Practice my race
Publication Date: 2016-Aug-31
The IP.com Prior Art Database
Runners cannot train for a race by practicing the exact route. Therefore when it comes to the race day a runner has potentially never actually run the route with the exact hills, bends, gradient and surface. This can cause a runner to find the race harder then they previously did in training and hence their race time may be sub-optimal. Products such as treadmills can be programmed to provide a distance and elevation simulation, but they do not provide the realism of actually running outside. Disclosed is a system that analyses the surrounding terrain and provides a best-fit route for a runner given a set of input conditions.
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Practice my race
The disclosed system uses the data provided from the race providers of the length, gradient, elevation and surfaces of the race. Users select segments of the race they
wish to practice and the data will be sent to their mobile to calculate the most similar
route based on their location. This will provide a runner with the optimum route for them to take outside in real time. The main features of the system are:
- Recommending a race simulation based on local geography - Using input parameters with adjustable weightings to recommend such a simulation, including distance, incline, terrain, weather and temperature
- Automatically selecting a section or subsection of a race to practice based on the best fit similarity to current terrain
- Recommending and marking a user's current location on a map if their current environment is a better fit than a previous environment for a particular run
The disclosed system will also look at similar health trends between runs and other peoples data who have run the same segment. This will allow a runner to see
what is causing problems in their run and where they struggle along with a view to
other data to see how other people tackle the same area. This system works by taking the input parameters and plotting a graph based on the best routes available. This is based on the assumptions that a user already has some data of the race they're running, such as length and direction of the route, elevation of the route and terrain of the route.
At a user's location, they will have similar access to a map with elevation and terrain data. The idea plots a running route for the user based on the following example algorithm:
Step 1: Key necessary features are identified from the planned route and the surrounding location. This is done by extracting the steepest gradients (by differentiation), particularly if they are close together, and unusual terrains in the route. Similar gradients and terrains are identified on the surrounding area. If both gradient and terrain are unusual at the same time, areas that meet both as close as possible are identified.
Step 2: Repeat step 1 until a threshold point when there are no more interesting gradients or terrains.
Step 3: Identify the two rarest gradients/terrains to use. If the route requires a distance smaller than that which is possible between these two...