Human App - This is How We Move

Barbara Kerby, Freelance Journalist

San Francisco motorized transportation map

San Francisco motorized transportation map

Human is an activity-tracking app that tracks movement by millions of people in more than 900 cities worldwide, based on walking, biking, running or motorized transportation. The designers describe the app this way: “Human motivates people to move 30 minutes or more every day and hosts 20,000 Human Clubs where people share their daily activity and motivate each other to get active. The app was selected as an App Store Best of 2014, installed on more than 1M devices, and currently featured on every device in Apple Stores around the world.”

Even if iphone users are not using the Human app, the Health app on every Apple mobile device automatically tracks daily movement unless it is turned off by the user. All data from Apple devices is automatically collected as total minutes of exercise on the Human website. This blind data helps track actual movement in cities, not just from those who use the Human app. 

Average daily activity in San Francisco compared to the rest of the world.

Average daily activity in San Francisco compared to the rest of the world.

Data from 900 cities worldwide are available to anyone, even non-users, at http://cities.human.co to track the movements of app users. There are three options to view available movement data, including What’s Happening Now, which posts the number of minutes tracked in real time for each city. Next is the final average movement time data from the top eight cities worldwide from each category from the previous day. But the most interesting data show current movement on real-time maps. The maps are displayed as white lights on a black background. The lights move with the users; as they move the lights get brighter or fainter based on the number of users. Even during the middle of the night there are some routes with faint lights showing movement around the city. 

The most amazing thing about the Human app is that the designers only gave themselves ten days to work out the details. Translating 55 million points of data daily into graphics that inspire is not easy. While the statistics are interesting, the constantly changing maps tracking real-time movement may be what make people want to add their data to help their city’s movement statistics compared to the rest of the cities in the world. The friendly competition makes sense because the map designs are based largely on game mechanics.

San Francisco cycling map

San Francisco cycling map

The original maps used Google map grids under the data, but plotting so many data points of human movement created its own map, so a design decision was made to delete the grid map. This made the maps easier to read. This proved to be a good decision since user data show people who use the app increase their exercise by 75% in a six-week period.

To protect the privacy of users, data exports are limited and files are merged to prevent a way to connect activities to individual users. Data is also connected to individual cites by collecting all locations per city into one dataset. According to their website, “Our infrastructure is entirely built with Amazon Web Services. We use an RDS (MySQL) database to store stats for individual activities. Roughly 10 terabytes of motion and location data for activities currently sit on [Amazon] S3. GPS boundaries for chosen cities allowed us to select the correct JSON files from S3, which were then converted to CSV. A simple multithreaded Python script opened connections to S3 and ingested thousands of files per minute.”

San Francisco walking map

San Francisco walking map

The tool used to create the maps is R. Designers quickly found out opacity is the key to making the maps easy to read. Amsterdam was the first map created, and it underwent the most changes. Besides deleting the grid, experiments were done with color and opacity. But one size does not fit all. Major US cities such as New York and Los Angeles work best with an opacity of .025 while Copenhagen and Cape Town work best with 0.1.

Designers also decided that showing a 30 second video of actual movement over a 24-hour period would be more effective than a static map. According to the website, “With the command line tool ffmpeg it's possible to easily render a movie out of a sequence of images. This is where AWS really came to the rescue. An extra large EC2 instance based on this Rstudio AMI by Louis Asslet doubled your computing power in little less than an hour. To make a 30 second video at 24 FPS, you need 720 frames. Based on the timestamp of a location point, we calculated the local time of day, and used that to assign a point to one of 720 frames. Points disappear after being visible for 60 frames (2 hours), which made a total of 780 frames per city. We rendered these for a small selection of cities.”

Animated San Francisco running map

Animated San Francisco running map

In addition to all the data collection and design work, they also had to create a website to show the data, and create a Facebook page and Twitter account for reaching social media. To keep it simple, yet aesthetically pleasing, they used the Sketch program for all virtual design. The typography and layout was classic. All charts are based on amassed stats using D3.js. The website was built using a simple grid via Cactus, and was completed in one weekend. To stay on track, all decisions were made live, without any emails.  Through their determination to keep it simple, the designers met their self-imposed deadline.

On November 18, 2015 San Francisco was ranked number 18 in the world for the most exercise.

On November 18, 2015 San Francisco was ranked number 18 in the world for the most exercise.

A nice side benefit of the maps is giving the public and business sectors ways to get information that helps them get business or find friends. By highlighting the areas where people are already exercising, users have a way to find safe routes for walking, running or riding bikes. Clubs could recruit based on this information since foot and pedal traffic is already using these routes. Businesses could cater to those clubs and other foot traffic in the area.

This data could be used in other ways to benefit the resident of San Francisco. The city is already trying to create safe places for foot and bicycle traffic, so using the Human maps could give them real-time data of the routes residents are already using. This could cut down on the time and money the city would have to spend on data collection about current movement patterns. The data show that although people talk about how great it is riding and running on the hills, the major routes are in the flatter areas of the city.

Fall 2015 Volume 8 Issue 2