… , leaving in particular, machine learning (ML) … accident detection based on mutimodal in-car
sensors. Our work is a unique and innovative study on detecting real-world driving accidents …

… This paper presented an accident detection and classification system based on the IoT that
… response to accidents by contacting the necessary entities. The accident information is also …

… The domain used in our system is Machine Learning technology where we used three
algorithms … detection. We consider accidents in normal road traffic flow as abnormal. When road …

… This study has shown that accidents can be detected using machine learning methods.
Probe vehicles can use proposed system during their travel and check constantly if any …

… performance of two popular machine learning models, Support Vector Machine (SVM) and
… is the use of machine learning on different TTDs to detect the occurrence of accidents. Since …

… a drilling accident detection, it is necessary to use a supervised machine learning approach…
The algorithm should take into account the particular mud logs pattern for different accident …

… The rest of our research article is written as follows: Section 2 discusses the related work
on smart city transportation systems, accident detection, and machine learning methods. …

… and six accidents happen every hour on average. This paper proposes an efficient
automatic accident detection system that attempts to detect the occurrences of the accidents in …

… ad hoc networks, various machine learning algorithms, and mobile apps. Every vehicle
should have an automatic road accident detection and information communication system …

… accidents (from Countrywide Traffic Accident dataset). Furthermore, we evaluate multiple
machine learning … error (RMSE) of traffic accident duration prediction while providing higher …