Anh-Ngoc Le
Electric Power University

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Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT Thi Thu Nguyen; Phuc Thinh Doan; Anh-Ngoc Le; Kolla Bhanu Prakash; Subrata Chowdhury; Duc-Nghia Tran; Duc-Tan Tran
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp785-792

Abstract

In this paper, we introduce a mobile application called CarSafe, in which data from the acceleration sensor integrated on smartphones is exploited to come up with an efficient classification algorithm. Two statuses, "Driving" or "Not driving," are monitored in the real-time manner. It enables automatic actions to help the driver safer. Also, from these data, our software can detect the crash situation. The software will then automatically send messages with the user's location to their emergency departments for timely assistance. The application will also issue the same alert if it detects a driver of a vehicle driving too long. The algorithm's quality is assessed through an average accuracy of 96.5%, which is better than the previous work (i.e., 93%).