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Hi.
I'm Martin Kronberg, and welcome to our first IoT Developer
Show.
If you didn't get a chance to see our show announcement
last week, this is going to be a monthly show all about IoT
where we're going to be showcasing
some awesome projects and interviewing
the creators behind them.
With me today is Priyanka Bagade,
who is an engineer at Intel.
And she has a really cool intelligent infrastructure demo
that we're going to show off.
Priyanka, thank you so much for being here.
Could you tell us a little more about what you do at Intel?
Sure, Martin.
I'm an Internet of Things Developer Evangelist at Intel.
After receiving PhD in computer science
from Arizona State University, I immediately joined Intel.
Currently I work with cloud partners
to integrate their cloud technology
into Intel IoT platforms.
That's really cool.
And you know, I'm really excited to see
these kind of collaborations happen.
Well, let's take a look this demo.
I'm really excited to see it.
Sure.
Here is the intelligent infrastructure demo
which utilizes existing infrastructure and IoT
technology to make our cities smarter and safer.
So in this demo, we are using Intel NUC to do each compute
and we are using GE Predix cloud to do historical analysis
of the data.
Very cool.
So what are the infrastructure pieces
that you're modeling here?
We already have the traffic ports deployed on our streets
which have traffic cameras.
So we are using that.
We have emulated that using logical camera here.
Also we are using the inductive sensors
on the road which are being used to detect
the car on the street.
We have emulated the inductive sensor
using Hall effect sensor.
So how are you analyzing all of this data?
So what we are doing, we are taking video feed
from this camera.
We are sending that feed on Intel NUC.
Intel NUC is using computer vision and machine learning
algorithms to process that data to compute speed of the car.
So when the car is moving on the street, we are calculating ROI.
That is the region of interest for that particular street.
And then we are converting that ROI into [? counter. ?]
And when the car is moving, we can see the blue vectors.
We are computing magnitude of those vectors with respect
to length of the dotted lines on the street.
For each country, this length of the dotted lines is fixed.
For example, for US, it's 10 feet.
And after obtaining magnitude of the vectors,
we are calculating average of those magnitudes, which
gives us speed of the car.
And then we have also developed a web server application
which shows what kind of computation
is going on on the NUC.
That is, the H [INAUDIBLE].
So whenever I'm moving this car, you
can see the actual speed of the car on this graph.
And if I move the car faster, we can see that it says "Danger."
That means the car is orbiting through.
After that, we are taking the Hall effect sensor data
to see how many cars are actually
passing through the street.
You can see a nice blue light here
which shows that car is actually passing through that street.
We are taking the speed of the data
as well as how many number of cars pass through that street,
and sending that data to the cloud
to do historical analysis using the data visualization
and analytics service.
So are systems like this in place right
now in the real world?
That's a really good question, Martin.
So GE Current has deployed lampposts
on streets of San Diego.
The project is called CityIQ.
They are collecting data from the infrastructure
and processing that data on Intel [INAUDIBLE] Gateway,
which is in-built in that lamppost.
And they are using this collected data
in applications such as smart parking, pedestrian safety,
and environmental planning.
Really cool.
Well, it sounds like we can start
leveraging existing infrastructure
and making it more intelligent and make
our cities, like you said, safer and smarter, more efficient.
Yeah.
It's really great.
Priyanka, thank you so much for coming here and showing us
this great demo.
If you guys want more information about it,
we're going to provide some links.
And Priyanka, once again, thank you so much for being here.
Thanks, Martin, for inviting me on the show.
I really enjoyed it.
So before signing off, I want to talk
about a couple exciting events that are coming up.
First, we're sponsoring the fourth IoT Open Challenge
hosted by the Eclipse Foundation.
Submit your proposal for an IoT solution
around smart cities, industry, or remote help
by November 13 for a chance to receive hardware development
kits and really cool prizes.
Second, we're also going be having an online global IoT
DevFest on November 7 and 8 to explore all things
IoT through keynotes, demos, and mentoring opportunities.
Thanks for watching this episode of the IoT Developer Show.
Don't forget to like this video and subscribe to the Intel
Software YouTube channel.
And remember to check out the resources
and the links provided as well.
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