  This paper introduces a framework based on computer vision that can detect
road traffic crashes (RCTs) by using the installed surveillance/CCTV camera and
report them to the emergency in real-time with the exact location and time of
occurrence of the accident. The framework is built of five modules. We start
with the detection of vehicles by using YOLO architecture; The second module is
the tracking of vehicles using MOSSE tracker, Then the third module is a new
approach to detect accidents based on collision estimation. Then the fourth
module for each vehicle, we detect if there is a car accident or not based on
the violent flow descriptor (ViF) followed by an SVM classifier for crash
prediction. Finally, in the last stage, if there is a car accident, the system
will send a notification to the emergency by using a GPS module that provides
us with the location, time, and date of the accident to be sent to the
emergency with the help of the GSM module. The main objective is to achieve
higher accuracy with fewer false alarms and to implement a simple system based
on pipelining technique.
