Transcriber: Amanda Chu Reviewer: Peter van de Ven
Sydney-Pacific, it's a very active community,
and the vast majority of events
center around congregating in groups and eating shared food.
In March,
the undergraduate dorms de-densified
and then the graduate dorms relatively soon after.
In Sydney-Pacific,
our new mode of living required that we not allowed to gather,
and our student life sort of halted.
The spark that became this study
actually originated from the grad students in the dorm.
They said, "Isn't there some type of technology or means
to understand usage of our shared spaces and risk associated with it?"
I thought it's a good question, so I sent a note to two different groups,
one at the Computer Science and Artificial Intelligence Laboratory
and another in the Media Lab.
I just asked, "Is there something that we can use that is useful,
actually, like in a dorm?"
And both responded back immediately and said,
"Not with what we have right now, but here's an idea.
Take Bluetooth beacon sources
and install them in each of the common spaces,
and then we could develop an app
that would receive that signal on the phone.
From that, you have the potential to back out distance and proximity
and therefore use of those common spaces.
I just asked a few questions and had a lot of volunteers overnight.
We had this amazing team
of faculty, grad students, and professionals at Lincoln Lab.
[Anthony Lapadula - Researcher, MIT Lincoln Laboratory]
Anthony Lapadula: So I think everybody had the same idea at the same time.
Everybody carries a smartphone -
"Oh, what can we use from the smartphone to measure a distance?"
Bluetooth was kind of an obvious first guess.
And then the question is,
Can you measure how long you've been close to someone,
and how close have you been to that person?
I don't think anyone knew at the beginning how hard it was going to be.
Bluetooth was not designed for this.
If you just stand close to a Bluetooth beacon with your phone
and watch the signal strength,
it tends to bounce around quite a bit.
Their reflections are across the wall; there's multi-source;
there's all kinds of problems.
One of the biggest things that degrades signal strength
is the human body.
What really excites me about this project
is the possibility of collecting lots of Bluetooth data
to help us build a good mapping between signal strength and proximity.
But we already had a calibration protocol
for people to collect data in a structured way;
however, it was probably a couple hours to actually run the entire protocol.
There was no way that we would get people to volunteer,
so we came up with a very streamlined calibration protocol.
You should be able to run through one of these in about 60 seconds.
The joke I always make is,
"You're in the kitchen.
You just put your burrito in the microwave.
You have a couple of minutes. Go ahead and do a couple of calibrations."
Abhishek Singh: So I've been working mostly around the app development.
It really gets tricky running these Bluetooth apps
because the Google and iOS operating systems
are really stringent about Bluetooth code running in the background,
so it requires some fiddling around and some rigorous testing.
So with iOS,
whenever the app goes to a background state,
the iOS operating system makes it in a sleep mode.
The app is - although running in background -
it's not really doing anything,
and it's not really trivial to wake up this app
and make sure that it keeps recording the Bluetooth data and keep sending it.
In Android, we can do this for every minute,
but there is some trade-off with battery usage.
It looks like 15 minute is like sort of a sweet spot,
where the app can wake up and listen to the chirps
and then again go to sleep.
Daniel Ribeirinha-Braga:
The tricky part is those sensors.
You could have an Android phone
that is five or six years old;
however, your phone does not have a gyroscope or a barometer,
so we have to be able to create a data model
so that even if you don't have that information,
our backend server can still ingest that
and do something with the remaining information.
So being able to test those cases is critical.
We'd just run a bunch of emulators on our computers,
but that's completely different
because a barometer and a gyroscope don't exist in a virtual machine.
In a computer, you need a physical device.
We all did a bunch of testing on the app.
Some people have old iOS phones,
some people have different Android phones.
That's how we go through it.
Everyone tested on their phone.
We reported a bunch of bugs.
But there was a solid two- or three-week period
where we were constantly getting a list of tasks
and it'd be like, "I saw this issue and that issue,"
but little by little,
we were able to really make some progress to solidify the application.
Christopher Fourie: So phones have complications.
Our tile-based solution is far simpler.
You have constant transmission power
because you no longer have to worry about different device platforms.
It doesn't require user inputs,
because you can just attach it to your keys and forget about it.
So the entire solution is a lot simpler and as a result, a lot more robust.
The device will constantly emit chirps.
We'll record those chirps using an external architecture,
and you can then figure out
which people were in close proximity to each other.
So the tile solution allows us
to directly compare the additional consequences
of using a phone-based environment
as opposed to something that's a little bit different.
Ilaria Liccardi: As a privacy researcher,
sometimes I try to think of the worst case scenarios.
Sometimes I cannot even predict what that will be,
because there are so many things that could go wrong.
Especially some of the contact traces app have leaked their entire email addresses.
So the fact that we're using an ID that only a few people have access to
and the fact that we are not using location,
that was something that we had discussed at length
because removing this kind of information makes it more difficult,
but it does make people's identity more secure,
and we actually found a good balance as a result.
We could have gone even further.
But with the balance that we strike, I think it was good enough.
Sarah Chung: This whole process is for the students, right?
I mean, there are research goals,
but part of it is to benefit MIT campus in general,
and then much of it is by students
because they're the boots on the ground.
They're not only the boots on the ground to set up all the infrastructure,
but they're also the ones
who have to volunteer their own data and download this app.
Without these student volunteers advocating in the dorm,
this wouldn't happen.
Without installers, this wouldn't happen.
Without students registering, this wouldn't happen.
And then even after they register,
without them calibrating like, also, it will not happen.
However, volunteers really need to be invested in too.
They have to feel like they're getting something out of it.
And a lot of my thinking
has gone into how do we make this more efficient and less work for them
so that they can enjoy benefits with less cost
and they do what we hope that they will do.
We shall see, right?
Because we're just at the cusp of rolling out Eastgate and Ashdown,
and we shall see.
Geeticka Chauhan: As I talk with my officers
about different policies we want to implement
or different events we want to run,
having the knowledge
that the contact tracing study is going on in parallel
is very helpful,
and the officers that I'm involved with
are quite excited.
A lot of the questions that other dorm presidents had
were primarily privacy concerns
and how the information of the student would be kept
and how this information would be used by MIT Medical.
Another thing that the dorm presidents were really excited about -
they were thinking,
"Yeah, this is a really good thing to start in the dorms,
but they were also asking Julie
if she'd be willing to deploy this in the labs.
Przemyslaw Lasota:
The main objective of the scientific protocol
was to evaluate
how digital contact tracing would compare to manual contact tracing,
and we had three secondary objectives in this study.
The first one was understanding the trade-offs
between more privacy preserving
and less privacy preserving digital contract tracing methods;
also, contributing calibration data
to help other researchers understand the relationship
between Bluetooth signal strength and distance;
and finally, trying to understand
user acceptance of different digital contact tracing methods.
JS: I still am amazed where at the point,
we are just about ready to launch the study at full scale
because the team that came together
was a set of people who had literally never worked together,
and now we're co-developing software, hardware virtually.
And it's been a dream team.
The complexity and scale was surprising to me,
but you wouldn't know it based on how this has come together
in the course of six weeks to two months.
We're currently rolling out to three of the graduate dorms,
but then three of the undergrad dorms,
as sort of a pilot or a test
of what we might be able to do more broadly
when undergrads return at a higher level in September.
The hope is that we can help keep our community safer
through the fall reopening
and also provide valuable knowledge
on how digital contact tracing technologies
can be used more broadly beyond MIT.