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IoT-based Driver's Doziness Detection

Manish Mokal, Aaman Sayyad, Anushka Patil, Rutuksha Kedari, Charusheela Pandit

Abstract


A couple of lakh injuries have happened because of numerous factors, including terrible usage, avoiding protection, motive force fatigue, and so forth. According to statistics, driver indolence constitutes 40% of injuries. Internet of things (IoT) can assist in decreasing the number of accidents. To resolve this problem, a machine for motive force doziness detection is presented in this article. This device uses a system learning algorithm to usually monitor the driver's eye movements and activates a buzzer if any signs and symptoms of doziness are visible on the driver's face. Here, a small safety digicam with a snap function is applied to examine the driving force's face and check the eyes for symptoms of drowsiness. The sensor for alcohol will hit upon the inebriated driver and sound an alarm to prevent him from operating a car. This development can reduce accidents and improve protection.


Keywords


Safety, Reduce Accidents, IOT, Doziness, Seat Vibration.

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References


Alajlan NN, Ibrahim DM. DDD TinyML: a TinyML-based driver drowsiness detection model using deep learning. Sensors. 2023; 23 (12): 5696.

Gandhi RN, Ambhorkar PR, Datir AA, Kale PR, Pundkar SG. Driver drowsiness detection system using embedded system. Int J Computer Sci Inform Technol Res. 2022; 10 (2): 73–77.

Akshara MC, Harshitha TS, Deepak N, Priyanka B, Sharath HA. IoT-based driver drowsiness detection and smart alerting system. Int J Res Appl Sci Eng Technol. 2022; 10 (VII): 3638–3646.

Anto A, Chackochan S, Blessen L, Jose J. IOT based real-time driver drowsiness detection and alert system. Int Res J Modern Eng Technol Sci. 2021; 3 (5): 1739–1745.

Biswal AK, Singh D, Pattanayak BK, Samanta D, Yang MH. IoT-based smart alert system for drowsy driver detection. Wireless Commun Mobile Comput. 2021; 2021: 1–3.

Jang SW, Ahn B. Implementation of detection system for drowsy driving prevention using image recognition and IoT. Sustainability. 2020; 12 (7): 3037.

Ashwini, Veda M, Smitha S, Krishna D, Talekar PS. IoT-based driver drowsiness and health monitoring system. Int Res J Eng Technol. 2020; 7 (6): 6063–6066.

Mehta S, Dadhich S, Gumber S, Jadhav Bhatt A. Real-time driver drowsiness detection system using eye aspect ratio and eye closure ratio. In: Proceedings of International Conference on Sustainable Computing in Science, Technology and Management (SUSCOM), Amity University Rajasthan, Jaipur, India, February 26, 2019.

Nursyuhad, AS. Alert System for Drowsy Driver by Study the Eyes Closure Using IoT. BSc Project Report. Universiti Malaysia Sarawak; 2019. Available at https://ir.unimas.my/id/eprint/33936/1/

Nursyuhada%20Binti%20Amir%20Shariffuddin%20-%2024%20pgs.pdf

Rambabu K, Shalini J, Anjum SA, Ramani PR. IoT based drowsiness detection system using Labview. Int J Recent Technol Eng. 2019; 7 (6S5): 1909-1913.

Deng W, Wu R. Real-time driver-drowsiness detection system using facial features. IEEE Access. 2019; 7: 118727–118738.

Raghuvaran V, Sai Priya P, Vidhya V. An IoT based reliable driver drowsiness detection system for automobiles. Int J Res Anal Rev. 2018; 5 (3): 246–253.

Yacchirema DC, Sarabia-Jácome D, Palau CE, Esteve M. A smart system for sleep monitoring by integrating IoT with big data analytics. IEEE Access. 2018; 6: 35988–36001.

Galarza EE, Egas FD, Silva FM, Velasco PM, Galarza ED. Real time driver drowsiness detection based on driver’s face image behavior using a system of human computer interaction implemented in a smartphone. In: Rocha Á, Guarda T, editors. Proceedings of the International Conference on Information Technology & Systems (ICITS 2018). Cham, Switzerland: Springer; 2018. pp. 563–572.

Flores MJ, Armingol JM, de la Escalera A. Real-time drowsiness detection system for an intelligent vehicle. In: 2008 IEEE Intelligent Vehicles Symposium, Eindhoven, The Netherlands, June 4–6, 2008. pp. 637–642.


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