Artificial
Published an edge-ai driver drowsiness detection system with Arduino Uno Q for our high school research
The complete architecture and documentation for EyeDriveSafe are now publicly available. Developed as concluding STEM research, the project addresses road safety by deploying a MobileNetV2 transfer learning model on an Arduino Uno Q for real-time edge AI facial analysis. The system utilizes whole-frame binary classification to compute continuous drowsiness metrics and translates visual cues into an escalating three-tier alert state machine. The formal research paper is...
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