AI is making mapping devices smarter, and Location of Things navigation is becoming a reality. To learn more about how cloud-based, AI-powered location technology is bringing us closer to a world of autonomous cars, connected cities, and more, don’t miss this VB Live event!
The map is evolving, says Peter-Frans Pauwels, co-founder of TomTom. Cloud-based maps, built in real-time from a vast array of aggregated individual data points, are the foundation of the “the location of things” — an increasingly valuable corollary of the internet of things.
The internet of things is a network of billions of connected devices; the location of things offers a new dimension to that network: the context of those devices. The result is a living map, or virtual representation of the world in real time.
“We’ve always felt that location is going to be so important in so many applications,” Pauwels says. “You need to have the right details, the right freshness of the data, in order to build applications that might very well be critical in terms of life and death.”
That’s clearly applicable in the case of autonomous driving, one of the more fashionable applications of live maps and location data. AI stirred into the mix adds critical immediate insight to the increasingly detailed input from video and photo and radar, and also broadens what we know of the world around that vehicle, from immediate congestion reports to smart construction of daily traffic patterns.
We’re not at real time yet for every aspect of the map, Pauwels says. Things like traffic information, sure. But for things like major road construction work, the time between data aggregation and the resulting report about conditions still lags behind about 48 hours. But that’s still a major leap from the average of three months, just three years ago. And that’s just scratching the surface, he says.
“In a couple of years we’re going to see a whole range of new applications that will become possible because we’re now building this infrastructure, this real time map, that is in itself driven by AI,” Pauwels says.
We’re getting closer to real time every day, he explains, and closer to handling logistics issues. For instance, even solving for irregular spikes in traffic — not commuter time traffic jams but the snarl that could occur as a football game lets out and the weather kicks up — is a huge step forward.
“That’s the correlation of different events, happening in different dimensions,” says Pauwels. “And that’s where you need to have AI.”
Simple sensors that can detect temperature, pressure, humidity will pop up in more and more places, Pauwels predicts, offering more and more detailed information about the weather, about the state of the asphalt on the road, whether it’s frozen or very warm, which impacts tire pressure and fuel consumption.
But taking that data, plotting it over time and feeding it into a neural network means you can start asking questions about how the climate is changing, what can be done with these over-time changes in the patterns, and how do they correlate to other events, beyond just daily traffic. This data is the seed of the smart city and it’s about to sprout.
Origin and destination matrices, which look at where people move throughout the city, are the key. Where do they tend to come from? Who moves from where, on the grand scale? How do they get there?
Then, as a local government, he says, you can start thinking, “Okay, how do we make sure that the infrastructure is up to date, or that we have the right form of public transport in place?”
Car service companies are already in the mix, using location-based data to make sure that their drivers are in the right places when demand occurs — for instance, when the BART train in San Francisco arrives and spits out a couple of hundred people, there’s a good chance a number of them will be hailing a lift to their ultimate destination.
“We can take this forward to the smart city of the future, where the dream is that every individual will be able to just get mobility as a service,” Pauwels says. “These are the smart city applications in transport that we’re looking at, working together with the Ubers of the world and local governments to look at connecting the very different types of transport networks we have today.”
There are concrete applications for things like waste management, too, he says. Where does it happen? Where does waste get collected? Where does it need to go? How can you better plan around that? And even online delivery can be made more efficient in a smart city, and reduce carbon footprints.
But, he says, it’s still early days.
“For a lot of industries out there, they’re struggling to understand the power of AI, the power of data, the amount of data out there and the intelligent things you can do with it,” Pauwels says. “Location ties what we’re doing in the digital world to the real world. That’s where the next battlefield and field of opportunity is going to be.”
To learn more about the opportunities location data is opening up, from smart city applications to retail, industry, and more, don’t miss this VB Live event.
Don’t miss out!
In this VB Live event, you’ll learn about:
- Leveraging the power of the cloud, AI, and machine learning across devices by contextualizing location data in real time
- The role of location-based data mapping in the “Location of Things”
- The application of data-enriched mapping to industries like retail and automotive
- How “Location of Things” powered by geographical data can be used to connect autonomous driving, smart mobility, and smarter cities
- Chris Pendleton, Principal PM, Azure Maps
- Jennifer Belissent, Principal Analyst, Forrester
- Peter Frans Pauwels, Co-founder, TomTom
- Rachael Brownell, Moderator, VentureBeat
Sponsored by TomTom