The Living Network - Consciousness

In this episode, we explore the revolutionary concept of a living network with Prof. Dimitra Simeonidou, Director of the Smart Internet Lab. Discover how data and AI can transform our urban environments into intelligent ecosystems that enhance our quality of life. From traffic management to public health, learn how the infrastructure we already have can become a sensor-rich network, improving our cities for both citizens and nature. 

Chapters:
(00:00) Introduction to Smart Internet Lab
(01:15) The concept of a living network
(05:30) The role of sensors in urban environments
(10:45) AI and the evolution of smart networks
(15:10) The implications of conscious networks
(20:00) Future applications and the timeline for implementation
(25:30) Conclusion and next episode preview

This is an 18Sixty Production.

Transcript

>> Paul Wilson: Our cities are getting more congested, they're getting more and more complicated to live in. So if we could use data to make the way the city works work better for us and for nature, then why wouldn't we do that?

>> Host: If you wouldn't mind getting us started by just explaining your vision for what it is that Smart Internet Lab is working towards.

>> Prof. Dimitra Simeonidou: We are creating the giant sensor that actually gives us all the time information of what is happening around this ever present communications infrastructure that's almost a biological function. A living, living network. This is not science fiction. This is going to happen.

>> Host: Welcome to the Living Network from the Smart Internet Lab at the University of Bristol. Episode 1 Consciousness that voice you just heard was Paul Wilson, Director of the Smart Internet Lab and chief scientific Advisor to the European Commission. But before we can understand the idea of this living network, we need to take a step back and talk about sensors.

>> Prof. Dimitra Simeonidou: When we are looking at telecom infrastructures, there has always been the case that this infrastructure connect devices at the end of networks. Certain devices could be your WI fi routed in the home, it could be your smart metering system in the home, could be cameras that we are using for surveillance and so on. But when usually we are talking about sensors is really what we call Internet of things, where actually we are having platforms of sensors that for instance they are measuring air quality or they are looking at traffic congestion, or for instance when we are looking at digital health, we are looking at assisted living biometric sensors. So usually sensors are devices that they are connected at the end of a network infrastructure and then they're connecting among themselves in order to provide information. And usually the information that we are getting is very specific to what we would like to measure. For instance, sensors in the water to look at water quality. And that has been up to now. And we have been developing networks, for instance 4G, 5G now 6G. And always one of the things that we are looking is how many sensors we are going to be able to connect in these networks. Oh, I'm going to connect 1 billion sensors. I'm going to connect 1 trillion sensors. With what we're discussing here, we are moving away from this. we're not saying that we're not going to connect sensor platforms in the network, but what we are saying, the network itself acts as a sensor. So the network itself, when you are having a WI FI device in your house, this WI FI device is ready to detect how you move in your house. So in an assisted living scenario of the future, then you Wouldn't need to wear a biometric sensor or any additional device because your WI fi router in your home could actually look at movements or lack of movements. And it's going to be able to exactly locate where you are inside your house, you know, downstairs, upstairs. And this is the difference. And quite a lot of times very difficult to actually change your mindset. To think about this, what we have put already in place, and that could be our fiber broadband, the WI fi router, or our satellite connection, things that they're there in place with a primary focus to connect people and connect things. Now this infrastructure actually is there to sense the environment, to sense the infrastructure itself.

>> Host: So, a giant, potentially global network that has the ability to sense what is happening around it. But how does it learn to do this? Paul Wilson from the Smart Cities World Advisory Board.

>> Paul Wilson: You've got to think about these networks that are sensing networks. We can learn actually how humans develop their understanding of sensing. When a baby is born, it doesn't have all the information in its mind to understand the world around it. And that's why it's quite useful. It can't walk so quickly because it needs to learn that bumping into things causes pain or putting your hand on a flame, you'll get burned. Babies, they don't know this. They only learn it by doing it. And thankfully they've got a sort of two year period during which time their parietal lobe in their mind is developed with an understanding of sensing. And then it can learn as it develops its physicality for walking, that, it's not a good idea to walk into a wall, or it's not a good idea to stick my hand in a flame. But that is, each of us had to learn that. And we learned it over a couple of years. Well, with these networks they're sensing, they begin to understand the real world around them, that a building is a building, a tree is a tree, a road is a road, and a car moves. These are, the network doesn't know that. But over time, if you train the network to know that, the network can learn that. And this is exactly where AI and networks combine. So you start to use the physical network that's spread all over the world, everywhere you begin to train AIs that, oh, when that amount of vibration happens in the network, it means a car went by a car. And then even more clever, a car of this weight went by, or that's a person walking by, or that's a tree rustling in, in the wind. And with the Advent of AI. we can increasingly use those networks to understand that, that is, that this gives an incredible level of cognition to this sensing network or the living network.

>> Prof. Dimitra Simeonidou: So we have networks that they use their sensory data to actually learn. Yes. And extrapolate. And so knowledge is a byproduct. And then quite a lot of the learning could actually be actionable. So I get the information, I learn, I action if I need to action. That's almost a biological operation, you know, biological function. And that is conscience. So you build conscience over the time. Your network knows about the city, your network knows about the citizens. Your network understands even before some emergency happens, that something is going wrong and is going to happen. And therefore at the point that something bad is going to happen because you have a good natured network is going to action, some intervention. And you can take this from a local, from a city to a global. At that point you have something that looks like a global conscience and that is taking beyond to what we have called up to now, intelligent networks, cognitive networks, to that situation that you are having a conscience. A, living network, a biological network, which is a very exciting thing.

>> Host: Exciting, absolutely. A conscious living network, but also maybe slightly scary.

>> Paul Wilson: Immediately once you realize that that can be done. You have given computing and AI the ability to understand the physical world. So most the AI we're doing with today, it's all come off the Internet. It's words, videos. Once you train AIs to understand the physicality of the real world, actually what you can do next is both helpful and of course it doesn't take long to say. Also very frightening and particularly when you add in robotics into that, because the network can then understand the physical world and it can create actuators in the physical world that we call robots, drones, other autonomous systems. This honestly is pretty frightening or wonderful. It's wonderful if we get a grip on it. It's frightening if we let bad actors get in charge of it.

>> Prof. Dimitra Simeonidou: We are going to start directing with robots more and more and more that's going to come part of our life because that's a huge future of AI. So robots by themselves, they have sensors and they are intelligent. So actually robots by themselves, we have, we are going to have a lot of information about this, robots autonomous systems. What this extra sensory or sensing information is giving is some context and some information of robots within their environment. So it's not only I'm actually controlling a robot, but actually I can understand where the robot is moving, what the environment looks like. And you do that in a way that is there all the time. So hopefully we are not going to have robots attacking people, because we are always going to see in context where the autonomous element is a robot, with what is happening, what else is happening in the environment. I know that this is a little bit of a future example, but this is quite an important. And it's a guardrail in manufacturing. They are going to be, for instance, working on a production line in a, nuclear plant. They may be working on things that we don't want to send people to do in a city. They may be cleaning our parks. And that's where it becomes quite interesting, because if you have your robot cleaning your park, then of course, you don't want that to interfere with people that they're having picnics or children that they play. We are going to see robots in our hospitals. There are so many examples that we can see actually robots being introduced already. And that is going to happen more and more.

>> Host: The next big question that needs to be asked is, why? Why do we need this?

>> Prof. Dimitra Simeonidou: Well, it's a byproduct of what we created already. So we have, I mean, all of us, we have a mobile phone, and all of us, we are connected to the Internet. I mean, vast majority of us. I know that there are still connectivity gaps everywhere. But the thing is that we have this infrastructure that is there in very, very high density in cities, under the water, in the oceans, you know, up in the sky, with satellites is already there. Now, what is more recent is actually getting your information from your wireless infrastructure, because that information is very much related to what is happening around, for instance, where people, where you have huge, big density of people, where people are moving, is going to give you a lot of information that you can use, hopefully in a useful way.

>> Host: Dimitra talks about large volumes of people, areas of dense population, cities. And one big use for this new technology, this living network, is to optimize our cities. Paul Wilson.

>> Paul Wilson: As more and more people live in cities. So today, more than half of the world's population lives in cities, rising to like two thirds, three quarters by the middle of the century. And it means that a million more people live in a city every week than they did the week before. So our cities are, getting more congested, they're getting more and more complicated to live in. So if we could use data to make the way the city works work better for us and for nature, then why wouldn't we do that? In fact, it's almost the most noble calling of the technology industry. To try to crack that nut. So actually when it comes to transport, probably you need to declutter the roads, but you can start to automate traffic flows using traffic signals, traffic lights as they're called. you could start to improve the flow of the traffic in the system city with better ability to plan that kind of model of getting the data, thinking through the problem and then increasingly automating some of the solutions. You can then apply that to all sorts of facets of the city from the water system, the energy system, and even down into health systems and public health systems as well. So it depends on which lens you want to bring it through next as, to what problem you're solving, as to where you apply. But it's the same methodology that you'd apply in every facet.

>> Host: We're talking about the future, about things being developed and evolving quickly. When can we expect to see this happening?

>> Prof. Dimitra Simeonidou: Sensing and AI hosting within the network are being discussed as key features of SIGG Seek. The the earliest that is going to be launched is about 2030, but many people predict it for later. but I think some of this we are going to see them coming earlier and they're going to be creeping in.

>> Host: The Living Network is coming and sooner than some may think. Join us next episode where we'll discuss and how do we control and regulate the growth of a conscious global network? Is it even possible?

>> Prof. Dimitra Simeonidou: We have to go fast and we have to tell the regulators, we have to inform our policy people within the government. Yes, we have to go fast, but please do not go so fast that we cannot actually recover afterwards. So fast with assurances. That's the important thing.

>> Host: You've been listening to the Living Network from the University of Bristol's Smart Internet Lab. This was an 1860 production. The producer was Kate White.