(Image source: Bone)
AI Smart Safety Systems: How Bicycles Can See Danger
In urban riding environments, the greatest risks for cyclists often come from information gaps:
approaching vehicles from behind, blind-spot hazards, or sudden situations at intersections that riders may not detect in time.
As a result, bicycles equipped with AI-powered computer vision and sensor systems have begun to emerge in recent years, such as:
• AI rear-view cameras or radar systems that proactively detect approaching vehicles
• Smart bike lights that identify pedestrians or potential hazards and issue warnings
The key value of these systems lies not only in sensing, but in AI’s ability to determine which situations truly require alerts — making warnings more accurate without disrupting the ride.
(Image source: apeman official website)
AI Ride Behavior Analysis: From Data to Actionable Advice
Cyclists have long been accustomed to using bike computers or apps to record speed, heart rate, and cadence,
but with the addition of AI, this data is now truly being “understood.”
Through machine learning, systems can analyze:
• Whether riding intensity matches the rider’s current condition
• Signs of fatigue or overtraining risk
• Riding habits that affect efficiency and stability
This allows everyday riders to receive training insights close to a professional level,
evolving from simple data logging into personalized riding assistance.
(Image source: HOVERAir official website)
AI Posture Analysis and Bike Fitting
Bike fitting has traditionally been a high-barrier professional service,
but AI and computer vision are now changing that.
Through video analysis, AI can identify joint angles and motion trajectories,
evaluate saddle height, handlebar reach, and riding stability, and provide adjustment suggestions.
These technologies are not only about increasing speed,
but more importantly about reducing injury risk and enabling riders to ride longer and more comfortably.
(Image source: MyVeloFit official website)
AI e-Bikes: Assistance That Understands the Rider
In the e-bike segment, AI plays an even more defined role.
Next-generation e-bike systems learn riders’ habits and road conditions,
adjusting power output, shifting response, and energy distribution in real time.
Assistance is no longer about switching between fixed modes,
but dynamically adapting based on slope, cadence, and usage conditions,
creating a more natural and effortless riding experience.
Take SMALO LX2 as an example. Its proprietary Smart Mode™
automatically calculates optimal electric assistance and gear settings based on pedaling behavior, helping riders move forward efficiently.
At the same time, SMALO’s AI system can simulate professional riders’ shifting patterns,
automatically adjusting mechanical gears to the appropriate chainring for smooth, uninterrupted riding.
(Image source: SMALO official website)
From Individuals to Cities: AI in Smart Transportation
When individual riding data is aggregated at a city level,
AI can help identify high-risk road segments and high-density cycling routes,
providing actionable insights for urban planners.
These insights can be used to improve bike lane design, enhance road safety,
and even support traffic engineering decisions with real-world evidence.
Studies have shown that AI-supported traffic planning can optimize urban road networks and cycling flow,
reduce accident risks, and improve overall transportation efficiency.
This means bicycles are no longer just personal fitness or commuting tools,
but are gradually becoming part of the smart city framework —
serving as “data nodes that can be understood and optimized”,
connecting individual mobility behavior with urban transportation strategies.
(Image source: Bone)
Smart Riding Starts with Stable Access to Information
AI makes bicycles smarter, but the foundation is surprisingly simple —
riders must be able to receive information safely and steadily while riding.
Whether it’s navigation, ride data, training insights, or safety alerts,
smartphones remain the primary gateway for most riders to access AI-powered cycling services.
That’s why products like Bike Tie 6
play a crucial role in the smart cycling ecosystem.
Designed to fit various handlebar types and stay firmly in place without shaking,
it ensures reliable smartphone use across different bikes and riding scenarios.
When the phone is mounted more securely,
the intelligent riding experience powered by AI can truly take root
and become part of everyday cycling.
(Image source: Bone official website)