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IoT-based Smart Drowsiness Detection and Alert System

Abubakar ., Samra Shaheen, Hareem Hayee, Rimsha Sarwar, Sawera Shehzadi, Amna Tariq, Muhammad Hamza Zulfiqar


Drowsiness detection systems are necessary in the current era, as drowsy driving contributes to about 20% of all traffic accidents. Approximately 50,000 people have accidents due to drowsy driving annually. Because driving when tired is dangerous, new strategies must be devised to mitigate the impact. Our system is a microcontroller-based system for protecting drivers from unsafe driving based on the physiological parameter of eye blinking. The proposed system detects the sleepy state of the driver using an IR sensor and delivers a WhatsApp message to the emergency contacts provided by the driver. The system is portable and can accurately detect whether the driver is dizzy. The physiological parameter-based system can be used to prevent many accidents.


Drowsiness, IOT, microcontroller, accidents, drivers

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Sikander, Gulbadan, and Shahzad Anwar. "Driver fatigue detection systems: A review." IEEE Transactions on Intelligent Transportation Systems 2018; 20 (6): 2339-2352.

Centers for Disease Control and Prevention. “Drowsy Driving: Asleep at the Wheel,” November 21,2022.

ubbarao, A., and K. Sahithya. “Driver drowsiness detection system for vehicle safety.” Int. J. Innov. Technol. Explor. Eng 8 (2019): 815-819.

“Fatigued Driving. National Safety Council,” n.d.

“Crashes & Fatalities Related to Driver Drowsiness/Fatigue.” ROSA P, 1 Nov. 1994, Accessed 26 May 2022.

Brown, Ivan D. “Driver fatigue.” Human factors 36, no. 2 (1994): 298-314.

Ueno, Hiroshi, Masayuki Kaneda, and Masataka Tsukino. "Development of drowsiness detection system." In Proceedings of VNIS'94-1994 Vehicle Navigation and Information Systems Conference. 31 August 1994-02 September 1994; Yokohama, Japan. US: IEEE, 1994. pp. 15-20.

Xing, Tianzhang, Qing Wang, Chase Q. Wu, Wei Xi, and Xiaojiang Chen. "Dwatch: A reliable and low-power drowsiness detection system for drivers based on mobile devices." ACM Transactions on Sensor Networks (TOSN) 16, no. 4 (2020): 1-22.

Biswal, Anil Kumar, Debabrata Singh, Binod Kumar Pattanayak, Debabrata Samanta, and Ming-Hour Yang. "IoT-based smart alert system for drowsy driver detection." Wireless communications and mobile computing 2021 (2021)

Arunasalam, M., N. Yaakob, A. Amir, M. Elshaikh, and N. F. Azahar. "Real-Time Drowsiness Detection System for Driver Monitoring." In IOP Conference Series: Materials Science and Engineering, vol. 767, no. 1, p. 012066. IOP Publishing, 2020

Manideep, Tungali, Isha Upadhyay, Nikhil Aggarwal, P. Govardhan Reddy, and Deepak Das. "IoT Based Eye Blink Detection System." In 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), pp. 491-494. IEEE, 2022.

Ramzan, Muhammad, Hikmat Ullah Khan, Shahid Mahmood Awan, Amina Ismail, Mahwish Ilyas, and Ahsan Mahmood. “A survey on state-of-the-art drowsiness detection techniques.” IEEE Access 7 (2019): 61904-61919

Montag, C., Błaszkiewicz, K., Sariyska, R. et al. Smartphone usage in the 21st century: who is active on WhatsApp?. BMC Res Notes 8, 331 (2015).

“WhatsApp Statistics 2023-Usage, Users,Revenue & More.”, 12 july 2022, Accessed 8 Mar. 2023

Lohnes, Kate. “How Does Wi-Fi Work?” Encyclopædia Britannica, 2019,



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