Being an avid cyclist that doesn’t have time to ride during daylight hours mid-week, I often end up riding my bike on a stationary trainer in the evening while watching bike race videos on YouTube. Friends, that dog only hunts for so long.

To address this very issue, an enterprising on-line virtual cycling experience vendor named Zwift recently released their new multi-player virtual cycling experience.  Cyclists use smart sensors to communicate effort and performance to Zwift that then places them in a digital riding experience. Each rider has an avatar whose performance relative to other riders is driven by the sensor data. (See Figure 1.) After taking my first Zwift ride, I can see its attraction.  I have fellow riders that motivate me to ride faster.  Being a Masters level bike racer, my competitive instincts immediately kick in and I found myself pedaling harder than usual to get to the front of the pack.

Figure 1. Zwift’s  virtual riding experience

So what does this have to do with Internet of Things? Information about my effort comes from speed, cadence (rpm), power and heart rate sensors on my bike and me. (See Figure 2.) Each Zwift participant uses sensors similar to mine to communicate their riding effort.  Ant+ or BlueTooth are the local wireless communication protocols that connect the sensors to a smart phone, tablet or PC which in turn act as gateways.

Figure 2. Integrating my bike’s smart sensors with Zwift

Today’s ride was on a virtual replica of the 2015 World Road Championship course in Richmond, VA. At times on the course, there were opportunities to sprint for fastest time on a leaderboard. (See Figure 3.) One of the sprints was the climb up Libby Hill. Huff! I am out-of-shape!

Figure 3. Libby Hill  climb leaderboard

At the end of a ride, Zwift then computes various maximum, average and total metrics for time, distance, speed, heart rate and power. (See Figure 4 below.) With this data I can track my performance over time, seeking to maximize performance improvement without overtraining. I can also engage in friendly competition with other riders including those from my club and also other riders from elsewhere in the world. Data can also be uploaded to Strava.com, a cycling performance management app.

Figure 4: Zwift  post-ride analytics

There has been quite a bit of hoopla about smart homes and medical device communications as primary consumer Internet of Things use cases.  It is my opinion that IoT-enabled sports will create killer apps. I wrote recently about Wilson Sporting Goods’ Connected Basketball that enabled collection, analysis and sharing of basketball shot performance data. Zwift is another example of a connected device-enabled sports experience.

There has been quite a bit of hoopla about smart homes and medical device communications as primary consumer Internet of Things use cases.  It is my opinion that IoT-enabled sports will create killer apps. I wrote recently about Wilson Sporting Goods’ Connected Basketball that enabled collection, analysis and sharing of basketball shot performance data. Zwift is another example of a connected device-enabled sports experience.

With this collected data, performance insight that was once was only available to well-funded racing teams is now available to most any rider with the ability to connect to Zwift. Herein is the big insight; Internet of Things applications will democratize access to device data and associated insight that is openly shared.