Abstract: Road crashes often happen because of visibility fast-moving vehicles and the absence of early alert mechanisms in vital road areas like tight bends and junctions. This project suggests an accident avoidance system utilizing real-time image analysis with a microcontroller development board. A camera module is employed to record live road scenes and track vehicle flow. The gathered information is analysed to identify and categorize vehicle types such, as cars, buses and trucks.The processed data is examined by a microcontroller equipped with edge AI features to enable precise decision-making. Upon detecting a vechicle the system shows the vehicle type, switches on a red traffic light and issues a voice alert to caution drivers and pedestrians, about incoming vehicles. In the absence of a detected vehicle the display and voice alert stay inactive. A green light is turned on to signal a safe situation. This proposed system improves road safety by delivering alerts and visual cues thereby lowering the risk of accidents. Its affordable time functioning and straightforward implementation render it appropriate for use in locations susceptible, to accidents.

Keywords: Image Processing, Vehicle Detection, Embedded System, Microcontroller, Camera Module, Accident Prevention

Downloads: | DOI: 10.17148/IJIREEICE.2026.14211