Why City Planners And Public Officials Should Embrace Smartglasses

When people talk about use cases for smartglasses, they usually start with app-based examples. Maps that allow users to follow directions without having to look down at their phones are popular, and for good reason – we've all been stuck behind someone moving at a glacial pace while they are absorbed in following a map. Responding to texts and emails, looking at interactive 3D content, and listening to music and podcasts are all other examples of consumer-focused apps that will no doubt drive individual adoption of the devices.

And while the head-mounted cameras on the glasses have drawn both praise and criticism for their ability to seamlessly and unobtrusively take photos for personal and social media use, they also provide an even bigger opportunity. When enough people start to wear the glasses on a daily basis and stream while they are walking around in public, they are helping to create a massive spatial data set that will empower the next generation of builders in the physical space. Pretty soon, we could have digital twins of the real world, and this would empower everyone from city planners to robotics manufacturers.

Start with one of the most common and yet difficult to solve problems for any city – fixing hazards on roads or sidewalks. The new mayor of New York City, Zohran Mamdami, went out of his way to highlight the fact that his team paved over a hole of the base of the Williamsburg Bridge that forced cyclists to brake quickly (and in some cases to crash). While some laughed it off, this is actually a core function of city government, and the reason it drew outsize attention was that cyclists had been sharing images and complaining for a long time. But for every Williamsburg Bridge bump, there are millions of hazards that go unnoticed or unreported, because there's not a system in place to easily capture and share the data. Dubai is an outlier in that it has an app where citizens can report hazards and track repairs , but that still requires someone taking out a phone, using an app, and filing a report. If you're rushing to get to work or herding kids to school, you might not have time to take those extra steps.

Now imagine a world where that data is transmitted ambiently. At first, there will likely be an additional step to reporting problems; a user will have to prompt the glasses and say "report road hazard" to send an image and location. But after enough data is built up at scale, the system will be trained well enough to recognize the hazard and file a report. Ideally, all of this would be made publicly available so that governments can be held accountable when they fail to fix problems (or credited when they do).

This data can also be used for crowd control and mitigation. Heatmaps can show where there is overcrowding and solutions can be deployed to solve it. This again creates a data-driven accountability structure – if the same train line shows massive overcrowding on a regular basis, more trains can be added, for instance, and if the problem isn't solved, those who control the solution can be held accountable.

It can even extend to third party apps. While Google Maps sometimes will show location is more or less busy than usual, it's a pretty imperfect measurement. If the glasses capture a heatmap in a restaurant that shows that it is full to capacity, apps like Google Maps and Yelp can temporarily stop recommending it, because no one wants to wait around just to be told there's a two hour wait for a table.

Spatial data at scale won't just benefit governments and individuals – it will eventually power robots as well. A full spatially mapped digital twin of a city will include all the edge cases that sometimes befuddle delivery robots and cause them to freeze up. And as robots take on more tasks inside the home, people will be incentivized to create digital twins of their living spaces, including all the indoor edge cases (new furniture, dog toys on the floor, etc). This data will have to be treated differently and held to a much higher privacy standard, but if wearing your glasses at home means never having to vacuum or fold laundry again, lots of people would go for it.

One of the reasons LLMs work so well today is the sheer amount of data they draw on. In the not too distant future, smartglasses could do the same for the physical world, and the results could transform the way we interact.

This article was originally published on Forbes.com