Current Status and Future Research Directions in Monitoring Vigilance of Individual or Mass Audience in Monotonous Working Environment

B. F. Momin1 and Parag P. Abhyankar2,1WCE,India and 2Finolex Academy, India

ABSTRACT

Working in monotonous environment often causes lack of concentration or fatigue in an operator and many times such non-vigilance leads to accidents. Therefore early detection of fatigued state has become essential in monotonous working environments like driving vehicle, operating machines etc. Such fatigued state often gets developed gradually and can be identified by certain symptoms. Different types of symptoms help in modelling non-vigilance in different ways. This paper reviews and compares current status of research in modelling fatigue where fatigue is modelled using probabilistic models, machine learning models, finite state machine etc. The paper also presents possible future research directions in the same field like identifying non-fatigue non-vigilance mental states, extending non-vigilance monitoring for mass audience etc. 

KEYWORDS

Vigilance Monitoring, Fatigue Modelling, Physiological, Behavioural and Visual Measure, Machine Learning. 

Original Source URL: https://airccse.org/journal/ijsc/papers/3211ijsc04.pdf

https://airccse.org/journal/ijsc/current2012.html

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 #vigilancemonitoring #fatiguemodelling #physiological #visualmeasure #machinelearning

CURRENT STATUS AND FUTURE RESEARCH DIRECTIONS IN MONITORING VIGILANCE OF INDIVIDUAL OR MASS AUDIENCE IN MONOTONOUS WORKING ENVIRONMENT

CURRENT STATUS AND FUTURE RESEARCH DIRECTIONS IN MONITORING VIGILANCE OF INDIVIDUAL OR MASS AUDIENCE IN MONOTONOUS WORKING ENVIRONMENT 

B. F. Momin1 and Parag P. Abhyankar2 1Department of Computer Engg., WCE, Sangli, India bfmomin@yahoo.com 2Department of Information Technology, Finolex Academy, Ratnagiri, India paragabhyankar15@gmail.com 

ABSTRACT 

Working in monotonous environment often causes lack of concentration or fatigue in an operator and many times such non-vigilance leads to accidents. Therefore early detection of fatigued state has become essential in monotonous working environments like driving vehicle, operating machines etc. Such fatigued state often gets developed gradually and can be identified by certain symptoms. Different types of symptoms help in modelling non-vigilance in different ways. This paper reviews and compares current status of research in modelling fatigue where fatigue is modelled using probabilistic models, machine learning models, finite state machine etc. The paper also presents possible future research directions in the same field like identifying non-fatigue non-vigilance mental states, extending non-vigilance monitoring for mass audience etc. 

KEYWORDS 

Vigilance Monitoring, Fatigue Modelling, Physiological, Behavioural and Visual Measure, Machine Learning.  

ORIGINAL SOURCE URL : http://airccse.org/journal/ijsc/papers/3211ijsc04.pdf

http://airccse.org/journal/ijsc/current2012.html