of
crime in the city then make us
learn where crime will occur but
It’s enough today the cities are more
intelligent of only one data
on the crime today the cities have the
big data
if they are intelligent then the idea is
how to use these big data ea
this we started to work
in the university with a project that
we have achieved here quite unique
I would say to the world we have achieved
here where perhaps there is no crime
much even if we should not say
because they are not convinced with Trentini
the police headquarters of trento from 2013 to 2015 e
with the university we as coordinators
with the brown foundation kessler e
above all I want to emphasize the
common because this is a new element
the municipality and the two administrations
questions to understand the idea that I want
transferring the first is this for
predict crime in cities
really only the police data is needed
to understand what will happen to understand
where crime goes will only serve
this data
we have only this data is the second one but
we are sure that building security
in the city it means only avoiding crimes
future means only leaving in a way
more efficient
the territory by the forces of
police
security means only this
security also means feeling
safe security means to feel good and
live the city and often live well
city and not wanting to live it can be
not dependent on objective quantity
of crime but create security
to build urban security means
work with these themes on flights too
these themes means working with i
citizens
it means working with
administrations and this is what we have
done and to do it
we went to imagine a city
future that wants to prevent the
crime and that future city is one
city made of data is a city made of
sensors and a city that sensors in the
territory that has ganglia that can
take information and can take them
even by their own citizens by communicating
with its citizens in constant and
this communication will lead to obtain
lots of data of what kind we forget
for a moment the police data on mine
shoulders
see a rundown of possible data
that today exist in cities that are not
not even so clever because
There are smarter cities than
this that I am going to show you and that there
we are sketching right now
in the traffic data mind
traffic data speak of the
livability of the cities but they also speak
where we go and the places we leave
so they have to deal with
security and have to do with
crime data weather if it rains of
Sunday I’m at home and if I’m home is
very unlikely they come to steal
while I’m there
if instead it does not rain and go away to the sea or
the lake is likely to steal one
stupid example sorry for you to understand
how much climatic conditions
influence crime and the
safety use of public transport one
m full is a place where they happen
many pickpockets is a fact
the closer we are to a market
there are criminal but one opportunities
m full at ten in the evening in the center
city
it means that that city probably
safety
because the city center has lived because
citizens are coming out because there
they believe and therefore they live the city and
therefore the full metro data
and may in some cases also be one
safety data of perception
security depends on how I use it
in traffic parking lots
you remember we do not do it all
enter a city that we do not know
let’s go to the nearest parking with i
available places that the municipality
It has but a full parking lot
outdoor and parking where
they happen can come with more
probable theft of objects from cars
because because the thief lowers and yes
hides between cars and enters
in cars when there are few
machines tell us who will steal in
that moment that does not steal on cars
so the data given that a data that there
it can serve data on the users of the
citizens of light gas and water want
simply say how much we live there
our homes and if we leave uninhabited or
if there are whole neighborhoods and there
I assure you that you can only see with that
given there that they are turned off and if with
Goalkeepers are turned off are disorganized
they are neighborhoods where there is social hardship
where there is disorganization and therefore where
it’s probably safe
that’s who that data is talking about me
another thing mobile data
what that phone obviously I do not know the
gbl the geolocation le
geolocation on
if I had I know where I am if we have it
we are all in this theater
when we walk that datum speaks of
our movements and you know the data
of mobile phones and what he predicts
better than concentration and those
of people who use mobile phones to
crime in the city after crime
imagine yourself the strength of that
given there and if a neighborhood of the city in
center while all others are
lived that neighborhood not to mobile phones
turned on and because people probably
they may be afraid they are not
visiting that part of the center then
that data there today that the telephone
they sell limited let’s do from
part of this thing is an important fact
that can be used
and all the cameras we put
you know that cameras can today
launch alarms count how many people
pass as many cars pass to the guano
intelligent algorithms to identify
characteristics phenomena and those
identified characteristics may
end up in databases
so the digital camera has a
information power that goes beyond use
that we usually think can have
and then our local police records
many police administration
overcome the municipal police not the
police forces
that data is a data on management
of the territory and there are cities
smart from us, for example
who have a lot of information about
local police and social media
today they stole me at home
oh my God, I feel insecure in this city
terrible I just arrived and I do not know
where to go it seems all dark even i
lighting data are important
and there are intelligent cities
the social data is a data of people
that communicate objective security or
subjective security
you just have to know how to look and then
applications in the hands of citizens
why not make an act in which to report
there are reports of crimes reporting in
safety report fear report
disorder that bothers us and receive
reports from our communications
on the safety of ours
administrations because today these
technologies allow that
communication that does not make only the
citizen but those data are given to us
we can use and then the
placement of sensitive objectives
a school an ATM an office
postal
and so on the cases facilitators and that
they have remained unattended as they can
become a place of shop allows
of the places of protection as it may be
a barracks
these influence crime
compared to where they are
or the lack of criminals
the perceptions of security and then all the
data that all the municipalities have unfortunately
always less open even if they should
be open on information data
very demographic social networks I have
probably done a head like that but
think you have all this data a
handy to take them for purposes and
to use them for purposes other than
those for which they were created e
constructed
the purpose for us today is to prevent it
crime and make the cities feel more
secure and citizens safer
then take follow me and imagine
to be in an English room
they would call it because they use these
terms not when it is against the thesis
criminology security control room one
security control room from
that room I’m in connection with
my policemen like the policemen
municipal with my citizens and in
that room is software and that
we have already created it, there is no software
I’m talking about something very distant
called the day before we did with
this startup and I do not know why i
it looks like software is not important
doing what that takes that data
maybe it mixes them with the data of the
police and makes predictions much more
accurate on where the
concentration of crime in the
space and time and make them more accurate
for that it will also combine character data
social social data all data
that I showed you and then they will be
more refined and these forecasts a
trento years ago we made and
they worked a lot is better in the
simple predictive cleaning but then does
one more thing
the answer to that second question that
I tell you that I have told you that we are here
opposites do this and not urban security
is that we gave him predictive ago
feeling close to citizens makes people understand
because of disorder in security
crime makes it clear how to intervene
because today there is a lot of belly in the
urban and non-urban security management
only in the management of an institution with del
crime while serving a little more
head a little more than reason to understand
it means intervening and not just when
we intervene imagine one
mayor can put more lightings
can put the cameras can do more
beautiful the city has many options but
then he does not know if these options work
if those data continue to monitor us
we know if the interventions work
this is the idea of a city
clever than antibodies that you
protects that it is close to the citizens and from
an administration that with the data always
protect privacy
I did not say that but it’s more than obvious
it comes to preventing and fighting e
also to fight crime
making them feel safe at all more
nearby is an idea that seems far away but
I assure you that a close idea with
that start up but we are already building
in a very large Italian city and
we hope to be able to do so soon
other cities thank you for
attention
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