So yes, so I present myself and Pierre Romant.
I'm here for the first time to first them, so I'm really happy to share our work in the lab.
I'm working in a lab.
It's a mixed unit research.
The name is Umra, it's about environmental acoustics.
And it's mixed unit research, because we are between two institutes.
University of Tel Aviv, and Serema.
It presents you specifically one tool, which is noise milling,
because I am the main facilitator of the tool and one of the main developer.
But I also want to speak more generally about a pencil since the lab is a team,
and also about all the ecosystem around this noise milling tool.
So I know that acoustics, especially on the Romantan noise, is quite a niche subject,
so I have two or three slides to speak about just on the Romantan noise, of course.
So why are you now made in Europe?
We consider that 20% of the people living in our area where noise levels are considered harmful to else,
if we take the threshold of the world else organization.
It's more or less 20 million of people declaring that they have high annoyance.
The sleep disturbance is really high with 6 million people,
that probably have sleep disturbance considering our models.
And there is also directly increase air disease, for example, because it generates stress,
problem when you sleep, and it generates air disease.
It's more or less 50,000 air disease in Europe, directly linked to noise,
and premature mortality and cognitive impairment in children.
So this is as issue is now really well known,
but also in the late 80s, the Fannerachet Kaplan popularized,
the concept of attention restoration theory.
Basically, they say that spending time in natural environment
helps to restore depleted cognitive resources,
and natural environment are not just silent places,
it's also where natural science gap are important, and should be preserved.
A last way to see the problem is noise is not only harmful for humans,
but also for nature.
It can make it harder for animal to communicate, find food, survive.
So it's now really clear evidence that some births, for example,
for the same species, if they live in the rural area,
or if they live in the urban areas, they change the way to sing.
They will sing maybe higher to go over the infrequency to have higher pitch
and to go over the noise or traffic, or they sing louder,
or they sing sooner before the traffic peak at the morning,
or more frequently.
So this is clear evidence for some species,
and we have the same for a lot of different animals.
So this was general idea about environmental noise issues,
and of course, as researchers, we need tools and data to study this,
and we need open tools and open data, because I mean, first of them, you know why.
Okay.
So in the lab, in the lab, we decide to take this a problem with the platform,
now we call it a platform, which is a nice platform.
It begins between a collaboration between two labs, one geometric lab,
GIS expert, lab stick, and all our lab lab art acoustic,
and one of the art acoustics, basically the idea to propose new tools,
based on science features for environmental noise assessment.
The idea behind was, public money, equal, public code, as we can see here,
a lot in the first name, open science.
And of course, black boxes, private software,
to prevent efficient transparent property spill research.
It begins in 2008.
It was the first, the first funder of the platform, the idea I will say,
and the two main guys, what is critical, because the acquisition director of the lab now,
and one bushy on the right side, that was really forced, and still,
really forced on to just.
I say it was because he went a little bit away from the team,
we'll come back about this, because he focused on climate change studies,
but still really close to us.
And they began to work together with this tool.
We now have three tools, noise money, which is a software to do noise maps,
noise capture, which is an Android application to do code sourcing,
mobile measurements.
And the last one now, it's only sensor, which is sensors,
like fixed sensors, that you can put with hardware,
hardware and the software part of the sensor.
Basically, the organization of the noise planet,
seeing I call it platform, because website,
but it's a bit more than that.
There is like official organization, which is inspired by
foundation structure, because we had a foundation in certain universities,
the idea is to have a chair inside and so on.
But this foundation idea is a little bit in standby.
The tools, when, finally, separately, they have separate funding,
separate research projects and so on.
But the devs are shared across a project, because inside the lab,
we have two devs.
The lab is more or less 50 people.
And research and software engineer can work on one tool on the other one,
independently.
So now, we'll do a short focus on noise capture,
which is one of these two main tools.
So noise capture began in 2017, more or less.
It's Android applications.
The idea at the beginning was to dedicate this application for the expert.
And why we did it is because in 2015, more or less,
we began to see a lot of application to measure noise on the store.
Android store.
As a Christian, we were looking at the application on most of them,
was really bad.
I would say, they were not following the thumbnails in acoustics and so on.
So we said, OK, we will do an application,
following the thumbnails of measurements.
We know that they're not going to be bad,
because smartphone, I'm not calibrated outside of the industry.
But still, we wanted to see what we'll happen with this.
And I'll surprise that not only experts began to use the tool,
but it was really used like code source platform,
and a lot of people began to use it.
We have now of more than 300,000 downloads,
and a lot of trace and measurements around the world,
what you can see here.
And here it's the city in the world where we have more measurements,
which is young in France,
because we have really fanatic users in this place.
And we begin to have like really nice maps.
I saw that live demo was appreciated here,
so I will just show you the platform.
So this is the platform where you can see here's the last measurements
that we have done today, for example, in Germany,
oh, your little boy, and so on.
And you can see here's the map past here.
I saw sometimes that quiz was also appreciated here,
so maybe you can try to find, what is this?
Oh, on my screen is okay, but okay.
What is this small, round, really silent area?
Do you have any idea in the city?
No.
Yes, it's a cemetery here.
So this is a silent place in this city.
So that air, I really rough.
They are not calibrated and so on.
It's aggregated on the map.
So we come do a lot just looking about it,
but this is a topic of research for us.
Some PhD has working out to have better quality
that are out to qualify these data and so on and so on.
The tool is not just like short source information.
It's also raising an awareness about noise.
We do some stuff.
The name is noise capture parties.
For example, you have a science festival, something like that.
And you do a noise capture party just behind the side of this.
In university also, this is Italian university.
Each chair, they do a big noise capture party in the university.
So this is the way to use the app.
And lastly, the three or four last year,
we had a project, the name was Sonorose.
And the idea was not to use the app only just to measure 11 and put it in the platform
but to go beyond.
To go beyond.
For example, to see if using the tool as a mediator for the city
then can help them to empower themselves to speak about noise
at the same levels that researchers and elected people.
So we are all in the same room as 25 people,
two of three researchers and two of three elected people.
And the idea was to speak specifically about the airport close to the city
and how we could find solution to raise awareness
or to mitigate some, some, some, some singing and so on.
So it's to explain that maybe it's a really technical tool at the beginning
but the use of the tool is just not around the code
and around the, it's more than that.
It can be useful for research, social, social, and humanities,
and social humanities.
Now we are working in the next chapter two.
So this is the next version of NOS Capture.
I will try to keep it like this.
It's already, it's already online.
You can open to do some measurements.
You have the spectrogram.
And so on.
So if you want to see it, this is on the GitHub platform
so you have to search it a little bit.
But the Android application NOS Capture,
you can download it on the Android store really fast.
I guess it will be releasing during the year,
but we are not totally sure.
And then you have a noise modeling.
So I will try to go fast,
but to speak a little bit about noise modeling.
So the idea is to do noise map for a road range industry
or noise sources at local and national scale.
We implement a method, the name of the method,
this Knossos EU method.
In fact, it's a standard that all European cities
of more than 100,000 inhabitants in Europe
and last transport, in fact, you have a noise map.
If you look inside your country, if you are European,
you are looking inside your country,
that the base, you should find these noise maps.
It takes some inputs like buildings and roads,
all what you can find in open street map, for example.
And thanks to the information about the flow rate of the vehicle
and the percentage of EV and live vehicle,
and seeing like that in the speed,
then we can have a noise emission level,
and we have a pass finder algorithm,
that finds the shortest pass between the source and the receiver,
considering the building,
then we apply some basic physical laws
to have what is a sound level at the receiver place.
And finally, have these nice noise maps.
We began this tool in 2010 already,
it's Java library with the same problems
that the Sinky was calling on this moment was popular
and our Python is much better, but yes.
We are stick with Java and Groovy.
We have connection with Portuguese and H2G databases,
and it's GitHub distributed, you can see here's a GitHub pages.
We have a graphical user interface, which is really ugly,
but sufficient to work with students,
but most of advanced users, of course, use scripts
and stuff like that, much faster.
Website, of course, documentation.
We also use did the publication, the JOS,
which is on the review, but yeah.
I hope it will be okay.
Because we did the update publication about the tool.
And why research needed it, because at this moment,
because it's mandatory in Europe,
a lot of private company began to do their tools,
it's a software.
But for us as research, we could improve,
it was not possible to improve a little bit the acoustic model,
to do some specific chain and so on.
So I will show you just two of us, for example.
This one is a huge chain.
On the left part, a POS seems to me very much
and it's transportation and adjorn based model.
Basically, if you know the game,
it seems to be a city skyline,
it seems to be this kind of thing,
but with real data behind.
And then we can connect this with air pollution
on noise pollution model as noise modelling.
To finally know every 15 minutes,
where are the people in the city,
and which air pollution,
which noise pollution they receive in this place.
So we can follow someone in the city
and to know where are the critical area
in terms of both in population and noise level.
Also, we did some thing about tsunami warning system.
We have a nylon and on this island,
you want to find the best localization
or deterioration or deterioration of siren, if you have a tsunami.
So basically, it's a genetic algorithm.
It gives all these kind of possibilities of configuration of sirens.
So of course, it's not like to replace the Xperpsiren location,
which is black dots, was the idea of the Xperps.
But to propose some other possibilities,
that maybe it can open their mind and say,
okay, maybe this location was a good idea.
And so on.
Also, in our team,
we are really close to the French government for historical reason.
And because we,
friends asked to do noise morphology and fracture,
we began to build a full infrastructure
compute automatically all the noise maps in friends.
So this is the noise map we did in 2022,
and now we are doing the one for 2021.
And you will see after it's important for us,
because part of the found,
we have found noise,
directly come from this.
The,
the, the, the money that saved the French government
because they, they save because they are using us,
we have a little bit a little part of this money
directly like,
from the, the tool.
So there is also users.
Mostly we, we are amends the universities
because these people that need less support
that classical users and we don't,
we are not enough to, to provide support.
But we are a pin-out because, basically,
acquisitions in universities, I know about the tools.
But also some private company are using it.
Some people can teach it.
And we have now a kudji's plugin,
because a Japanese researcher, this is plugin.
It's not perfect, but it's it's working.
We do every year's a nice morning day,
which is one of two days.
Ebrid online offline, depends of the year.
Speaking just about the noise modelling advances
and what's a user have doing with the tool, basically.
And this is organization now.
We have this noise modelling day one time a year.
And the most important level of the organization
is a technical community plus.
Because noise modelling layer is more
less 100 people coming here.
And the technical community is a 20 people more active
on the platform.
Most of them are user, more than the developer, but active.
And it's where it's every three months
and it's where strategic decision are done,
are taken, what will be our next implementation and so on.
Then we have a technical community.
It's only six people.
And it's just like to take really sometimes
we have some strategic decision to take really fast
and we just join all of six people together.
And we should have a nice plan as to your community,
but it never happened.
We communicate inside with formatimen matter,
most kind of slack and alternative.
The phone links come from the lab when the developer
have time because they are not on reset project.
They develop noise capture on the developer noise modelling.
Most of the phone links are from research project, of course.
Especially now, we try for all the people
from the university contacting me because they want
to use noise modelling for the research project.
I asked them to put the funding, of course,
of the size of the project, but to a like 1, 2,000, 3,000 euros
inside the lines saying, OK, I will contribute to the model.
I will contribute to the project with this money.
Basically, help us to do the noise modelling days, for example.
This kind of thing.
Or for example, I am here normally,
I should be here for for them with this kind of money.
It's not the case for other reasons, but here.
So this is the idea.
And it's not enough to have a developer on the tool,
but it's enough to make the tool alive.
We have this amount of money every five years,
because it's mandatory.
So every five years, government should do the noise modelling,
they contact us.
And we say, ah, we need two years of research in the near or
two engineer, as they found these two years of two engineer.
And sometimes we are funding from private company,
but it's really small, because it's only if research is involved.
And yeah, private company don't invest so much in researching
and very modern noise and so on.
I want to take this last minute to speak about two very close projects.
And these two projects are related by Air 1,
Bocher, as the first on Tuesday, I'll show you at the beginning.
One is H2G, this is a spatial database that we are using.
We are not using POSG, it's connected to POSG,
but most of the time we are using this database.
It's much less popular, but it's really useful for us,
especially because it's standalone.
So it's really easy to give your database to someone just a file.
And most of the time, it's most easy to install a POSG server on the side.
Another platform is geoclimate.
It's a geospatial processing tool box.
And Air 1 did the job to finish.
Do you just don't open three-platform data?
And they are directly formatted for noise modeling
to do noise mapping.
So this is a useful tool for us.
We could do it by N or to have our own script,
but it's directly integrated inside this platform.
I see that there is not the link, but of course,
if you put it in Google, you will update it
with the GitHub leak documentation.
So my conclusion, maybe it's just why I'm in for them.
Of course, to get inspired, to get some advice,
reconnect with first community, because there
are one is not so close than before.
I think we have to reconnect a little bit with this community.
To see, of course, as you are, I guess,
to see how other research software
struggle with open source from the X-M antennas,
community and so on.
And also, from two or three years ago, one colleague
won a European project about open research and open source in acoustics.
So you begin to see in the acoustics
Congress some session about open source.
So there is a rise of an acoustic open source community,
much more than before, but it's not clear
or if we have to stay between acousticians,
or if we have to under enforce them and force
for the instead of like this.
So this is this discussion we have inside the group.
And maybe find some logics or a mongubert.
Yes.
So thank you very much.
Thank you.
Yeah.
Have you considered maybe a correlate in open device
and the project more than, like, I think this can have an impact on
how the population is going to be displaced,
because it's been noise and it might be getting working with
a company that will develop building through physicians
and more to place them more to the mutual way that,
you know, there's been noise that will be going to be
over something like that.
Yeah.
So question is, are we connecting the data that we have with
with something as like buildings or like,
how it's moving inside the city and so on?
And the noise capture data is not is really rough.
It's not a good quality data.
So up data.
So I will never did it and I guess it will not work,
because it's spare data and with really different quality and so on.
Now noise modelling, one of the private company I list
is was because it doesn't exist anymore,
but it was a startup providing a website
where I want to, when you want to buy our someone,
it was competing a noise map, a small noise map giving a noise
to develop the facade and you kind of have some information about it.
Yeah, the startup doesn't exist anymore.
I don't know if because the market is not here,
or for other reasons, but yeah, some people are using it.
But yeah.
But I saw only three research tropics here,
but of course we are connected with epidemiologists.
For example, we are connected with people in
ecological science, biodiversity and so on.
We also have simulation to see how the noise level actually
all over the time.
This is something, a topically interesting,
but we have two issues.
Oh, again, noise capture data is not a good quality.
And noise modelling, as a single model
are going really, are changing also time.
So it's really difficult to be sure that the change in noise level
is not due to the change of the model of the quality of the input data.
Or if it's due to a modification of mobility,
for example, transportation and so on.
And for example, for the moment, the studies that we are done
are, for me, it's not really clear what we are looking at.
If we are looking at change of method or yeah.
But I guess one time we will have a really nice paper
doing it well, but not at the moment.
Yeah.
My question is very similar, but I don't know about that.
And so it's a couple of minutes, and it's very flexible.
I think when populations like those,
some of them are going to be able for normal life,
take advantage like that, and maybe use them
or handle them as possible.
Yeah, the question is if there is like big festival in the city,
the population can double, and oh, we could handle
this kind of phenomenon in the platform.
And noxmoling is perfectly adaptive to this kind of thing, yeah.
And the model, you can simulate the doubling traffic
in the city and so on.
The main issue when you do this kind of thing is,
if you don't that transportation model connected,
you can double the traffic, but maybe traffic can't go,
you have congestion, and so on, and this kind of thing,
or traffic will change the routes that they will take.
So people will change the routes they will take.
So it's exactly why we are working with this kind of big chain of model
to connect to this traffic model, because it's like one piston or more.
So for example, that's not much traffic increases.
Other than the human traffic.
Ah, yes, perfect.
What do we call it?
At the end of the day, we'll say if it's a very distant model.
Yeah, yeah, yeah.
And in this festival, it's not so much the traffic increases,
but the human increases, the noise of people and so on.
And yes, it's much less an interest in size of the lab,
because historically we work about some partition,
but the closer model you can put, whatever the sun source you want,
just at the front.
I worked specifically on human noise sources.
The most difficult is to find the density of the people
where they are in the city.
For a specific festival could be okay.
But for city like Briggs and to know where people are speaking or shouting and so on,
it's not so easy.
The places are changing both the time and so it's difficult,
but it's one research interest here.
Yeah.
The most maps are to the mention of the further
the calculations in the model are the three-dimensional.
Yes, in fact, noise map, yeah.
No map, I showed our two-dimensional, but the question is,
if the calculation is three-dimensional,
and I showed, like, two-dimensional,
but the reservoirs that form matters over the floor,
but you can put reservoir, whatever you want, finally.
You could do three, three, three,
no, it's map without any problem.
The only thing is because we are using DA as platform,
the pass-finding algorithm is like two-and-a-half-d,
dimension, it's like a studied building.
If you have, like, an art, the nice of a don't go inside the art,
but there is not so much this kind of building in the world, so that's okay.
Yeah.
Um, it's very much real great, just a thing.
I was wondering if you are familiar with a people-day noise map,
so on the ground systems, because it's a thing,
but if there's a place where you speak, I don't.
Yeah.
So, question if I am familiar with people doing
underground noise map for transportation, transportation system, for example.
Yes, and no, we are familiar with them when they are outside.
Because sometimes, the control is going outside and going down.
But when it's, yeah, when it's in close places,
it's all the other models and knosos EU,
and really specific one.
And it's more, the same models that I use for architecture, for example,
because close spaces.
We also have an open source.
In fact, it was the first software,
an open source in the lab was for architecture,
all acoustics, the name is Isapa.
And is this software can be used for, for underground,
for transportation, and similar as that one.
All right.
Yes, there's a question.
You mentioned some, in terms of public collaboration.
So, we have collaboration with OBR, the technologies,
like some of which you can see, because much of a reflection,
you work with the involvement of our advanced science,
to the G, although are like this.
Yes, so the question is about interdisciplinarity,
and this kind of tools.
In the lab, we are part of one institute, for example,
with the Institute of Research of Science and Technics
about the city.
And inside this institute, there is all this.
Most of the time it's your banner here,
but inside this institute, you have like sociologist,
your band studies and so on, and so on, and we work with them.
For example, here, the guy you're doing this part
is an economic, it's an economic transportation,
an economic guy, for example.