The Smart Cyclo Project

Our company has been running succesfully the Smart Cyclo project.

Smart Cyclo Platform aims to offer a ground-breaking solution that will revolutionise the way cyclists, as well as potentially other athletes, monitor and fine-tune some of the crucial aspects that affect their performance. Posture is one such aspect which is currently exceedingly difficult to monitor in real-life situations and which can make a significant difference when it comes to performance. SmartCyclo has identified a smart solution to this problem by combining state of the art wireless sensors as well as algorithmic intelligence. 

Our target is to combine our developed innovative prototype that is equipped with new technological advances and our own algorithms, with an online platform that will be essential for a highly active and motivated community, the cyclists.

THE PROBLEM:

Competitive cyclists, both professional and hobbyists, are expected to perform at the maximum average speed they can. Thus, they spend a lot of time on training, and they invest significant amount of money on expensive bicycles, on technological advances and other cycling gear, designed to help them either in training or during their race. Several equipment is used to monitor the pedal cadence, speed, heart rate, power output, balance figures and other key numbers that are essential for the cyclists’ training. 

Another major issue for racing cycling is the posture on the bicycle during the ride. An aerodynamic position can be as crucial as an expensive bicycle. Cyclists are spending a lot of time in front of mirrors trying to configure the bicycle to be able to maintain an aerodynamic position during a real ride. Nonetheless, there is no dedicated device or tool in the market that offers the cyclists the ability to see real-time or afterwards, their position during an outdoor ride correlated with the rest cycling data (such as watt, heart rate, speed, inclination etc.) in a simple and effective way.

THE SOLUTION:

Our product is a revolutionary solution for this need, since it is consisted of a small wireless sensor and a mobile app that can track real-time the cyclists’ posture and provide real data on their mobile during the ride. In addition, after finishing their ride, the cyclists can see data and statistics about their posture, how much time they have spent in specific predefined postures combined with the rest captured values. From this data, they can easily extract important conclusions like the position they performed better (speed, power) in a certain situation (e.g., with positive or negative slope).

This project’s plan is to develop an online platform where each cyclist-user can have his own account and can see his saved data, the progress they make, and training feedback based on the user profile and the captured rides’ data from our developed mobile app. Potential users of our platform can also be coaches that can monitor and provide feedback to their athletes that use our product and services. Our platform will be able to connect with other third-party fitness platforms and combine our captured data with third-parties’, providing an in-depth analysis about their performance based on their body posture.

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TODAY
During their training almost all cyclists are using a lot of specialized equipment that help them understand their effort, their performance and their compliance to their training plan. For example, a training program may include a warmup session, some intensity intervals, a specific period of time in a certain effort zone, and a cool down session. In order to identify the training zone they are into, what effort they are putting on, and other cycling data, the cyclists are using a number of tools to monitor them and accordingly adapt their workout.  Also, cyclists go to experts to get a “bike fit” in a specialized indoor studio, making adjustments to several parts of the bicycle so that they will be able to maintain an aerodynamic position more easily and comfortable. Still, during the ride, the cyclists are unable to monitor their cycling position. The optimum for the cyclist is to maintain as much more aerodynamic position as possible during their training or race. Some solutions that are in the market are not satisfactory and insufficient to solve this problem. 

THE FUTURE

Technology can be used to create smart systems for needs that in the past were considered to be difficult to satisfy.  Our solution takes advantage of state-of-the-art sensors and combines them with a smart algorithm on a mobile app creating a completely new application, that offers to cyclists and triathletes new benefits that are missing from their tool case in their daily training. 

WHY CYCLING POSITION MATTERS
Aerodynamic resistance plays a major role in determining how fast we can go on our bikes. So, how much air resistance can we “push” moving forward and how fast, at what speed is the limit where our power will equalise against air resistance. How much, so is a matter of an object’s (i.e., the athlete) drag coefficient (Cd) and its frontal area (A). The effective frontal area is the most important parameter that affects aerodynamic drag. Multiplied together, Cd-A gives a factor of aerodynamics. The higher this figure, the harder we must work to fight air pressure and maintain speed. So, the bigger the object is, the bigger its frontal area and the higher its CdA factor. CdA estimation techniques are now well recognized in cycling, and this parameter can be evaluated in a laboratory or in the field with great reliability. However, although the projected frontal area is easily quantifiable, the variation in the drag coefficient is more complex. Its evolution according to the speed of movement is not fully controlled. 

The fundamental physics governing the motion of a cyclist are well known and have been modelled in the literature. Martin et al. validated a mathematical model for cycling power. [Martin, James C., et al. “Validation of a mathematical model for road cycling power. “Journal of applied biomechanics 14.3 (1998): 276-291]. The importance of position has prompted many wind tunnel investigations into the main positions used by elite cyclists (see figure below):

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Postures in terms of aerodynamic performance

“Overall wind tunnel investigations are largely consistent in the relative ranking of these postures in terms of aerodynamic performance. The time-trial position (d) has the lowest aerodynamic drag followed by the drops position (b&c) and the upright break hoods and stem positions (a) exhibiting the highest aerodynamic drag. Average wind tunnel data suggest that the reduction in drag between an upright sitting position with straight arms (such as the stem and hoods positions) and a drops position can be as much as 15–20% and for the time-trial position as much as 30–35%.” [Crouch, Timothy N., et al. “Riding against the wind: a review of competition cycling aerodynamics.” Sports Engineering 20.2 (2017): 81-110.]

The aerodynamic position is not always the most comfortable position, but it is the one that allows the production of optimal power and pedalling cadence. During a race, comfort must be considered together with optimum aero position, the combination of the two will allow the athlete to have the best performance. The longer the duration of the race is, the more of a factor, comfort becomes. Everything will depend on the joint mobility and flexibility of cyclists. An athlete must be comfortable but also aero, in a position that can maintain in almost all the duration of the race. The recorded percentage of time spent in each different position is an important metric for the cyclists.

With the Smart Cyclo System there is no need to subject yourself in lab test which is, most of the times, expensive and does not replicate real on-the-road conditions, to estimate your CdA, to optimise your performance. The athlete just needs to take use of the application during training, assess many distinct positions and compare them with his power output, cadence, speed, and heart rate.

Learn more by visiting the product’s commercial page: smart-cyclo.com 

The Project is funded by the European Union Recovery and Resilience Facility of the NextGenerationEU instrument, through the Research and Innovation Foundation.