An Efficient Drowsiness Detection System For Pilot Using Wearable Body Sensor Networks
Keywords:
Negative emotion, Roadway accident, Stress, Wearable system, PPG, ZIGBEE, GSMAbstract
Driver drowsiness detection is a car safety technology which helps prevent accidents caused by the driver getting drowsy. Various studies have suggested that around 20% of all road accidents are fatigue-related, up to 50% on certain roads. Negative emotional responses are a growing problem among drivers, particularly in countries with heavy traffic, and may lead to serious accidents on the road. The focus of this study was to develop and verify an emotional response-monitoring paradigm for drivers, derived from Respiration signals, photoplethysmography signals, and eye blink signal. The relevant sensors were connected to a microcontroller unit equipped with a ZIGBEE-enabled low energy module, which allows the transmission of those sensor readings to a vehicle. When drowsiness is detected in driver then the driving mode is automatically going to automatic mode for driving using image processing and sent information to the transport department officer using GSM.
References
- Yuichi Saito, Makoto Itoh, Toshiyuki Inagaki, "Driver Assistance System With a Dual Control Scheme: Effectiveness of Identifying Driver Drowsiness and Preventing Lane Departure Accidents" IEEE Transactions on Human-Machine Systems March 21, 2016.
- D. Tran, E. Tadesse and W. Sheng, Y. Sun, M. Liu and S. Zhang, "A Driver Assistance Framework Based on Driver Drowsiness Detection" The 6th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems June 19-22, 2016.
- A. Mittal, K. Kumar, S. Dhamija, M. Kaur "Head Movement-Based Driver Drowsiness Detection: A Review of State-of-Art Techniques" 2nd IEEE International Conference on Engineering and Technology(ICETECH) March 17-18, 2016.
- Alesandar, Oge Marques and BorkoFurht "Design and Implementation of a Driver Drowsiness Detection System A Practical Approach".
- Anjali K U, Athiramol K Thampi, AthiraVijayaraman, Franiya Francis M, Jeffy James N, Bindhu K Rajan " Real-Time Nonintrusive Monitoring and Detection of Eye Blinking in View of Accident Prevention Due to Drowsiness" 2016 International Conference on Circuit ,Power and Computing TechnologiesICCPCT].
- J. Ahmed, Jain–Ping Li, S. Ahmed Khan, R. Ahmed Shaikh "Eye Behavior Based Drowsiness Detection System".
- A. Rahman, M. Sirshar, A. Khan "Real Time Drowsiness Detection Using Eye Blink Monitoring" 2015 National Software Engineering Conference(NSEC 2015).
- NilaNovita Sari and Yo-Ping Haung "A Two-Stage Intelligent Model To Extract Features From PPG for Drowsiness Detection" 2016 International Conference on System Science and Engineering (ICSSE) National Chi Nan University July 7-9, 2016.
- Jian-Da Wu, Tuo Rung Chen, ―Development of a drowsiness warning system based on the fuzzy logic images analysis‖, Elsevier, Expert System with Applications, vol.34, pp.1556-1561, 2008
- Vijayalaxmi, D.Elizabeth Rani, ―Eye state Detection Using Image Processing Technique‖,ajer, vol.04, pp.44-48, 2015
- Nidhi Sharma, Prof. V.K. Banga, ―Development of a Drowsiness Warning System based on the fuzzy logic‖, International journal of Computer Applications (0975-8887) vol.8, 2010
- Itenderpal Singh, V.K. Banga, ―DevelopmentOf A Drowsiness Warning System UsingNeural Networks‖, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol.2, pp.36143623, August 2013
- K. Dwivedi, K. Biswaranjan, A. Sethi, ―Drowsy driver detection using representation learning‖, IEEE, International Advance Computing Conference, pp.995-999, Feb-2014
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