The use of ML models in motorbikes will bring in a huge change

Motorbikes have come on leaps and bounds in the last five years. At this point, Motorcycle AI is a high contender for the next big innovation for futuristic motorcycles.  Self-learning technology is already a huge part of our lives. Industries such as healthcare and e-commerce greatly benefit from this technology – and the motorcycle industry is no exception. Thanks to machine learning, electric motorcycles can now learn and adapt to each individual rider to improve the riding experience with every journey. That being said, the most influential way in which self-learning technology has revolutionized riding is perhaps through motorcycle safety. While motorcycling is classed as a more dangerous form of transportation compared to the rest, it's the most common worldwide. So, a logical application where technology can help is augmenting rider awareness, resulting in safer motorcycle riders. Damon is one of the motorcycle manufacturers that are starting to focus more on motorcycle safety. This is evident in its in-house industry-disrupting software. From the 100% electric powertrain, HyperDrive™, to the award-winning CoPilot™, Advanced Warning System for Motorcycles (AWSM), its technology helps to reach the goal of no fatal accidents on any of the HyperSport Motorcycles by 2030.

Gigi Dall'Igna, Ducati course General Manager, who has got two World Superbike titles, among others, was given the challenging task of steering the Ducati racing ship back on course, after its factory racing efforts in both MotoGP and World Superbike began to founder, as stated by sportrider.com.  As such, he turned to big data besides turning to Lorenzo (not much of a turning for that matter) and implemented the first IoT and AI technologies into the Ducati's bikes for the MotoGP competition.

The purpose of the project is to help the Ducati team simply make better decisions when it comes to the bike configurations. Each year, the MotoGP bikes need to be configured for 18 tracks, and each time there are endless possibilities. That is where the machine learning algorithms come in, and according to Ducati's statements, it has made a difference in making the right decision when it comes to bike setup.

To go big on big data, Ducati implemented an AI and IoT project, so they can simulate the behavior and performance of the bike under various conditions. The sensors on the bike, ranging from 40 to 100, collect data such as speed, engine running parameters, revs, tire and brake temperatures, acceleration, oscillation, vibration, and grip. Once the data is collected, AI is applied to figure out the right configuration. According to their statements, around 4,000 sectors of race tracks and 20 different racing scenarios have been analyzed, with a wider roll-out of the solution expected. Moreover, the machine learning techniques can also predict the performance and behavior of the bike after a setting change. More details on silicon.co.uk.

When it comes to bikes, Ducati is not the only manufacturer turning to big data for insights. Yamaha also goes big on AI and ML and created an updated version of its self-driving motorcycle that after 3 years of learning, went on a circuit and competed with Valentino Rossi's time. Equipped with a humanoid robot, MOTOBOT managed to do a complete lap of the circuit, but without being even close to Rossi's time. We're still impressed. And a bit freaked out: Yamaha boldly predicts the bot will outperform Rossi within two years, and that freaks us out even more. However, the purpose of the project is not to build a bike that could compete in MotoGP, but to improve the existing street bikes, making them safer for riders.