Technologies for detecting and monitoring drivers' states: A systematic review
Driver fatigue or drowsiness detection techniques can significantly enhance road safety measures and reduce traffic accidents. These approaches used different sensor technologies to acquire the human physiological and behavioral characteristics to investigate the driver's vigilance state. Altho...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-10-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S240584402415623X |
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| _version_ | 1846170102308798464 |
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| author | Maged S. AL-Quraishi Syed Saad Azhar Ali Muhammad AL-Qurishi Tong Boon Tang Sami Elferik |
| author_facet | Maged S. AL-Quraishi Syed Saad Azhar Ali Muhammad AL-Qurishi Tong Boon Tang Sami Elferik |
| author_sort | Maged S. AL-Quraishi |
| collection | DOAJ |
| description | Driver fatigue or drowsiness detection techniques can significantly enhance road safety measures and reduce traffic accidents. These approaches used different sensor technologies to acquire the human physiological and behavioral characteristics to investigate the driver's vigilance state. Although the driver's vigilance detection technique has attracted significant interest recently, few studies have been conducted to review it systematically. These studies provide a thorough overview of the most advanced driver vigilance detection method available today in terms of sensor technology for scholars and specialists. This research is geared towards achieving three main objectives. Firstly, it aims to systematically gather, evaluate, and synthesize information from previous research published between 2014 and May 2024 on driver's state and driving sensors and their implementation on detection algorithms. It aims to provide a thorough review of the present state of research on wearable and unwearable sensor technology for driver fatigue detection, focusing on reporting experimental results in this field. This information will be necessary for experts and scientists seeking to advance their knowledge in this field. Lastly, the research aims to identify gaps in knowledge that require further investigation and recommend future research directions to help address these gaps. This way, it will contribute to the advancement of the field and provide beneficial insights for future researchers. |
| format | Article |
| id | doaj-art-9b72adb6f5884c3d855591ddc2968a11 |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-9b72adb6f5884c3d855591ddc2968a112024-11-12T05:21:01ZengElsevierHeliyon2405-84402024-10-011020e39592Technologies for detecting and monitoring drivers' states: A systematic reviewMaged S. AL-Quraishi0Syed Saad Azhar Ali1Muhammad AL-Qurishi2Tong Boon Tang3Sami Elferik4Interdisciplinary Research Center for Smart Mobility and Logistics (IRC-SML), King Fahd University of Petroleum Minerals (KFUPM), Dhahran, 31261, Saudi ArabiaInterdisciplinary Research Center for Smart Mobility and Logistics (IRC-SML), King Fahd University of Petroleum Minerals (KFUPM), Dhahran, 31261, Saudi Arabia; Department of Aerospace Engineering, King Fahd University of Petroleum Minerals (KFUPM), Dhahran, 31261, Saudi Arabia; Interdisciplinary Research Center for Aviation and Space Exploration, King Fahd University of Petroleum Minerals (KFUPM), Dhahran, 31261, Saudi Arabia; Corresponding author. Interdisciplinary Research Center for Smart Mobility and Logistics (IRC-SML), King Fahd University of Petroleum Minerals (KFUPM), Dhahran, 31261, Saudi Arabia.Research Center, Elm Company, Riyadh, 12382, Saudi ArabiaElectrical and Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, 32610, Perak, MalaysiaInterdisciplinary Research Center for Smart Mobility and Logistics (IRC-SML), King Fahd University of Petroleum Minerals (KFUPM), Dhahran, 31261, Saudi ArabiaDriver fatigue or drowsiness detection techniques can significantly enhance road safety measures and reduce traffic accidents. These approaches used different sensor technologies to acquire the human physiological and behavioral characteristics to investigate the driver's vigilance state. Although the driver's vigilance detection technique has attracted significant interest recently, few studies have been conducted to review it systematically. These studies provide a thorough overview of the most advanced driver vigilance detection method available today in terms of sensor technology for scholars and specialists. This research is geared towards achieving three main objectives. Firstly, it aims to systematically gather, evaluate, and synthesize information from previous research published between 2014 and May 2024 on driver's state and driving sensors and their implementation on detection algorithms. It aims to provide a thorough review of the present state of research on wearable and unwearable sensor technology for driver fatigue detection, focusing on reporting experimental results in this field. This information will be necessary for experts and scientists seeking to advance their knowledge in this field. Lastly, the research aims to identify gaps in knowledge that require further investigation and recommend future research directions to help address these gaps. This way, it will contribute to the advancement of the field and provide beneficial insights for future researchers.http://www.sciencedirect.com/science/article/pii/S240584402415623XDriver fatigueDriver's stateDetectionWearable sensorsUnwearable sensorsDeep neural network |
| spellingShingle | Maged S. AL-Quraishi Syed Saad Azhar Ali Muhammad AL-Qurishi Tong Boon Tang Sami Elferik Technologies for detecting and monitoring drivers' states: A systematic review Heliyon Driver fatigue Driver's state Detection Wearable sensors Unwearable sensors Deep neural network |
| title | Technologies for detecting and monitoring drivers' states: A systematic review |
| title_full | Technologies for detecting and monitoring drivers' states: A systematic review |
| title_fullStr | Technologies for detecting and monitoring drivers' states: A systematic review |
| title_full_unstemmed | Technologies for detecting and monitoring drivers' states: A systematic review |
| title_short | Technologies for detecting and monitoring drivers' states: A systematic review |
| title_sort | technologies for detecting and monitoring drivers states a systematic review |
| topic | Driver fatigue Driver's state Detection Wearable sensors Unwearable sensors Deep neural network |
| url | http://www.sciencedirect.com/science/article/pii/S240584402415623X |
| work_keys_str_mv | AT magedsalquraishi technologiesfordetectingandmonitoringdriversstatesasystematicreview AT syedsaadazharali technologiesfordetectingandmonitoringdriversstatesasystematicreview AT muhammadalqurishi technologiesfordetectingandmonitoringdriversstatesasystematicreview AT tongboontang technologiesfordetectingandmonitoringdriversstatesasystematicreview AT samielferik technologiesfordetectingandmonitoringdriversstatesasystematicreview |