[youtube https://www.youtube.com/watch?v=FZ8ODREybcs?rel=0]

About 9 months ago I wrote about a new startup called Urban Engines that was trying to improve urban mobility by using big data to optimize transit usage. 

Last Tuesday the app launched in 10 cities across North America. So if you’re in Boston, Chicago, Los Angeles, New York, Portland, Seattle, San Francisco, Toronto, Vancouver, or Washington D.C., you can go ahead and download it right now.

The biggest “wow factor” is probably the augmented reality feature that allows you to hold your phone up and see transit information overlaid on top of the street in front of you.

But more fundamentally, the real potential lies in the platform’s ability to collect data on the way people move in cities and on how transit lines are performing, so that it can be fed back to improve overall efficiency.

That’s why the company is also working with cities to give them 24/7 analytics and reporting on how every bus, car, and train is performing in their networks.

My hope is that with better data at our disposal, we’ll be able to elevate the discussions around transit and transit planning. Without great data, it’s too easy for these discussion to become political.

At the beginning of this year I wrote a post about a mobile tracking app called Moves that I had heard about through my friend Sachin Monga. He had just published a beautiful set maps showing where he physically spent his time in both Toronto and San Francisco.

His post spurred me to download the app and at the end of my post I promised to share my own set of maps once I had collected enough data points. It’s only been about 3 weeks, but already my maps are starting to fill out, so I thought I would do a release.

The orange lines represent transport of some sort (car, subway, streetcar, and so on) and the green lines represent walking. I don’t cycle very often in the winter (I know, I’m a fair-weather cyclist), so you won’t see any of those lines just yet. However if I posted a map from the summer, I know it would look completely different.

Here’s a first one showing a regional scale:

Here’s a second one showing the city of Toronto:

And here’s a third one showing mostly downtown:

What’s interesting about these maps is how much you can tell about me and the way I move around the city.

For one, there’s a good chance I ski or snowboard given that I’m driving up to Collingwood, Ontario in the winter. You can also see how heavily dependent I am on the Yonge subway line, which is the thickest orange line in the middle of downtown. It’s also interesting to see how localized I am within my neighborhood (St. Lawrence Market). I walk to get groceries. I walk to the gym. I walk to coffee. And the list goes on.

[youtube https://www.youtube.com/watch?v=FZ8ODREybcs?rel=0]

About 9 months ago I wrote about a new startup called Urban Engines that was trying to improve urban mobility by using big data to optimize transit usage. 

Last Tuesday the app launched in 10 cities across North America. So if you’re in Boston, Chicago, Los Angeles, New York, Portland, Seattle, San Francisco, Toronto, Vancouver, or Washington D.C., you can go ahead and download it right now.

The biggest “wow factor” is probably the augmented reality feature that allows you to hold your phone up and see transit information overlaid on top of the street in front of you.

But more fundamentally, the real potential lies in the platform’s ability to collect data on the way people move in cities and on how transit lines are performing, so that it can be fed back to improve overall efficiency.

That’s why the company is also working with cities to give them 24/7 analytics and reporting on how every bus, car, and train is performing in their networks.

My hope is that with better data at our disposal, we’ll be able to elevate the discussions around transit and transit planning. Without great data, it’s too easy for these discussion to become political.

At the beginning of this year I wrote a post about a mobile tracking app called Moves that I had heard about through my friend Sachin Monga. He had just published a beautiful set maps showing where he physically spent his time in both Toronto and San Francisco.

His post spurred me to download the app and at the end of my post I promised to share my own set of maps once I had collected enough data points. It’s only been about 3 weeks, but already my maps are starting to fill out, so I thought I would do a release.

The orange lines represent transport of some sort (car, subway, streetcar, and so on) and the green lines represent walking. I don’t cycle very often in the winter (I know, I’m a fair-weather cyclist), so you won’t see any of those lines just yet. However if I posted a map from the summer, I know it would look completely different.

Here’s a first one showing a regional scale:

Here’s a second one showing the city of Toronto:

And here’s a third one showing mostly downtown:

What’s interesting about these maps is how much you can tell about me and the way I move around the city.

For one, there’s a good chance I ski or snowboard given that I’m driving up to Collingwood, Ontario in the winter. You can also see how heavily dependent I am on the Yonge subway line, which is the thickest orange line in the middle of downtown. It’s also interesting to see how localized I am within my neighborhood (St. Lawrence Market). I walk to get groceries. I walk to the gym. I walk to coffee. And the list goes on.