Accident Detection and Real Time Alert System using CNN

Abstract - Road accidents remain a leading cause of fatalities worldwide, primarily due to delayed emergency response and lack of real-time monitoring systems. This paper presents a deep learning-based Accident Detection and Alert System utilizing Convolutional Neural Networks (CNNs) to identify accidents from video streams in real time. The proposed system processes video frames captured from cameras and classifies them into accident and non-accident scenarios. Upon detection, an alert mechanism is triggered to notify emergency contacts. The system is implemented using Python with libraries such as TensorFlow, OpenCV, NumPy, and Keras. Experimental results demonstrate that the model achieves high accuracy in detecting accident scenarios, making it a reliable and cost-effective solution for enhancing road safety.

Key Words: Accident Detection, Convolutional Neural Network, Deep Learning, Computer Vision, Real-Time Monitoring, Alert System