Abstract
Automobile collisions are consistently ranked among the leading causes of mortality worldwide. Accidents involving bicycles have been dramatically increasing in a wide variety of countries throughout the globe. As a result, the development of a system that can identify and mitigate some of the common errors or slip-ups that a biker makes is of the utmost importance. The development of technology in the sector of transportation has helped to reduce the number of accidents that occur by identifying factors that are essential to a safe voyage, such as the presence of a diving licence, the detection of the helmet, and tiredness. There are methods based on machine learning that may assist in the determination of necessary criteria for safety drives.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
