Car Accident Detection Techniques using Deep Learning

In terms of contributing causes, automobile accidents account for a disproportionate number of fatalities and injuries. A greater proportion of persons die owing to inadequate emergency care than due to traffic accidents. While car accidents are usually a complete surprise, they may be prevented with prompt and reliable emergency care. Mechanical failure, poor road conditions, and slow driver reaction times are all potential causes of accidents. Without prompt medical attention after an injury-causing incident, the victim is quite likely to die. Due mostly to delays in alerting emergency services, ambulance response times may be significantly lengthened. When the victim is incapacitated, they may not be able to make an emergency call. Consequently, there is a want for a reliable and practical method of auto-accident detection that makes use of techniques from the field of image processing. To this end, we use image normalization, Convolutional Neural Networks, and a Decision Tree to identify the occurrence of vehicle accidents. Future iterations of this study will provide more detail on this process.