Can Placemeter make life easier? CNN asks and answers

In the below video, CNN features Placemeter and our quest to make cities like New York better. Check out co-founders Alex Winter and Florent Peyre as they explain how Placemeter’s tech will one day make your life easier:

And an excerpt from the article:

In New York, a company called Placemeter is using feeds from hundreds of traffic video cameras to study 10 million pedestrian movements each day. It’s using that data to help businesses learn how to market to pedestrian consumers. Placemeter also says it wants to use the data to help consumers with information such as when to visit your neighborhood coffee bar when the line is shorter. Placemeter says it doesn’t store the video, nor does their analysis involve facial recognition.

Sound interesting? Find out more and help make your city better by becoming a Meter. Who knows? You may earn up to $50/month putting your window to work.

The Breathing City, Improved

By Jason Novack

A couple weeks ago, data analyst Joey Cherdarchuk published a beautiful visualization of the “Breathing City,” using census and open data to show how people move about Manhattan over the course of a typical workday. The animation offers a compelling look at the city’s land use and infrastructure challenges, and a glimpse of what life is like for the millions of people that live and work here.

Any project at this scale requires its creators to make a number of assumptions, and the Breathing City is no exception. To model where people spend their time throughout the day, Cherdarchuk used the American Time Use Survey by the federal Bureau of Labor Statistics. His acknowledgement that, “Manhattan probably has a different profile than the US average” inspired me to dig in to Placemeter’s data store and see if we can help replace this assumption with some real-world observations.

Placemeter uses live video feeds to collect data that describes activity at physical places. We are quantifying how people interact with one another, the city, and the infrastructure that defines it. With each passing day, our growing data set becomes exposes the underlying laws that govern life in our modern city—one of the most complex and fascinating systems in the world.

I started by pulling the foot traffic time series data we have in the areas surrounding Manhattan’s four major transit hubs: World Trade Center, Pennsylvania Station, Grand Central Terminal, and Port Authority Bus Terminal. I then cut out weekends and holidays and averaged the remaining days to generate a “typical” work day. The results show, as Cherdarchuk expected, there is a level of detail missing from the nationwide time use survey.

I found that not only are work hours in Manhattan different from the national averages, but they even vary by neighborhood within the city. Morning rush hour in the Financial District peaks right around 7:00 AM, while Midtown peaks at 8:20 AM. The data tells a similar story for evening rush hour. People working downtown head home about an hour earlier than people in midtown, 5:30 PM and 6:40 PM respectively. Both groups work a bit longer than the bulk of individuals surveyed by the Bureau of Labor Statistics.

WorkHoursComparison

Intuitively, these results make sense to me. Census data confirms that the finance industry dominates the economy around the World Trade Center. As such, their work schedules seem to follow market hours (9:30 to 4:00), with some time in the morning to catch up on news and prepare for the opening bell. Meanwhile, the finance industry makes up only 14% of the jobs near Grand Central Terminal as part of a much more diversified economy, including industries that follow traditional office hours (9:00 to 6:00).

Placemeter’s ability to track these differences allows us to provide the best data available. From improving pedestrian safety and optimizing park space, to aiding commercial real estate analysis and measuring outdoor advertisement campaign performance, we can serve a variety of applications in New York City and around the world.

If you would like to help us build a smarter city, visit placemeter.com and apply to become a Meter!

This week in cool computer vision GIFs

juggling
Via Gizmodo:

There hasn’t been much innovation in the world of juggling since the chainsaw was invented. But thanks to the work of Hiroaki Yamaguchi and Hideki Koike, who created a real-time tracking and projection system that can bring balls to life, busking is about to get interesting again.

Is this as cool as our data visualization? We think not. Is it more transfixing? You be the judge.

Live in NYC? Make you city better &
earn up to $50/month:
Become a Meter

 

Placemeter Named to Time Inc’s 10 NYC Startups To Watch

time-placemeter
If you noticed us blushing over here at Placemeter HQ, it’s because Time Inc. just named us one of their 10 NYC Startups To Watch. We’re humbled by the honor, and that much more driven for it.

Here’s the list:

It’s never been a better time to put your window to work: Become a Meter

 

Meet our newest team member: Tuan!

tuan

Tuan Hue Thi is the newest member of the Placemeter team and we’re very excited to have him on board. Tuan hails from Vietnam by way of Australia. He has a PhD in computer science, specializing in computer vision and deep learning. He’s joined the team as a Computer Vision Scientist. Read an interview with Tuan below.

Where’re you from?
I’m originally from Vietnam. I moved to Sydney to do my bachelors in software engineering for four years, then my PhD in computer science for three years.

My family is still in Vietnam. Normally I go back every year for the Lunar (or Chinese) New Year.

What first got you into computer science?
I got interested originally during high school. I went to a high school that specializes in physics, and my first programming language was Pascal. I did that in grade ten. A group of us entered a bunch of high school competitions. We won some, lost some. I entered the national olympiad for physics and got a silver. In Vietnam we have an intense university entrance exam, but because of the silver medal I didn’t have to take it.

From high school physics to software engineering makes sense. So many things in real life you explain using physics. In computer science you take those principles and can program using your knowledge of physics. For university In Vietnam, I started out by going to medical university and technology university at the same time. After half a year I got a scholarship to go to Sydney. So I moved to Sydney with this scholarship, and I switched to studying software engineering full-time there.
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