Date of Publication :20th October 2017
Abstract: By knowing psychological ailment of drivers, fatal road accidents can be readily prevented. Due to the drowsiness of car drivers, most road coincidences occur thru driving. This document offers head motion that alerts the topic in the dark state. This system is grounded on subject's psychological state is helpful in warning drivers during the original sleep cycle drowsiness stage by tracking head motions. The subject's physiological sleep state assessment may be resolute using an accelerometer to monitor head motion. If he/she falls asleep, he/she will be wakened by an alarm. Sensors enabled by an Internet of Things are used to communicate all information gathered by sensors over a smart grid network for rapid response team to take action under emergency circumstances. Recently, there have rapidly increasing injuries. Each hour there are about 17 injuries. Bike accidents are one biggest component of all incidents, since there are not as many safety criteria in four-wheelers as in two-wheelers. The explanations may be that it doesn’t have a cask, that it has drowsiness, that it has alcohol drunk, that two cars get nearer without the two passengers, that the traffic signals split, that there is no valid or no driving licenses that the driver is reckless, that the acceleration button requested, and so on.
Reference :
-
- A. Singhal, Sarishma, and R. Tomar, “Intelligent accident management system using IoT and cloud computing,” 2017, doi: 10.1109/NGCT.2016.7877395.
- A. Thakur, R. Malekian, and D. C. Bogatinoska, “Internet of Things Based Solutions for Road Safety and Traffic Management in Intelligent Transportation Systems,” 2017, doi: 10.1007/978-3-319- 67597-8_5.
- E. Nasr, E. Kfoury, and D. Khoury, “An IoT approach to vehicle accident detection, reporting, and navigation,” 2016, doi: 10.1109/IMCET.2016.7777457.
- H. Hamdane, T. Serre, C. Masson, and R. Anderson, “Issues and challenges for pedestrian active safety systems based on real world accidents,” Accid. Anal. Prev., 2015, doi: 10.1016/j.aap.2015.05.014.
- S. Yasmin, N. Eluru, A. R. Pinjari, and R. Tay, “Examining driver injury severity in two vehicle crashes - A copula based approach,” Accid. Anal. Prev., 2014, doi: 10.1016/j.aap.2014.01.018.
- J. S. Jermakian, “Crash avoidance potential of four passenger vehicle technologies,” Accid. Anal. Prev., 2011, doi: 10.1016/j.aap.2010.10.020.