Low-Cost Adaptive Led Matrix Headlight System Using Arduino and Computer Vision

Article Citation : Manisha Mhetre , Sanchit Shelke , Bhushan Shinde , Amey Sutar , Om Tambe , (2026) "Low-Cost Adaptive Led Matrix Headlight System Using Arduino and Computer Vision", International Journal of Industrial Electronics and Electrical Engineering (IJIEEE) , pp. 27-33, Volume-14,Issue-5

Abstract : Driving at night is particularly hazardous due to reduced visibility and glare from conventional high-beam head- lights. While existing adaptive lighting systems reduce these hazards, they remain confined to premium vehicles because current implementations rely on expensive sensors and actuators along with proprietary architectures. This paper proposes a low-cost, open-source adaptive LED matrix headlight system that controls light intensity and direction dynamically using computer-vision-based vehicle detection. The proposed design uses an Arduino UNO microcontroller along with a WS2812 LED matrix to simulate the headlight beams while processing live video input from a USB webcam with Python, utilizing the TensorFlow Object Detection API to detect oncoming vehicles. Real-time serial communication between the computer and the microcontroller enables the individual LEDs corresponding to the position of the detected vehicle to be selectively dimmed or turned off, thereby reducing glare while maintaining optimum illumination for the driver. Experimental validation of the prototype shows that real-time adaptive beam adjustment is possible with affordable compo- nents, while the functionality will be comparable with state- of-the-art commercial adaptive headlight systems at a fraction of the cost. The implementation successfully bridges embedded control, computer vision, and automotive lighting technology to create a feasible proof of concept for intelligent vehicle lighting. Future work includes upgrading to advanced object detection models, such as YOLOv8 or EfficientDet, integration of multi- sensor fusion using LiDAR or radar to handle adverse weather conditions, and the use of automotive-grade hardware for real- world deployment. Keywords - Adaptive Headlights, LED Matrix, Arduino, Computer Vision, Tensorflow, Automotive Electronics, Intelligent Vehicle Systems

Type : Research paper

Published : Volume-14,Issue-5