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Real Time Drowsiness Detection of an Operator


Affiliations
1 Department of Electronics and Telecommunications, University of Pune, India
2 Department of Electronics from University of Kolhapur, India
3 Department of Electronics and Telecommunication Engineering, The University of Pune, India
     

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In today’s fast lifestyle Safety of a human being is a major issue. The need to develop system model is because of the security issues of human being and improvement in automobile industry. The research report shows that Drowsiness leads to severe loss of health and wealth. So to reduce these all effects few techniques are created. This includes some standard approach and it will help to send warning signal to operator if he/she falls asleep. In this project the aim is to check drowsiness at real time with new hybrid model concept. The warning signals are developed at the end of detection methodology. The detection process includes capturing of video of operator, pattern recognition in Labview. After that analysis of parametric values comparison of total results are made. Finally according to the value of parameters awareness signal is given to the operator.

Keywords

Biological Signal, Drowsiness Level, Hybrid Approach, Sleepiness Scale.
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  • Real Time Drowsiness Detection of an Operator

Abstract Views: 267  |  PDF Views: 4

Authors

Ajita A. Patil
Department of Electronics and Telecommunications, University of Pune, India
S. D. Lokhande
Department of Electronics from University of Kolhapur, India
H. B. Mali
Department of Electronics and Telecommunication Engineering, The University of Pune, India

Abstract


In today’s fast lifestyle Safety of a human being is a major issue. The need to develop system model is because of the security issues of human being and improvement in automobile industry. The research report shows that Drowsiness leads to severe loss of health and wealth. So to reduce these all effects few techniques are created. This includes some standard approach and it will help to send warning signal to operator if he/she falls asleep. In this project the aim is to check drowsiness at real time with new hybrid model concept. The warning signals are developed at the end of detection methodology. The detection process includes capturing of video of operator, pattern recognition in Labview. After that analysis of parametric values comparison of total results are made. Finally according to the value of parameters awareness signal is given to the operator.

Keywords


Biological Signal, Drowsiness Level, Hybrid Approach, Sleepiness Scale.