Accurate, real-time location data drives optimized performance
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By: Becky Harris
Yesterday kicked off the Race Across America, a 7–9 day, non-stop, cross-country bike race billed as the toughest bike race in the world. Starting in Oceanside, CA, RAAM spans 3000 miles, climbs 175,000 feet, crosses 12 states and finishes at City Dock in Annapolis, Maryland
Ultra Cyclist Dave Haase is one of 39 single male riders competing. This year’s race marks Dave’s 7th time participating, with second place finishes in 2015 and 2016. This year, his team of performance analysts and data scientists is incorporating Mapbox’s real-time asset tracking architecture and map visualization capabilities into their analytical set-up to help give him the edge for first place.
Optimizing Dave’s performance is a major key to success. He’ll ride on average ~400 miles, with ~90 minutes of rest per interval, over the course of his 7–9 day ride. As he does, his team will be managing his internal temperature and blood oxygen levels, to ensure he is utilizing energy as effectively as possible while staying safe. His team will run analysis to determine the best rest times, based on his biometric levels as well as weather forecasts on the upcoming stretch of the route. Haase wants to ride when the weather (wind, temperature, sun, rain) is most in his favor, so taking a rest to avoid a particularly hot part of the day or to avoid a headwind helps optimize his time.
Dave’s team has set up an intricate system to collect, process, analyze, visualize, and optimize his ride. First, they will collect biometric data from several different sensors to create what they fondly call the “Internet of Dave”. They then combine this data with other datasets such as weather forecast data, Haase’s real-time location data, map, and route data, and process it using machine learning to produce recommendations to help Dave optimize his ride.
This year, Team Haase is using Mapbox’s Asset Tracking Solution Architecture to track the real-time location of Haase as well as his competitors along the route, and combine Dave’s biometric data with his location to train their machine learning models. They have also built an online fan experience that allows people to watch Dave’s ride in real-time on a Mapbox map, alongside competitors.
Team Haase believes that combining the best technology with real-time data can keep Dave on the right side of the “line” between greatness and catastrophe, to help him get to the finish line faster and more efficiently than anyone else.
Team Haase’s use of real-time data is a great example of how serverless technology coupled with Mapbox’s real-time asset tracking capabilities can help companies coordinate complex logistical operations and effectively move things or people through space.
And follow Team Haase’s progress through the Race Across America at raam.davehaase.com.
Team Haase partners with Mapbox for 2019 Race Across America bid was originally published in Points of interest on Medium, where people are continuing the conversation by highlighting and responding to this story.