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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 14 | Issue 2 | Month- February 2026
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Published Paper Details:
Paper Title
A HYBRID APPROACH TO REAL-TIME FATIGUE MONITORING IN DRIVERS
Authors
Sampadarao Nirosha, Dr. S. Sridhar, Maradana Siva
Keywords
ConvLSTM, EEG, KNN
Abstract
Driven by exhaustion is one of the leading causes of road accidents across the world which result in many reported deaths each year. This project attempts to mitigate the challenge using machine learning and deep learning techniques for easier and precise detection of fatigue. EEG signals and video images from the DROZY dataset are utilized to train ML and DL models, respectively. SVM, Random Forest, and KNN are some of the machine learning algorithms utilized for the analysis of EEG signals while the images are analyzed through CNN, ConvLSTM, and also a multi-model approach CNN+ConvLSTM. Further accuracy is enhanced by employing ensemble techniques such as Bagging Classifier. PV and PCA methods were applied to obtain superior model performance resulting in all 100% accuracy for all CNN-based approaches. Thus, this system provides strong approaches toward supporting real time driver fatigue assessment.
IJCRT's Publication Details
Unique Identification Number - IJCRTAS02012
Paper ID - 274206
Page Number(s) - 97-109
Pubished in - Volume 12 | Issue 12 | December 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Sampadarao Nirosha, Dr. S. Sridhar, Maradana Siva, "A HYBRID APPROACH TO REAL-TIME FATIGUE MONITORING IN DRIVERS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 12, pp.97-109, December 2024, Available at :http://www.ijcrt.org/papers/IJCRTAS02012.pdf
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Volume 14 | Issue 2
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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