AI-powered smart riding helmet with alcohol detection, drowsiness monitoring, GPS tracking, rider safety alerts, and machine learning-based risk assessment.
IoT-based driver safety system for drowsiness detection, alcohol monitoring, obstacle detection, and automatic speed control.
This project aims to detect heavy drinking risk using smartphone accelerometer time-series data and machine learning. It combines classical ML models (RandomForest, XGBoost, etc.) and deep learning (1D CNN) with an interactive Streamlit dashboard for risk analysis and participant comparison, trained on the UCI Bar Crawl dataset.
An IOT-based bus safety system using ESP32, Flask, MQTT, and sensors to enhance women's safety through smart entry, panic alerts, and alcohol detection.
This is a thesis project in Polytechnic University of the Philippines for alcohol and drowsiness detection system used in PUJ and this contains not optimized system but working
Face recognition attendance system with real-time alcohol/smoke detection via ESP32 + MQ3/MQ2 sensors. Flags intoxication using sensor thresholds, head movement, reaction time, and facial cues. Python, OpenCV, MongoDB.
Detect alcohol levels and control vehicle speed.
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