Advanced driver-assistance system on Raspberry Pi using CNN, Python and OpenCV
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Updated
May 17, 2024 - Python
Advanced driver-assistance system on Raspberry Pi using CNN, Python and OpenCV
Eye state localisation and detection for use in Advanced Driver Assistance System.
Get any car to drive itself with a highly flexible reimplementation of openpilot.
π¦ CivicSense: edge AI perception for intersection discipline, lane courtesy, road hazard alerts, and cooperative safety. Privacy-first, 100% on-device inference, zero video leaves the car.
Real-time, 100% on-device ADAS for Android: forward-collision, drivable-area segmentation, pedestrian, lane and traffic-sign warnings that self-tune from budget phones to flagships.
AutoSeatAdjust is an embedded AI project that uses real-time camera-based eye detection to automatically adjust the driverβs seat. It trains an XGBoost regression model on a dataset of eye coordinates mapped to seat positions, enabling the system to predict seat distance and height adjustments for optimal comfort and safety.
Creating a driver drowsiness detection project using the Haar -Cascade algorithm can be a valuable contribution to the open-source community
Real-time driver drowsiness and distraction detection using MediaPipe face mesh, YOLOv8 for phone detection, and a PyTorch LSTM; Streamlit UI for live webcam monitoring.
AI-Powered Smart Road Visibility & Hazard Detection System for smoggy conditions.
An Advanced AI based Driver Assistance System
STM32-based Smart Parking Assistance System using HC-SR04 ultrasonic sensors, Embedded C, STM32 HAL, LCD, buzzer, LEDs, and modular firmware architecture for real-time obstacle detection and driver guidance.
Real-time lane detection system using OpenCV and Python for autonomous vehicle applications
ADAS inspired driver assistance system using Raspberry Pi, OpenCV, lane departure detection, ultrasonic obstacle sensing, LCD alerts and haptic feedback
ποΈArduino safety system for eKarts/go-karts with obstacle & overheat alerts, FSM ignition, GPS tracking, SMS notifications, and visual/audio warnings.
Water puddle detection on roads using YOLO-based object detection for driver-assistance and autonomous driving applications.
Real-time AI Driver Assistant using Python, OpenCV, YOLOv8, object tracking, distance estimation, voice alerts, and futuristic dashboard UI.
Python-based vehicle detection and lane awareness assistant using YOLO & OpenCV β real-time distance estimation, centroid tracking, and Android deployment via Kivy/Buildozer. Educational prototype.
π Real-time lane detection using Python & OpenCV with image and video processing pipeline visualization.
KI-basierter Intelligent Speed Assist in CARLA mit Verkehrszeichenerkennung, Zustandsmaschine und Fahrerwarnung.
Predictive vehicle stability warning for race cars using IMU, steering, speed telemetry, vehicle dynamics, and ML.
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