Smart Passenger
Keywords:
Machine learning, IoT, NLP.Abstract
Smart Passenger is a smart device which is used to keep driver away from his drowsiness and makes his journey peaceful. Smart Passenger keeps interacting with the driver so that he stays awake during his entire journey. Smart passenger has features such as mist spraying of water, alarm system, alcohol detection, etc. Smart passenger interaction with the driver will be completely based upon driver’s interest as well as his hobbies. A camera fixed with this device keeps track over the driver’s movement of eyes and face using ML algorithms. Once the drowsiness is detected, stage of drowsiness will be checked & appropriate action is performed.
References
- Deep Learning for Natural Language Processing & Language Modelling by Mr. Piotr Klosowski SAP 2018, September 19th -21st, 2018, Poznan, POLAND.
- A Survey on State-of-the-Art Drowsiness Detection Techniques by Muhammad Ramzan, Hikmat Ullah Khan, Shahid Mahmood Awan, Amina Ismail, Mahwish Ilyas and Ahsan Mahmood in IEEE Access on 1st May 2019.
- Telematics: Artificial passenger & beyond by Mr. Dimitri Kanevsky at IBM, T. J. Watson Research Center.
- Drunken driving detection and prevention models using Internet of Things by Suparna Sahabiswas and Sourav Saha.
- Artificial intelligence techniques for driving safety by Zahid Halim, Rizwana Kalsoom, Shariq Bashir and Ghulam Abbas at Artif Intell Rev DOI 10.1007/s10462-016-9467-9
- Facial expression recognition using face-regions by Khadija Lekdioui, Yassine Ruichek, Rochdi Messoussi, Youness Chaabi and Raja Touahni in 3rd International Conference on Advanced Technologies for Signal and Image Processing - ATSIP'2017, May 22-24, 2017, Fez, Morroco.
- Research on Speech Recognition Technology and Its Application by Youhao Yu in 2012 International Conference on Computer Science and Electronics Engineering.
- Driver fatigue detection system by Yogesh Chellappa, Narendra Nath Joshi, and Vaishnavi Bharadwaj in 2016 IEEE International Conference on Signal and Image Processing.
- Real-Time Eye Blink Detection using Facial Landmarks by Tereza Soukupova and Jan Cech in 21st Computer Vision Winter Workshop Luka Cehovin, Rok Mandeljc, Vitomir Struc (eds.) Rimske Toplice, Slovenia, February 3–5, 2016.
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