An Efficient Embedded Security System for Reduce Car Accident to Build Safer World Based on IoT - Othman, Nashwan Adnan; Aydin, Ilhan; Karakose, Mehmet (Institute of Electrical and Electronics Engineers Inc., 2019)
Nowadays, people need to work hard to afford their life and this results in people to live under the stress of the modern life style. This pressure of the modern life style might cause problems and accidents, for example, when a driver feels drowsy while driving his car, there is a great possibility of making an accident. For the sake of solving or reducing the amount of such accidents, we designed an embedded system. This system presents an enhanced technique for detecting drowsiness in real-Time and reducing car accident. In this paper, we proposed an eye blinking technique for real-Time video by using machine learning and computer vision techniques. When a driver often feels drowsy, instead of stopping the car for a while to rest and gain back his/her conscious, he/she continues driving, so we utilize Internet of Things (IoT), which is a system connected to internet. When a driver feels sleepy, directly an alert message will be sent to one of his nearest kin or friends. Then the alerted person can call the driver and oblige him/her to stop the car. Meanwhile, there is a speaker inside the car to warn the driver. To implement this system, a jetson TX2 embedded platform is used and it uses its own camera board for taking frames. © 2019 IEEE.
2019 International Conference on Artificial Intelligence and Data Processing Symposium, IDAP 2019 -- 21 September 2019 through 22 September 2019 -- Malatya -- 153040
Keywords: computer vision; drowsiness; embedded platform; Embedded system; Internet of Things; jetson TX2; machine learning; smart system