GPS Activity Corrector

Mapped data before processing by our algorithm
Mapped data after processing by our algorithm
Main interface screenshot

GPS Activity Corrector

Runners and bikers from all around the world use various GPS tracking devices to measure their progress during their workouts. Unfortunately, bad weather conditions or trees can limit the accuracy of the measured data points.

At first glance, these errors might seem minor or insignificant. However, the even a few hundredths of a mile difference can effect the average pace by tens of seconds per minute.

Here's a few examples of such errors:

Maryville's Cross Country 8k course measured at 4.55 instead of 4.97 miles. For a 32:52 8k that's a difference between a 7:14 and a 6:36 pace per mile.

The Ijams South Loop measured at 11.58 instead of 12.00 miles.

Two of our group worked on the interface, using HTML, CSS, Flask, and Google Cloud. First, a responsive HTML page with CSS styles was tailored from a W3Schools template. Flask was layered on top of the html template to provide server-side interactivity. Flask is served, of course, by a main Python script that interacts with the data processing scripts. The Google Cloud Storage client is used for temporary storage, but the setup allows the app to be easily adapted to include storage for users’ previous processing tasks. The Google Cloud environment not only allows the system to be scalable, but gives many options for future integrations, including user management and the Google Maps API.