Accident Emergency Alert System using Deep Learning

An accident is an unexpected and unwanted event. One of the primary causes of car accidents is speed. Many lives could be saved if rescue services received accident information and responds to it quickly. Human lives became simpler with the emergence of technology and infrastructure. Given the concerning growth in the number of accidents occurring in India, this method ensures that authorities are notified prior to an accident or at the moment of the event. The advancement of technology has also resulted in an increase in traffic dangers and road accidents which result in huge loss of life and property due to inadequate emergency services. The failure to receive timely care is the leading cause of mortality in traffic accidents accounting for half of all fatalities. Since, after an accident every second counts and immediate action is required to avoid the death of a person, intelligent transportation systems have lately evolved as a powerful means of improving the interpretation of transportation systems and promoting travel safety. One of the most effective technologies is accident detection systems so that the rate of death in road accidents can be decreased by treating the victims as soon as possible. This article is based on computer vision which is an emergency alert system built on python which uses object tracking techniques to detect the occurrence of an accident. An efficient automatic accident detection system featuring automated reporting of the accident site to emergency responders is critical for saving valuable human life. This system intends to identify accidents beforehand and communicate the information to emergency responders in order to give rapid aid to the wounded individual. The research work purpose is to determine the severity of an accident and to warn the rescue crew in time.