May 21, 2024 • 29 mins
No matter the location - from the Global South to Northern Europe, from the Far East to the American West Coast - life in a modern-day city is both exhilarating and exhausting. But the rise of AI technology is making cities smarter and helping us reimagine how cities can be more energy-efficient, safer, and enjoyable than ever before. Technology experts Ashish Yadav and JVS Ramakrishna share their thoughts on the future of our cities and offer real-world examples of where AI has changed the way residents of one bustling city live, work, and commute every day.
Learn more about how Intel is leading the charge in the AI Revolution at intel.com/AIeverywhere
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Episode Transcript
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Speaker 1 (00:05):
No matter the location, from the global South to northern Europe,
from the far East to the American West Coast, life
in the modern day city is both exhilarating and exhausting.
Consider all the different cities you've visited throughout the world,
then try and take a mental picture of what you've seen.
(00:25):
Of course, you could focus on the luster of city life,
but don't forget about the traffic, the commotion, and the confusion.
I recently traveled to Italy with my family, and I
was crazy enough to drive through the narrow streets of Rome,
where local drivers take stop signs as suggestions. But in
the future, the chaos of busy city streets might become
(00:49):
distant memories of what city life used to be. The
rise of AI technology is making cities smarter. Urban planners
and city engineers are teaming up with some of the
eating minds in AI. Together they are streamlining how cities
can be more energy efficient, safer, and enjoyable than ever before.
(01:09):
Join us as we reimagine urban life and how we
interact with our surroundings in the smartest cities yet. Welcome
to Technically Speaking, an Intel podcast produced by iHeartMedia's Ruby
Studio in partnership with Intel. In every episode, we explore
how AI innovations are changing the world and revolutionizing the
(01:31):
way we live. Hey, then I'm grand class. Today we
take our episode to the city streets, where AI technology
is already making a tremendous impact across the globe. In
this episode, we will focus on how Intel's AI technology
is impacting local infrastructures and changing the urban landscape. Plus
(01:53):
we'll learn about real world examples where AI has changed
the way residents of one bustling city live, work, and
commute every day. But before we go any further, let's
welcome our guests. Joining us today is Ashshiyadov, the head
of Strategic Partnership, Alliances and Technical Product Marketing at cap Gemini,
(02:15):
a global leader in partnering with companies to transform and
manage their business by harnessing the power of technology. Cap
Gemini has partnered with Intel to develop the five G
Roadside Unit, which will improve five G communications between traffic
monitoring cameras, sensors, vehicles, and pedestrians, making cities run smoother
and safer for everyone. Welcome to the show, Ashiesh.
Speaker 2 (02:38):
Thank you Graham, It's so nice to be here. This morning.
Speaker 1 (02:41):
We're also joined by a JVS. Ramakrishna, a technology expert
who lives in Hyderabad, India, where local authorities have leaned
on Intel zeon servers as part of the solution to
address challenges around effective traffic management and ensure public safety
as the city has expanded beyond its limits. The strategy
has improved traffic flow significantly by identifying congestion hotspots and
(03:03):
dynamically adjusting signal timings, helping optimize travel times citywide. Today.
JVS is also the global business unit head for Sustainable
Smart World at L and T Technology Services, also known
as LTTS. Welcome to the show, JVS.
Speaker 3 (03:19):
Thank your Graham, pleasure to be here in the show.
Speaker 1 (03:26):
I think before we start discussing solutions on making our
cities smarter, I'd like to get both of your thoughts
about some of the common challenges cities face. When some
people think of busy city life, they think of congestion,
think of traffic, they think of safety concerns. I'm sure
some of our audience right now is listening to us
while in a traffic jam. When it comes to infrastructure,
(03:48):
how can we plan our cities? What sticks out is
the common problem most cities face. I'll start with you, Iseshesh.
Speaker 4 (03:56):
So traffic is definitely one of the most challenging part
of city life and there are many ways to solve it.
But for me also personally, I have a lot of
thoughts around how we can do it. Let's continue to
talk and we can tell more into it.
Speaker 1 (04:12):
Absolutely jvs.
Speaker 3 (04:14):
While technology plays a very important role, you know, I
come from part in India where traffic is like all pervesu.
I mean it's like everywhere and you would see millions
of people on the roads. But I think it started
with master about planning. Urban planning is the key in
terms of the city growth and how do the road
infrastructure is planned. Then follows the technology infrastructure.
Speaker 4 (04:37):
The cities are already planned, you cannot erase the lines
and create new roads. But I still feel technology can
do a lot of good even with all those I
would say misplanned roads, right, That's where the power of
technology comes in.
Speaker 1 (04:54):
Yeah. And it's interesting beside that because generally cities have
been planned from a historical perspective. If for example, in Perth,
it was an agricultural type city long time ago, so
the roads are designed for getting access to farmlands, and
now it's you know, obviously the metropolitan area has grown,
and perhaps that leads us into what is a smart city?
(05:15):
Maybe we could start a shish with what's your definition
of what a quite smart city is?
Speaker 4 (05:21):
So I would say a smart city's city that is
keeping the efficiency and quality of life of its citizens
at the foremost. Where I would say you are using
and integrating technology and communication efficiently so that everyday life
becomes easier and the challenges become less and less as
(05:45):
the city becomes smarter and smarters.
Speaker 3 (05:48):
I've been trying to figure out this definition for last
more eight nine years now, just to set the context.
In cities like San Francisco, Birth and all, they have
been planned historically. But most of the developing world where
there as a lot of infrastructure activity is happening, I think
that's where they have an opportunity to replan. But the
problem statements are different to different cities. What is a
(06:11):
smart city? In one small town of India where they
had a problem of unpredictable water supply, So people who
are like probably queuing up late night, you know, waking
for a water supply. If they get an SMS, they
know exactly when it's going to come. The water is
going to come right, so that's smart for them, Whereas
in big cities like Mumbai and Aderabat, it's all about traffic, safety,
(06:32):
utilities and a waste measurement so on. So I think
the definition varies, but ultimate it's all about production of
the wastage efficiencies, quality of life.
Speaker 4 (06:41):
I come from a small village in India and near
our village there is hardly any water, and today that
area is thriving. We may talk about a first world
country where smartness is more to do with sensing so
that I don't have to wait even one minute on
a traffic light, to somebody in a third world country
or a West country where even getting that water is smart.
Speaker 2 (07:03):
I agree with you, and.
Speaker 1 (07:05):
That actually leads us to thinking more about these sorts
of smart solutions. As she she've worked with five G
commercializations for a number of years. Now. Before we get
into the role five G plays in smart cities, we're
going to be hearing in this podcast episode the term
RSU or roadside unit a lot. Can you just help
(07:27):
us dissect what this actually means? What does five G
RSU mean?
Speaker 4 (07:33):
So five G is not just a fast data on
your phone or that five giken on your right top
corner of your phone. It enables much more because of
the low latency and high speed of the data. For example,
these roadside units could be just single server, harmless, small
service sitting somewhere and that could monitor and sense if
(07:57):
there is traffic. They can even sense if there is
a distin on the way the automous vehicle can take
a break, so they could enable that kind of interaction
between the pedestrian and the car. They could ensure that
the lights the signals are to the point where there
is less and less congestion, So it could be making
(08:18):
your traffic smarter. Because of the low latency, you could
have all those signals going out to the vehicles, to
the phones, if not the smart cars, and then making
it consistent also the signals on the lights based on
the sensors, on where the pedestrians are, where you could
(08:39):
prioritize the pedestrians, you could prioritize the bikers, you could
prioritize the congestion. All those things can be done with
the RSUs.
Speaker 1 (08:48):
I'm just thinking of another scenario, particularly around school zones
where I live. It would be nice to be able
to prioritize school students crossing the road or notifying cars
to slide down and watch out during those pick up
and drop off times at school.
Speaker 4 (09:03):
So, Graham, the thing is, once you have connectivity, once
you have cameras, the use cases expand. They can tailor
to your needs. You could even sense based on the height,
based on the uniforms, based on timing. You could do
all those wonderful things. It's just a matter of your
imagination and how far you can take it.
Speaker 1 (09:25):
And you've talked a little bit about the technological benefit
of the five G protocol. Why is five G a
game changer?
Speaker 2 (09:34):
All right, thank you.
Speaker 4 (09:35):
This is my favorite topic because I really believe five
G is going to make the change that's needed in
the society. When LT came, you could see a lot
of applications, You could see a lot of enablement of
the app stores, but still latency was a big concern.
With five G, the latency reduced, the throughput increased, so
(09:58):
now you can be in more reliable situations. LT was
a good step because it moved from just the voice
calls to more an application world. But with five G
you can take it to a real life level. You're
just not playing games. You're moving beyond. You're impacting and
touching real lives now, on traffic signals, on waste management systems,
(10:22):
on power grades, and these are all real examples that
are happening in cities. You see it in Singapore, you
see it in Barcelona, you see it in Dubai. So
so many of these countries are already deploying these use cases.
Speaker 1 (10:37):
Let's pause here for a second to analyze what Asheesh
just said. You heard her mention both LT and five
G and the differences between the two. LT stands for
long term evolution. And when it was introduced, it served
as a significant upgrade from existing three G technology, but
it only offers a speed of one hundred megabits per second.
(10:58):
Five G, on the other hand, delivers up to twenty
gigabits per second. That's the speed improvement of two hundred
times now. Five GEN. Near edge is the intersection of
two technologies, five G network technology and edge computing. It
brings the power of local computing in your home, in
your car, or at the traffic lights, together with high
(11:20):
speed mobile networks. All this means is that these edge
computers can make super fast decisions at the locations where
it's critically needed. With that in mind, I asked Ashish
how cap Geminis roadside units work and how five G
technology can help vehicles communicate with one another to ensure
safety on the road.
Speaker 4 (11:43):
So roadside units and autonomous A vehicles will go hand
in hand. This will become more relevant than the autonomous
vehicles come into play. So imagine a traffic signal not needed.
That could be the future. Why is it needed today,
Because when somebody takes a break, other person needs to
(12:05):
come in. What if you can coordinate the two vehicles.
The edge can tell the vehicle at this moment, this
vehicle is going to intersect, so you don't need to stop.
You can slow down, and then the same signal from
vehicle to vehicle can go to other vehicles which can
tell them to slow down. So the traffic might slow
down a bit, but you don't need to stop in
(12:27):
a traffic signal. That's the extent that it can go
to because there's a communication between vehicle to vehicle. There's
a communication between signal to vehicle. So for now it
can be more efficiency, but going forward it can be autonomous.
Speaker 3 (12:41):
That's the future of it and JVS.
Speaker 1 (12:44):
Where have you seen other areas or other cities that
I've used this sort of roadside technology And it's a
two part kind of question. Is that plus using some
of the new kind of AI type technology that's coming
about and being able to improve the overall infrastructure of
these cities.
Speaker 3 (13:04):
Yeah, So this technology has been extensively adopted in India.
More than hundred cities have implemented po or less similar
technologies where roads that units play significant route. The biggest
challenge is traffic enforcement in this part of the world,
and to do the traffic enforcement, we need to consistently
read the license plate numbers in terms of the violations,
(13:24):
whether they're crossing the red light, or somebody's coming in
the opposite direction and so on and so forth. It's
extremely important from latency point of view because the MOMENTI process,
it has to coordinate with the red light and decide
whether it's a violation or not, and then it has
to immediately notify the violation along with the evidences.
Speaker 4 (13:43):
I can really see this RSU getting more useful for
violations because in India it's a very common practice for
people to not honor the traffic light. So one of
the things that's happening these days which is leading to
very good traffic management India is those sensors on the
traffic lights and with the IRISU coind off the situation,
(14:06):
you can read the number plate and you can get
to the violators automatically. And I hear that these days
a lot of tickets that are coming to homes with that.
Speaker 3 (14:16):
At this moment, we run twenty five smart City Command centers.
Almost every city has got this feature. And trust me,
in some intersections the moment the tickets come next the morning,
you would find everybody behind the line. So it's quite
effective in this part of the world.
Speaker 1 (14:31):
Yeah, that might also lead me to I guess another challenge. Particularly,
I'd like to get your thoughts about India's overall approach
to this, because in Europe and American and in some
regards Canada and Australia, we are very much concerned about
some of the privacy aspects of this, of the sensors
(14:53):
and cameras and being able to automatically detect violations and
things like that. How some of the safeguards being put
in place so that it can protect people's informations about
themselves and their movements.
Speaker 3 (15:07):
First of all, all this data that is being captured
at the near edge is anonymous meus, you have license plates,
you wondn't have any information about that person because there
is nothing called people databas here. Number two most important
thing is that once you get the data, once the
tickets are generated, it goes into the data centers where
(15:29):
the data privacy is given the most highest priority in
terms of data availability point of view.
Speaker 4 (15:37):
Let me chime in and the technology part that takes
care of this. The moment edge comes into play, security
does become a concern because you are out of the
data center hole security now, especially when you are on
a standalone edge. But the best part about edge is
also that the data is with the enterprise. If it's
(15:59):
the police to department or the traffic management department that's
handling the edge, then the data is only with that department.
Speaker 1 (16:08):
Okay, great, And we talked a lot about the edge
and near edge and kind of related to the privacy issue.
Are you working with that data in terms of generating
new AI models or some sort of machine learning side
of things to continually improve the system as a whole.
Speaker 4 (16:29):
That is correct, that data, even when it's anonymous, can
be used for analytics and can be fed into the
machine learning engine so that it can create more insights
as well as more behavior modification for the use cases
going forward, enabling more efficiency for the users.
Speaker 3 (16:48):
Absolutely, yes, Okay, we do very extensively the data from
an anonymous point of view, but we are also very
of the fact that depending on where we put these
censors we can collect the data. There are a lot
of biases also getting introduced into the system, so there
is always some sort of judgment that comes from the
officers there. Whether the model is really reasonably unbiassed is
(17:13):
always a challenge which we've been tackling on a regular basis.
For example, we know how to product the traffic. We
even know where most of the vehicles are stolen and
where to get tratory them and and what atom and everything.
Speaker 1 (17:26):
Is one coming up next on Technically Speaking and Intel Podcast.
Speaker 3 (17:33):
There's a huge appetite in public infrastructure to adopt technology.
I think we need to focus more and more on
affordable use cases.
Speaker 1 (17:41):
We'll be right back after a brief message from our
partners at Intel, Welcome back to Technically Speaking, an Intel Podcast.
I'm here now with Ashishiadav and Javis Rama Krishna. I'll
(18:01):
switch now a little bit to perhaps a real world
case study. JVS. You live in Hyderabad, incredibly busy city
in India. I'd like you to introduce the city to
the audience and how many people live there, How do
you describe the city, and maybe a bit of a
day in a life of a typical resident and some
of the challenges that they face.
Speaker 3 (18:21):
Absolutely, absolutely, that's been my favorite subject for some time.
Hyderabad is one of the upcoming, fastest growing city in
Asia and it is in the southern part of the
India give and take maybe more than a ten million population.
But it has got two distinct qualities. One part of
the city is foreign years old legacy city. The other
(18:42):
part of the city is akin to probably a San
Francisco or Perth. So what we're able to do is
we planned almost I think ten thousand cameras and one
hundred thousand community cameras to be brought into one network.
There's a huge, massive command center that didn't put in
from the security point of which is very normal in
any city. But what is more important areas the city
(19:03):
has taken a view of to do more and more
use AA from the safety point of view, to identify
the hotspots and coordinate with the first responders at patrolling
vehicles to go on time and all. So what I
should tell you is that in the whole process using
AA and the core technology, they were able to improve
on first responders time to average to around eight minutes
(19:26):
from us by fifteen to twenty minutes. Very important. The
safety parameters so are so well monitored by the government.
I think that's a plus point for the city. The
crime rates have come down. Second part is on the
traffic side. A lot of work has gone into master planning,
especially in the new part of the city and almost
around two hundred and twenty five intersections we're having traffic
(19:50):
enforcement technologies could be a red light violation, speed and
all camera based, vision based analytics and also to really
identify the the patterns of their traffic and help their
transportation planning. We are even putting close to one hundred
and seventifare intersections the ATYCC cameras which do the traffic
classification and content. This actually helped us to give a
(20:13):
real time congestion index in every arm of the intersection. Okay,
so the number of possibilities are very using technologists. But
all of these things use vision, they use edge compute,
they use air.
Speaker 1 (20:26):
AI technology didn't just help city officials in Hyderabad deal
with issues of traffic and congestion. It also allowed the
city to share infrastructure information across various agencies so that
they could improve the safety, security, and quality of the
utility companies. City officials can also plan better for big
(20:47):
events like how many cars and how many people will
stream into their city on any given day, and they
can prepare accordingly to ensure greater public safety for everyone involved.
And all of those insights, it's a dependent on AI.
(21:07):
Going back to the technology in the solution, JVS, you're
part of the L and T Technology Services which actually
created the LTTS Fusion platform. Can you tell us a
little bit about that platform and what role Intel played
in its AI functionality.
Speaker 3 (21:22):
Sure. What we've found is that there are many applications
IT applications which are coming in trying to solve a
traffic problem or trying to solve this safety problem and
so on. But at a city level, when we started
analyzing so many cities, we found that you need to
have a platform which can actually try to get the
insights out of geospecial data, video data, structured data all
(21:46):
together and generate some insights or recommendations to the operator there.
So we have got into this act created what we
call Fusion its LTTUS platform. So this platform has got
feature of developing applications on the top of it, could
be traffic, to be safety or could be multi agency operations.
Video ingestion has been the core technology for US, which
(22:10):
is where we have been working with Intel. Most of
our infrastructure runs on Intel architecture here and it's quite
useful from that perspective. But what we're also trying to
do now in North America is we started working with
Intel primarily to use some of the confondents like Getty
and Sceinscape to actually do a lot of edge side analytics,
(22:30):
especially from the highwast point of view, and we get
the insights and on the top of it, we are
now able to put in a Fusion platform from the
command center point of view, which will through analytics, which
will do sort of business rules or can throw recommendations
on the top of it.
Speaker 1 (22:46):
And when you're implementing it, what's the top challenge you've faced?
Speaker 3 (22:51):
There is a big need in this part of the
world in this type of traffic to have a green
channel for any ambulance going in. We have tried a
lot of technologies to really communicate using radios wherein the
ambulance goes and then the signal turns green, and so
on and so forth. But the challenge is considering the latencies,
considering the infrastructure of word we are. It didn't really
(23:13):
scale the way we want. Probably technologies like Fiji will
ease out to some extent, but there is still the
challenge in terms of clearing the people from the intersection
in this part of the world, after it turns green,
is still going to be on the grown. There's a
huge appetite in public infrastructure to adopt technology. I think
we need to focus more and more on affordable use cases.
Speaker 1 (23:34):
And this is actually now question for both of you,
how do you see ten years in the future given
the growth and speed of technology development as well as
societal changes and being more adoptive of these sorts of technologies.
It's just where do you think we're going to be
in ten years time?
Speaker 4 (23:55):
So cram in ten years not just technology challenges. We're
going to have these natural resource challenges that are going
to intensify, so using them efficiently is going to be
one of the key challenges. Let's talk with very basic
things water energy. The usage is something that you see
cities saying if you water your gardens, you will be penalized.
Speaker 2 (24:18):
Still, you go for a.
Speaker 4 (24:19):
Walk on the sidewalk, you see overflowing gardens with water
and lush green grass. So you can definitely have observation
units that can send data to cities. Especially in a
country like United States, you cannot have people resources patrolling
from the city, so you certainly can have sensors that
(24:42):
can send the data to city. You can certainly have
energy efficiently being used in terms of renewable energy. If
some areas are producing excess energy, it can be diverted
to other areas which need more, and you can have
tabs on which areas use and why, and you can
even go to the extent of making those appliances more
(25:05):
energy efficient based on the analytics. So, in my opinion,
energy is going to be a key factor in terms
of how we will see the world change in next
ten years. Technology will continue to grow, we have to
channelize it towards how do we make it more efficient
so that we use minimal without impacting the quality of life.
Speaker 1 (25:27):
For people JIVS. Whe do you see ourselves in ten years.
Speaker 3 (25:31):
The biggest challenge is going to be because of the
limited resources on the planet. I think sustainability is the
way I think all of us actually we have to
spend a lot of time and energy and money in
the technology supporting sustainability, either in terms of environment, water, power,
renewable sources, and so on and so forth. While we are
talking about all these things, I think what also comes
(25:53):
to my mind is the cybersecurity is going to be
an extremely important aspect. The more connected we are in
the more the cybersecurity is going to disup the way
we do and our habits down the line. I think
these are the two things which are going to change
the way we live.
Speaker 4 (26:11):
And living in the United States. In case you are
hit with some natural disaster. The quick recovery in terms
of using the technology to ensure that the areas can
be brought up quickly. That's another thing that technology will
play a big role in.
Speaker 1 (26:26):
Yeah, and I like the fact that you know, we
have talked about the big cities, but also talked about
some of the technology going to the smaller cities. And
I think that's what it's all about, is the technology
being able to be diffuse to all corners of the planet.
And just with that, I think we'll leave it this.
I thank you so much for your time.
Speaker 2 (26:46):
And JBS listening to you.
Speaker 4 (26:48):
I would like to visit Hyderabayt the next time I'm
in India.
Speaker 3 (26:51):
You are welcome, Ashish, I think you should visit. The
way they are doing seeing is believing.
Speaker 1 (26:57):
All right. Thank your Shish, Thank you, JVS.
Speaker 2 (26:59):
Thank you what pleasure talking to both of you.
Speaker 3 (27:01):
Thank you Graham for the time and ashes. Thank you
pleasure meeting you all.
Speaker 1 (27:07):
Thank you to A SHOESH and JVS for the insights
to today's episode of Technically Speaking. Many of you listening
to this podcast will have experienced the frustrations of city
traffic stuck on freeways, roundabouts, and intersections. My takeaway from
this discussion is that using the new advances in low cost,
low power, highly efficient edge devices will reduce the time
(27:31):
spent commuting in your car. Think about it this way.
If the adoption of smart city technologies saves you just
ten minutes a day or five minutes each way in commuting,
the time saving will compound and mean an extra full
week to spend with your family and friends per year.
According to the World Bank, currently fifty six percent of
(27:51):
the world's population live in cities. This is projected to
increase to seventy percent by twenty forty five. I believe
that city is with a high livability score will attract
the best talent and the best investment if they can
utilize their new trends in AI, edge devices and computing
techniques to improve the life of residence. As with all technology,
(28:12):
privacy protections of the individual must be topmost in mind,
as we may fall into an unwonted scenario of feeling
like we're always being watched. However, I am confident that
if we continue to examine and discuss the potential of
smart city technology and use AI ethically, we will see
metropolises from all corners of the globe continue to grow
(28:36):
and prosper. Join us again on Tuesday, June fourth, we'll
be exploring the technologies impacting the future of retail. Technically
Speaking was produced by a Ruby Studio from iHeartRadio in
partnership with Intel and hosted by me Graham Class. Our
(28:57):
executive producer is Molly Socio Our EP of post production
is James Foster, and our supervising producer is Nikir Swinton.
This episode was edited by Sierra Spreen and written by
Nick Firshaw.
No matter the location, from the global South to northern Europe,
from the far East to the American West Coast, life
in the modern day city is both exhilarating and exhausting.
Consider all the different cities you've visited throughout the world,
then try and take a mental picture of what you've seen.
(00:25):
Of course, you could focus on the luster of city life,
but don't forget about the traffic, the commotion, and the confusion.
I recently traveled to Italy with my family, and I
was crazy enough to drive through the narrow streets of Rome,
where local drivers take stop signs as suggestions. But in
the future, the chaos of busy city streets might become
(00:49):
distant memories of what city life used to be. The
rise of AI technology is making cities smarter. Urban planners
and city engineers are teaming up with some of the
eating minds in AI. Together they are streamlining how cities
can be more energy efficient, safer, and enjoyable than ever before.
(01:09):
Join us as we reimagine urban life and how we
interact with our surroundings in the smartest cities yet. Welcome
to Technically Speaking, an Intel podcast produced by iHeartMedia's Ruby
Studio in partnership with Intel. In every episode, we explore
how AI innovations are changing the world and revolutionizing the
(01:31):
way we live. Hey, then I'm grand class. Today we
take our episode to the city streets, where AI technology
is already making a tremendous impact across the globe. In
this episode, we will focus on how Intel's AI technology
is impacting local infrastructures and changing the urban landscape. Plus
(01:53):
we'll learn about real world examples where AI has changed
the way residents of one bustling city live, work, and
commute every day. But before we go any further, let's
welcome our guests. Joining us today is Ashshiyadov, the head
of Strategic Partnership, Alliances and Technical Product Marketing at cap Gemini,
(02:15):
a global leader in partnering with companies to transform and
manage their business by harnessing the power of technology. Cap
Gemini has partnered with Intel to develop the five G
Roadside Unit, which will improve five G communications between traffic
monitoring cameras, sensors, vehicles, and pedestrians, making cities run smoother
and safer for everyone. Welcome to the show, Ashiesh.
Speaker 2 (02:38):
Thank you Graham, It's so nice to be here. This morning.
Speaker 1 (02:41):
We're also joined by a JVS. Ramakrishna, a technology expert
who lives in Hyderabad, India, where local authorities have leaned
on Intel zeon servers as part of the solution to
address challenges around effective traffic management and ensure public safety
as the city has expanded beyond its limits. The strategy
has improved traffic flow significantly by identifying congestion hotspots and
(03:03):
dynamically adjusting signal timings, helping optimize travel times citywide. Today.
JVS is also the global business unit head for Sustainable
Smart World at L and T Technology Services, also known
as LTTS. Welcome to the show, JVS.
Speaker 3 (03:19):
Thank your Graham, pleasure to be here in the show.
Speaker 1 (03:26):
I think before we start discussing solutions on making our
cities smarter, I'd like to get both of your thoughts
about some of the common challenges cities face. When some
people think of busy city life, they think of congestion,
think of traffic, they think of safety concerns. I'm sure
some of our audience right now is listening to us
while in a traffic jam. When it comes to infrastructure,
(03:48):
how can we plan our cities? What sticks out is
the common problem most cities face. I'll start with you, Iseshesh.
Speaker 4 (03:56):
So traffic is definitely one of the most challenging part
of city life and there are many ways to solve it.
But for me also personally, I have a lot of
thoughts around how we can do it. Let's continue to
talk and we can tell more into it.
Speaker 1 (04:12):
Absolutely jvs.
Speaker 3 (04:14):
While technology plays a very important role, you know, I
come from part in India where traffic is like all pervesu.
I mean it's like everywhere and you would see millions
of people on the roads. But I think it started
with master about planning. Urban planning is the key in
terms of the city growth and how do the road
infrastructure is planned. Then follows the technology infrastructure.
Speaker 4 (04:37):
The cities are already planned, you cannot erase the lines
and create new roads. But I still feel technology can
do a lot of good even with all those I
would say misplanned roads, right, That's where the power of
technology comes in.
Speaker 1 (04:54):
Yeah. And it's interesting beside that because generally cities have
been planned from a historical perspective. If for example, in Perth,
it was an agricultural type city long time ago, so
the roads are designed for getting access to farmlands, and
now it's you know, obviously the metropolitan area has grown,
and perhaps that leads us into what is a smart city?
(05:15):
Maybe we could start a shish with what's your definition
of what a quite smart city is?
Speaker 4 (05:21):
So I would say a smart city's city that is
keeping the efficiency and quality of life of its citizens
at the foremost. Where I would say you are using
and integrating technology and communication efficiently so that everyday life
becomes easier and the challenges become less and less as
(05:45):
the city becomes smarter and smarters.
Speaker 3 (05:48):
I've been trying to figure out this definition for last
more eight nine years now, just to set the context.
In cities like San Francisco, Birth and all, they have
been planned historically. But most of the developing world where
there as a lot of infrastructure activity is happening, I think
that's where they have an opportunity to replan. But the
problem statements are different to different cities. What is a
(06:11):
smart city? In one small town of India where they
had a problem of unpredictable water supply, So people who
are like probably queuing up late night, you know, waking
for a water supply. If they get an SMS, they
know exactly when it's going to come. The water is
going to come right, so that's smart for them, Whereas
in big cities like Mumbai and Aderabat, it's all about traffic, safety,
(06:32):
utilities and a waste measurement so on. So I think
the definition varies, but ultimate it's all about production of
the wastage efficiencies, quality of life.
Speaker 4 (06:41):
I come from a small village in India and near
our village there is hardly any water, and today that
area is thriving. We may talk about a first world
country where smartness is more to do with sensing so
that I don't have to wait even one minute on
a traffic light, to somebody in a third world country
or a West country where even getting that water is smart.
Speaker 2 (07:03):
I agree with you, and.
Speaker 1 (07:05):
That actually leads us to thinking more about these sorts
of smart solutions. As she she've worked with five G
commercializations for a number of years. Now. Before we get
into the role five G plays in smart cities, we're
going to be hearing in this podcast episode the term
RSU or roadside unit a lot. Can you just help
(07:27):
us dissect what this actually means? What does five G
RSU mean?
Speaker 4 (07:33):
So five G is not just a fast data on
your phone or that five giken on your right top
corner of your phone. It enables much more because of
the low latency and high speed of the data. For example,
these roadside units could be just single server, harmless, small
service sitting somewhere and that could monitor and sense if
(07:57):
there is traffic. They can even sense if there is
a distin on the way the automous vehicle can take
a break, so they could enable that kind of interaction
between the pedestrian and the car. They could ensure that
the lights the signals are to the point where there
is less and less congestion, So it could be making
(08:18):
your traffic smarter. Because of the low latency, you could
have all those signals going out to the vehicles, to
the phones, if not the smart cars, and then making
it consistent also the signals on the lights based on
the sensors, on where the pedestrians are, where you could
(08:39):
prioritize the pedestrians, you could prioritize the bikers, you could
prioritize the congestion. All those things can be done with
the RSUs.
Speaker 1 (08:48):
I'm just thinking of another scenario, particularly around school zones
where I live. It would be nice to be able
to prioritize school students crossing the road or notifying cars
to slide down and watch out during those pick up
and drop off times at school.
Speaker 4 (09:03):
So, Graham, the thing is, once you have connectivity, once
you have cameras, the use cases expand. They can tailor
to your needs. You could even sense based on the height,
based on the uniforms, based on timing. You could do
all those wonderful things. It's just a matter of your
imagination and how far you can take it.
Speaker 1 (09:25):
And you've talked a little bit about the technological benefit
of the five G protocol. Why is five G a
game changer?
Speaker 2 (09:34):
All right, thank you.
Speaker 4 (09:35):
This is my favorite topic because I really believe five
G is going to make the change that's needed in
the society. When LT came, you could see a lot
of applications, You could see a lot of enablement of
the app stores, but still latency was a big concern.
With five G, the latency reduced, the throughput increased, so
(09:58):
now you can be in more reliable situations. LT was
a good step because it moved from just the voice
calls to more an application world. But with five G
you can take it to a real life level. You're
just not playing games. You're moving beyond. You're impacting and
touching real lives now, on traffic signals, on waste management systems,
(10:22):
on power grades, and these are all real examples that
are happening in cities. You see it in Singapore, you
see it in Barcelona, you see it in Dubai. So
so many of these countries are already deploying these use cases.
Speaker 1 (10:37):
Let's pause here for a second to analyze what Asheesh
just said. You heard her mention both LT and five
G and the differences between the two. LT stands for
long term evolution. And when it was introduced, it served
as a significant upgrade from existing three G technology, but
it only offers a speed of one hundred megabits per second.
(10:58):
Five G, on the other hand, delivers up to twenty
gigabits per second. That's the speed improvement of two hundred
times now. Five GEN. Near edge is the intersection of
two technologies, five G network technology and edge computing. It
brings the power of local computing in your home, in
your car, or at the traffic lights, together with high
(11:20):
speed mobile networks. All this means is that these edge
computers can make super fast decisions at the locations where
it's critically needed. With that in mind, I asked Ashish
how cap Geminis roadside units work and how five G
technology can help vehicles communicate with one another to ensure
safety on the road.
Speaker 4 (11:43):
So roadside units and autonomous A vehicles will go hand
in hand. This will become more relevant than the autonomous
vehicles come into play. So imagine a traffic signal not needed.
That could be the future. Why is it needed today,
Because when somebody takes a break, other person needs to
(12:05):
come in. What if you can coordinate the two vehicles.
The edge can tell the vehicle at this moment, this
vehicle is going to intersect, so you don't need to stop.
You can slow down, and then the same signal from
vehicle to vehicle can go to other vehicles which can
tell them to slow down. So the traffic might slow
down a bit, but you don't need to stop in
(12:27):
a traffic signal. That's the extent that it can go
to because there's a communication between vehicle to vehicle. There's
a communication between signal to vehicle. So for now it
can be more efficiency, but going forward it can be autonomous.
Speaker 3 (12:41):
That's the future of it and JVS.
Speaker 1 (12:44):
Where have you seen other areas or other cities that
I've used this sort of roadside technology And it's a
two part kind of question. Is that plus using some
of the new kind of AI type technology that's coming
about and being able to improve the overall infrastructure of
these cities.
Speaker 3 (13:04):
Yeah, So this technology has been extensively adopted in India.
More than hundred cities have implemented po or less similar
technologies where roads that units play significant route. The biggest
challenge is traffic enforcement in this part of the world,
and to do the traffic enforcement, we need to consistently
read the license plate numbers in terms of the violations,
(13:24):
whether they're crossing the red light, or somebody's coming in
the opposite direction and so on and so forth. It's
extremely important from latency point of view because the MOMENTI process,
it has to coordinate with the red light and decide
whether it's a violation or not, and then it has
to immediately notify the violation along with the evidences.
Speaker 4 (13:43):
I can really see this RSU getting more useful for
violations because in India it's a very common practice for
people to not honor the traffic light. So one of
the things that's happening these days which is leading to
very good traffic management India is those sensors on the
traffic lights and with the IRISU coind off the situation,
(14:06):
you can read the number plate and you can get
to the violators automatically. And I hear that these days
a lot of tickets that are coming to homes with that.
Speaker 3 (14:16):
At this moment, we run twenty five smart City Command centers.
Almost every city has got this feature. And trust me,
in some intersections the moment the tickets come next the morning,
you would find everybody behind the line. So it's quite
effective in this part of the world.
Speaker 1 (14:31):
Yeah, that might also lead me to I guess another challenge. Particularly,
I'd like to get your thoughts about India's overall approach
to this, because in Europe and American and in some
regards Canada and Australia, we are very much concerned about
some of the privacy aspects of this, of the sensors
(14:53):
and cameras and being able to automatically detect violations and
things like that. How some of the safeguards being put
in place so that it can protect people's informations about
themselves and their movements.
Speaker 3 (15:07):
First of all, all this data that is being captured
at the near edge is anonymous meus, you have license plates,
you wondn't have any information about that person because there
is nothing called people databas here. Number two most important
thing is that once you get the data, once the
tickets are generated, it goes into the data centers where
(15:29):
the data privacy is given the most highest priority in
terms of data availability point of view.
Speaker 4 (15:37):
Let me chime in and the technology part that takes
care of this. The moment edge comes into play, security
does become a concern because you are out of the
data center hole security now, especially when you are on
a standalone edge. But the best part about edge is
also that the data is with the enterprise. If it's
(15:59):
the police to department or the traffic management department that's
handling the edge, then the data is only with that department.
Speaker 1 (16:08):
Okay, great, And we talked a lot about the edge
and near edge and kind of related to the privacy issue.
Are you working with that data in terms of generating
new AI models or some sort of machine learning side
of things to continually improve the system as a whole.
Speaker 4 (16:29):
That is correct, that data, even when it's anonymous, can
be used for analytics and can be fed into the
machine learning engine so that it can create more insights
as well as more behavior modification for the use cases
going forward, enabling more efficiency for the users.
Speaker 3 (16:48):
Absolutely, yes, Okay, we do very extensively the data from
an anonymous point of view, but we are also very
of the fact that depending on where we put these
censors we can collect the data. There are a lot
of biases also getting introduced into the system, so there
is always some sort of judgment that comes from the
officers there. Whether the model is really reasonably unbiassed is
(17:13):
always a challenge which we've been tackling on a regular basis.
For example, we know how to product the traffic. We
even know where most of the vehicles are stolen and
where to get tratory them and and what atom and everything.
Speaker 1 (17:26):
Is one coming up next on Technically Speaking and Intel Podcast.
Speaker 3 (17:33):
There's a huge appetite in public infrastructure to adopt technology.
I think we need to focus more and more on
affordable use cases.
Speaker 1 (17:41):
We'll be right back after a brief message from our
partners at Intel, Welcome back to Technically Speaking, an Intel Podcast.
I'm here now with Ashishiadav and Javis Rama Krishna. I'll
(18:01):
switch now a little bit to perhaps a real world
case study. JVS. You live in Hyderabad, incredibly busy city
in India. I'd like you to introduce the city to
the audience and how many people live there, How do
you describe the city, and maybe a bit of a
day in a life of a typical resident and some
of the challenges that they face.
Speaker 3 (18:21):
Absolutely, absolutely, that's been my favorite subject for some time.
Hyderabad is one of the upcoming, fastest growing city in
Asia and it is in the southern part of the
India give and take maybe more than a ten million population.
But it has got two distinct qualities. One part of
the city is foreign years old legacy city. The other
(18:42):
part of the city is akin to probably a San
Francisco or Perth. So what we're able to do is
we planned almost I think ten thousand cameras and one
hundred thousand community cameras to be brought into one network.
There's a huge, massive command center that didn't put in
from the security point of which is very normal in
any city. But what is more important areas the city
(19:03):
has taken a view of to do more and more
use AA from the safety point of view, to identify
the hotspots and coordinate with the first responders at patrolling
vehicles to go on time and all. So what I
should tell you is that in the whole process using
AA and the core technology, they were able to improve
on first responders time to average to around eight minutes
(19:26):
from us by fifteen to twenty minutes. Very important. The
safety parameters so are so well monitored by the government.
I think that's a plus point for the city. The
crime rates have come down. Second part is on the
traffic side. A lot of work has gone into master planning,
especially in the new part of the city and almost
around two hundred and twenty five intersections we're having traffic
(19:50):
enforcement technologies could be a red light violation, speed and
all camera based, vision based analytics and also to really
identify the the patterns of their traffic and help their
transportation planning. We are even putting close to one hundred
and seventifare intersections the ATYCC cameras which do the traffic
classification and content. This actually helped us to give a
(20:13):
real time congestion index in every arm of the intersection. Okay,
so the number of possibilities are very using technologists. But
all of these things use vision, they use edge compute,
they use air.
Speaker 1 (20:26):
AI technology didn't just help city officials in Hyderabad deal
with issues of traffic and congestion. It also allowed the
city to share infrastructure information across various agencies so that
they could improve the safety, security, and quality of the
utility companies. City officials can also plan better for big
(20:47):
events like how many cars and how many people will
stream into their city on any given day, and they
can prepare accordingly to ensure greater public safety for everyone involved.
And all of those insights, it's a dependent on AI.
(21:07):
Going back to the technology in the solution, JVS, you're
part of the L and T Technology Services which actually
created the LTTS Fusion platform. Can you tell us a
little bit about that platform and what role Intel played
in its AI functionality.
Speaker 3 (21:22):
Sure. What we've found is that there are many applications
IT applications which are coming in trying to solve a
traffic problem or trying to solve this safety problem and
so on. But at a city level, when we started
analyzing so many cities, we found that you need to
have a platform which can actually try to get the
insights out of geospecial data, video data, structured data all
(21:46):
together and generate some insights or recommendations to the operator there.
So we have got into this act created what we
call Fusion its LTTUS platform. So this platform has got
feature of developing applications on the top of it, could
be traffic, to be safety or could be multi agency operations.
Video ingestion has been the core technology for US, which
(22:10):
is where we have been working with Intel. Most of
our infrastructure runs on Intel architecture here and it's quite
useful from that perspective. But what we're also trying to
do now in North America is we started working with
Intel primarily to use some of the confondents like Getty
and Sceinscape to actually do a lot of edge side analytics,
(22:30):
especially from the highwast point of view, and we get
the insights and on the top of it, we are
now able to put in a Fusion platform from the
command center point of view, which will through analytics, which
will do sort of business rules or can throw recommendations
on the top of it.
Speaker 1 (22:46):
And when you're implementing it, what's the top challenge you've faced?
Speaker 3 (22:51):
There is a big need in this part of the
world in this type of traffic to have a green
channel for any ambulance going in. We have tried a
lot of technologies to really communicate using radios wherein the
ambulance goes and then the signal turns green, and so
on and so forth. But the challenge is considering the latencies,
considering the infrastructure of word we are. It didn't really
(23:13):
scale the way we want. Probably technologies like Fiji will
ease out to some extent, but there is still the
challenge in terms of clearing the people from the intersection
in this part of the world, after it turns green,
is still going to be on the grown. There's a
huge appetite in public infrastructure to adopt technology. I think
we need to focus more and more on affordable use cases.
Speaker 1 (23:34):
And this is actually now question for both of you,
how do you see ten years in the future given
the growth and speed of technology development as well as
societal changes and being more adoptive of these sorts of technologies.
It's just where do you think we're going to be
in ten years time?
Speaker 4 (23:55):
So cram in ten years not just technology challenges. We're
going to have these natural resource challenges that are going
to intensify, so using them efficiently is going to be
one of the key challenges. Let's talk with very basic
things water energy. The usage is something that you see
cities saying if you water your gardens, you will be penalized.
Speaker 2 (24:18):
Still, you go for a.
Speaker 4 (24:19):
Walk on the sidewalk, you see overflowing gardens with water
and lush green grass. So you can definitely have observation
units that can send data to cities. Especially in a
country like United States, you cannot have people resources patrolling
from the city, so you certainly can have sensors that
(24:42):
can send the data to city. You can certainly have
energy efficiently being used in terms of renewable energy. If
some areas are producing excess energy, it can be diverted
to other areas which need more, and you can have
tabs on which areas use and why, and you can
even go to the extent of making those appliances more
(25:05):
energy efficient based on the analytics. So, in my opinion,
energy is going to be a key factor in terms
of how we will see the world change in next
ten years. Technology will continue to grow, we have to
channelize it towards how do we make it more efficient
so that we use minimal without impacting the quality of life.
Speaker 1 (25:27):
For people JIVS. Whe do you see ourselves in ten years.
Speaker 3 (25:31):
The biggest challenge is going to be because of the
limited resources on the planet. I think sustainability is the
way I think all of us actually we have to
spend a lot of time and energy and money in
the technology supporting sustainability, either in terms of environment, water, power,
renewable sources, and so on and so forth. While we are
talking about all these things, I think what also comes
(25:53):
to my mind is the cybersecurity is going to be
an extremely important aspect. The more connected we are in
the more the cybersecurity is going to disup the way
we do and our habits down the line. I think
these are the two things which are going to change
the way we live.
Speaker 4 (26:11):
And living in the United States. In case you are
hit with some natural disaster. The quick recovery in terms
of using the technology to ensure that the areas can
be brought up quickly. That's another thing that technology will
play a big role in.
Speaker 1 (26:26):
Yeah, and I like the fact that you know, we
have talked about the big cities, but also talked about
some of the technology going to the smaller cities. And
I think that's what it's all about, is the technology
being able to be diffuse to all corners of the planet.
And just with that, I think we'll leave it this.
I thank you so much for your time.
Speaker 2 (26:46):
And JBS listening to you.
Speaker 4 (26:48):
I would like to visit Hyderabayt the next time I'm
in India.
Speaker 3 (26:51):
You are welcome, Ashish, I think you should visit. The
way they are doing seeing is believing.
Speaker 1 (26:57):
All right. Thank your Shish, Thank you, JVS.
Speaker 2 (26:59):
Thank you what pleasure talking to both of you.
Speaker 3 (27:01):
Thank you Graham for the time and ashes. Thank you
pleasure meeting you all.
Speaker 1 (27:07):
Thank you to A SHOESH and JVS for the insights
to today's episode of Technically Speaking. Many of you listening
to this podcast will have experienced the frustrations of city
traffic stuck on freeways, roundabouts, and intersections. My takeaway from
this discussion is that using the new advances in low cost,
low power, highly efficient edge devices will reduce the time
(27:31):
spent commuting in your car. Think about it this way.
If the adoption of smart city technologies saves you just
ten minutes a day or five minutes each way in commuting,
the time saving will compound and mean an extra full
week to spend with your family and friends per year.
According to the World Bank, currently fifty six percent of
(27:51):
the world's population live in cities. This is projected to
increase to seventy percent by twenty forty five. I believe
that city is with a high livability score will attract
the best talent and the best investment if they can
utilize their new trends in AI, edge devices and computing
techniques to improve the life of residence. As with all technology,
(28:12):
privacy protections of the individual must be topmost in mind,
as we may fall into an unwonted scenario of feeling
like we're always being watched. However, I am confident that
if we continue to examine and discuss the potential of
smart city technology and use AI ethically, we will see
metropolises from all corners of the globe continue to grow
(28:36):
and prosper. Join us again on Tuesday, June fourth, we'll
be exploring the technologies impacting the future of retail. Technically
Speaking was produced by a Ruby Studio from iHeartRadio in
partnership with Intel and hosted by me Graham Class. Our
(28:57):
executive producer is Molly Socio Our EP of post production
is James Foster, and our supervising producer is Nikir Swinton.
This episode was edited by Sierra Spreen and written by
Nick Firshaw.
Host
Graeme Klass
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