Decision Analytics
Objective
To collect and process data collected from an athlete’s bike sensors, such as biometric data, exact location and upcoming weather conditions with the goal of enhancing decision-making and performance during the Race Across America.
RAAM is widely considered to be one of the toughest endurance tests in the world. Crossing four mountain ranges and three desserts, cyclists travel 3,000 miles from the west to the east coast of the United States. During the Race Across America, the clock never stops. Rather than being split into stages, once started, the race does not stop until the cyclist crosses the finish line.
Solution
In collaboration with IBM, Axmor specialists designed a web application for ultracyclist Dave Haase, which visualizes data collected from various sensors, upcoming weather conditions and location. The athlete’s data is consolidated onto his smartphone and then imported into the database.
Data collected from a wide variety of devices can be divided into the following groups:
- Biometrics: heart rate, core temperature, skin temperature, breathing rate
- Performance metrics: power, speed
- Weather conditions: wind speed, direction, air temperature
- Position: terrain, altitude
The end users of this application are Dave’s crew and his fans. Taking into account the requirements of each end-user segment, our team developed two dashboards showing the athlete’s main metrics.
To make it easier for fans to follow cyclist Dave Haase’s progress, the web application was integrated with popular social networks like Twitter and Facebook.
To track Dave Haase’s place in relation to his opponents, our team integrated the application with Track Leaders tracking system. This enabled fans to follow the participating athletes’ position, route and status - active, finished, or DNF (did not finish).
When crossing the area from the west to the east coast, the athletes can find themselves in extreme conditions, encountering torrential rain, high-speed winds, and sweltering heat. In order to forecast weather conditions and work with them effectively in real-time, the web application was integrated with the Weather Underground service.
