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Built an AI system last year for my college project that watches your face and yells at you before you fall asleep at the wheel

A college student built FocusFleet, a drowsy driver detection system that uses MediaPipe to track 468 facial landmarks and a custom-trained Keras model to monitor eye closure and yawning, triggering an audio alert when it detects a driver falling asleep. The system includes a state machine with active, warning, drowsy, and face-lost states to avoid false alarms. The developer shared the project online after improving it since its creation last year.

read1 min views1 publishedAug 3, 2026

So last year for my final year project I built FocusFleet — a drowsy driver detection thing that actually works pretty well, and I’ve kept improving it since.

Basically it watches your face through the camera (468 landmarks via MediaPipe), tracks how much your eyes are closing and whether you’re yawning, and runs that alongside a Keras model I trained myself for a second opinion. If it thinks you’re actually falling asleep (not just blinking), it sets off an audio alert loud enough to snap you back.

There’s a whole state machine behind it too — active, warning, drowsy, face lost — so it’s not just spamming alerts on every blink, it actually waits for a real pattern before reacting.

You can run it two ways:

Honestly proudest of this one out of everything I built in college, so figured I’d finally share it here instead of letting it die in a folder. Would love to know what you think, if the detection feels accurate, or if it triggers false positives for anyone.

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