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Smart city article details
| Title | Smart Prediction Of Severity In Vehicular Crashes: A Machine Learning Approach |
|---|---|
| ID_Doc | 51336 |
| Authors | Koley S.; Mondal S.; Ghosal P. |
| Year | 2022 |
| Published | Proceedings - International Conference on Computational Intelligence and Networks, 2022-December |
| DOI | http://dx.doi.org/10.1109/CINE56307.2022.10037474 |
| Abstract | The number of vehicles on the road is increasing steadily every day, and even with substantial technological breakthroughs in vehicle safety systems, the number of injuries and fatalities related to traffic accidents is still very high. It has been noted that victims have frequently passed away as a result of wasting valuable time looking for appropriate hospitals. It goes without saying that locating a suitable hospital for collision victims will be quicker and easier if the severity of their injuries can be assessed right away. In this article, a machine learning-based model has been proposed that can measure the severity of a vehicular crash immediately after an accident. Real road accident data has been used in the proposed model to train the system using various machine learning models and other relevant information related to a crash have been collected from the OBD system of vehicles. The proposed system provides a crash severity report according to three predefined categories i.e. Slight, Serious and Fatal which may be very much useful for choosing appropriate hospitals without wasting precious time. © 2022 IEEE. |
| Author Keywords | Machine Learning; Road Accidents; Severity Prediction; Smart City |
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