Last year, Argon 18 showed off a drag detection and body motion analysis system that was completely integrated into a prototype bike. By Taipei Cycle Show this spring, it had shrunk to a bar-mounted design. Now, it’s in its final form factor and ready to show you all the ways you could be better.

The device looks much like the air speed indicators on fighter jets, but it builds in 20 different sensors and metrics to measure everything from speed, wind speed, bike sway, bicycle dynamics, and environment. The result is a device that’ll transmit data on your overall efficiency…and the efficiency of your bike. By correlating speed with wind speed, it knows your drag, giving you a number you can immediately change by modifying your position on the bike, wheels, clothing, helmet, etc.

argon18 notio konect aerodynamics drag detector for bicycles

So, what’s new? First of all, Notio Konect is the new subsidiary brand of Argon18 that’ll develop the tech. They’ve entered into a licensing and development agreement with PowerPod, which has been developing wind speed-based power and drag detection and analysis for years. And the device itself has gotten smaller and completely self contained, relying on external Bluetooth sensors for things like power, cadence and heart rate to help it paint a complete picture.

argon18 notio konect aerodynamics drag detector for bicycles

Only thing not included in this unit is the braking forces, because those required on-bike sensors not currently available from others…and they wanted this to be a self-contained unit.

It’s coming early next year, and retail price is not set, but expect something between $1,000 and $1,500. The device has been in development almost two years, and there are now 10 people working on it full time. Some of that is software, because they want to provide more than data, they want to provide insight, making it easy for more people to understand what all the data means and give them actionable advice.


  1. Francisco on

    “much like the air speed indicators on fighter jets”.

    The ASI is the instrument inside the cockpit, what you mean is the “pressure probe”. The pictures show that this device combines a total pressure probe with a ring of static pressure ports, a pretty standard multiprobe. Total pressure minus static pressure yields dynamic pressure (proportional to air drag) while the variation of static pressure gives an indication of climbing rate, both needed to run the device’s calculation model. I would not rate the accuracy of this device very highly, however. Turbulence and interference drag near the ground will cause large errors. Perhaps the developers have found ways of estimating the errors given enough data crunching.

    • Gillis on

      The “pressure probe” is a Pitot tube. Used on all aircraft and F1 cars (likely other high speed racecars as well). Although this one uses a bevy of sensors to calculate different data.

    • Robin on

      Actually, it’s not a re-branded PowerPod. It’s much better than that. This could be a tool for coaches, teams, and some riders that don’t have access to a wind tunnel. It’s certainly going to be cheaper over time than paying for wind tunnel time.

  2. Dude on

    Looking forward to some velodrome vs windtunnel confirmation testing reports. While spendy, I could see this being rented out by coaches or shops for optimization sessions with triathletes and TTers.

  3. ed on

    How does it measure road drag to subtract it form aero drag. Road surface has a big effect on speed so if this pod doesn’t measure that it is worthless.

    • Jacques on

      As you may know, air drag has three times the effect on momentum that frictional drag does. It might be possible to factor in the frictional force, but you’d need to have some sort of accurate measure of the weight of the bike with the rider and any accessories. If you usually ride with two full bottles and end your rides with two empty bottles, that’s a material change in the weight that will impact frictional drag. Bottom line, you work with the most reliable data, establish a baseline and if the outputs are consistent, you can effect improvements.


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