In this article, Keisha Michael explores Shimano’s innovative patents for automatic seat adjustments and AI-powered pedalling assistance to advanced fitness tracking, and how AI is transforming how we ride.
Artificial Intelligence is everywhere. Farmers are now using AI to help them manage their crops, long dead artists are having their voices resurrected and used to create new songs, and Apple have recently announced that it will be adding AI to its handset’s Operating System. Most industries are embracing the use of AI, but how could Artificial Intelligence impact the cycling industry?
Shimano appear to be leading the way when it comes to filing patents related to Artificial Intelligence in the cycling space.
Riding a bike that has been professionally set up can prevent injury and provide the marginal gains to make you faster. But getting a bike fit is expensive and the right set-up can take time to perfect. US patent, US20200014321, describes a seat post which is automatically adjusted using an artificial intelligence processor that collects data about the rider. The processor can consider the speed of travel, biological information about the rider and/or information about the route to configure the seat post accordingly. It is also able to adjust the suspension by considering the same information.
Similarly, Shimano’s patent US11912371 uses an artificial intelligence processor to provide an assistive force to help propel the bike using information about the riders driving force.
[Figure 1, US20200014321]
Another Shimano patent, US11526699, uses machine learning to detect a degree of wear for a portion of a bicycle, particularly the brakes. The degree of wear is then reported back to the user, who is also provided with additional information such as a method for removing or adjusting the worn portion.
There is a constant demand for more data in sports. We now use watches and computers to track so much more than how far we’ve travelled and how fast.
In US patent, US2014030952, a fitness tracker is described which uses machine learning to improve fitness tracking. A machine learning algorithm is described which tracks a user’s sleep by using collected data to determine whether they are awake or asleep. A second algorithm can predict cardiovascular intensities experienced by the user based on their heart rate and other personal data, which can then be used by the user to improve their training.
[Figure 2, US2014030952]
Artificial Intelligence has the potential to transform the future of cycling. As AI is embraced by innovators throughout the industry, it is definitely an area to watch as exciting developments are no doubt still to come.
This is for general information only and does not constitute legal advice. Should you require advice on this or any other topic then please contact hlk@hlk-ip.com or your usual HLK advisor.
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