Our Data Explained

What Makes Our Data Different

Most people know AI can analyse video to detect a cyclist or car. See.Sense does something similar—but with motion data.

Our patented lights and trackers use high-resolution accelerometers, recording movement 800 times per second. Then our onboard AI analyses the data to detect braking and swerving, surface roughness, speed and dwell time, and routing patterns.

Our system profiles each rider’s unique behaviour, so we can identify extreme events—like sudden braking that’s out of the norm. These events often correlate with risk or discomfort.

We then transmit only the most valuable data, using low-power cellular connectivity and efficient on-device processing. This means we get powerful insights, without draining power or bandwidth.

What We Measure

Braking

Sudden deceleration—often linked to risk or conflict on the route.

Swerving

Evasive actions due to narrowing, obstructions, or unexpected hazards.

Surface Condition

Indicates how rough or smooth a route is, affecting ride comfort and safety.

Route Choices

Reflect real-world rider decisions—not just the shortest or fastest path.

Collisions

Track accident hotspots and analyze collision data to improve safety for cyclists.

Survey Reports

Collect feedback from cyclists to gain insights into their experiences.

Independently Validated

Award-winning Collision Risk Detection

Working with RoSPA and TfL, our braking and swerving data was shown to correlate strongly with historic collision locations.

RoSPA recommended See.Sense data be used to identify hazardous areas.

Our collision risk detection work with TfL was recognised with the Prince Michael International Road Safety Award, acknowledging the impact of our data in improving cyclist safety.

🔗 View the RoSPA project →

Road Surface Accuracy

In a project with AECOM and Dublin City Council, engineers visually inspected routes flagged by See.Sense as rough. They found a high correlation with their own surface condition ratings.

Research by University of Hasselt also showed that our road condition data matched how cyclists felt.

🔗 See the Dublin trial case study →

📊 Our insights align with engineering assessments and the rider experience.

🔐 Privacy by Design

We take privacy seriously. All data is anonymised and aggregated by default, and our collection process is built with transparency and user control at its core. We’ve designed our system to ensure that users can contribute with confidence, knowing their information is handled responsibly and is compliant with local data protection legislation.