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This tip is about the how to get better GPS-Tracking Accuracy in Workout Apps. So read this free guide, How to get better GPS-Tracking Accuracy in Workout Apps step by step. If you have query related to same article you may contact us.
How to get better GPS-Tracking Accuracy in Workout Apps – Guide
Many runners have discovered the hard way that GPS-based apps and gadgets don’t accurately calculate distance. Official race distances are determined by a bicycle-mounted tachometer (cyclometer) rather than GPS, which often overestimates the distance. Unfiltered GPS data can result in significant overestimation errors. It can be more than ten minutes in a 26.2-mile run – the difference between qualifying for the Boston Marathon and not.
We care a lot about accuracy as a running software. We spend a lot of time talking to people about MapMyRun, and one of the most common questions we get is accuracy. We are continually looking for ways to improve it, given its importance. To improve MapMyRun’s accuracy, we’ve made several adjustments to the way we filter GPS data. This was no small undertaking. Thousands of races were analyzed, routes were measured by hand in several cities and hundreds of tests were carried out.
How to get better gps tracking accuracy in workout apps
Developing a new GPS filter
We are introducing new GPS filtering technology to MapMyRun to help athletes avoid large GPS errors and overestimations when tracking workouts. We are testing this through multi-month studies and a variety of methodologies. Over the course of these tests, we’ve seen that the improved filtering offers a very high level of accuracy when compared to measured courses, race tracks and results from other products. Let’s review some of the tests and what we learned from each.
The first step was to test the existing GPS filtering system to gauge its level of accuracy before making any improvements. We start by analyzing the data collected in a highly controlled environment. We observed GPS signals recorded on routes that we measured with a cyclometer, following the USA Track and Field preferred method. We literally measured these routes by hand! We then compared the GPS-based distance with the cyclometer-determined distance and found that the existing GPS filtering system overestimated the distance by 4-6%.
We then tested the existing GPS filtering system in a semi-controlled environment. Using technology that identifies races tracked by MapMyRun (as described in US Patent number 10331707B2), we identified over 500 races sanctioned by US Athletics (i.e., race courses were measured with a cyclometer). Comparing MapMyRun’s GPS-based distance, we found that the existing GPS filtering system overestimated the distance by the same 4-6% that we saw in our own controlled tests. The similar results in overestimation error with the controlled and semi-controlled tests gave us confidence in our baseline and gave us a significant target for improvement.
We took a close look at our GPS filters and identified several fixes that could improve accuracy, using this 4-6% overestimation as our baseline. We took advantage of numerical simulations to optimize our changes to the GPS filters, which reduced the occurrence of individual errors by 50%. This error reduction was mainly achieved by reducing the overestimation tendencies of the original GPS filters. Overestimation is caused by including incorrect GPS points in a tracked workout. Errors in these points cause the total distance to be longer than the actual training distance. Therefore, when the new GPS filters are applied and fewer errors become part of a workout, the speed and distance of the workout will be less than it would be with the old GPS filters or without any filters.
We validated the new GPS filters by re-running all the tests above with the new filters. We found that the new GPS filters significantly outperformed the original filters. The new GPS filters have reduced the overestimation to 2–3%, down from 4–6% with the original filters. We also compared the results of the same tests with the results obtained by Garmin™ wrist-based GPS running trackers and found that the new GPS filters produced distances of 1% for wrist-based running trackers, compared to 3-5% for the wrist-based running trackers. original GPS filters. The margin of error with the new GPS filters is much better, especially in reducing overestimation errors, which means that the new GPS filters will better meet industry standards and expectations.
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