Why False Detections Happen

Phones experience bumps, vibrations, and accidental touches. These can sometimes appear similar to intentional phone use. LETSTOP uses AI to interpret patterns so the system becomes better at recognizing genuine distraction while filtering out noise.

Understanding Intent vs Noise

The core challenge is distinguishing deliberate phone interactions from accidental signals.

AI evaluates these signals in context to avoid penalizing you unfairly.

How AI Filters Out Accidental Touches

Machine learning models compare signals against patterns from thousands of anonymized trips.

This helps prevent accidental bumps from harming your score.

Detecting Context Through Motion and GPS

Context matters. AI does not look at touches alone. It examines the moment in relation to the rest of the trip.

Contextual signals help the system avoid misclassifying real world errors.

Learning Over Time Without Tracking Identity

Model improvements come from anonymized data. The AI learns patterns, not people. It never links specific behaviors to your name, contacts, or personal files.

Better Accuracy for Everyone

Each update makes scoring more fair and more consistent. The result is fewer false detections, fewer surprises in your summaries, and a scoring system you can trust regardless of where or how you drive.