Oraan KhunpisuthTaweechai ChotchinasriVarakorn KoschakosaiNarit HnoohomMahidol University2018-12-212019-03-142018-12-212019-03-142017-04-21Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016. (2017), 661-6682-s2.0-85019252594https://repository.li.mahidol.ac.th/handle/20.500.14594/42373© 2016 IEEE. The purpose of this paper was to devise a way to alert drowsy drivers in the act of driving. One of the causes of car accidents comes from drowsiness of the driver. Therefore, this study attempted to address the issue by creating an experiment in order to calculate the level of drowsiness. A requirement for this paper was the utilisation of a Raspberry Pi Camera and Raspberry Pi 3 module, which were able to calculate the level of drowsiness in drivers. The frequency of head tilting and blinking of the eyes was used to determine whether or not a driver felt drowsy. With an evaluation on ten volunteers, the accuracy of face and eye detection was up to 99.59 percent.Mahidol UniversityComputer ScienceConference PaperSCOPUS10.1109/SITIS.2016.110