Rusmin et al., 2013 - Google Patents
Design and implementation of driver drowsiness detection system on digitalized driver systemRusmin et al., 2013
- Document ID
- 1616947086648395354
- Author
- Rusmin P
- Osmond A
- Syaichu-Rohman A
- Publication year
- Publication venue
- 2013 IEEE 3rd International Conference on System Engineering and Technology
External Links
Snippet
In Indonesia, based on data from police, from the 2007-2010 at least 218 253 number of accidents occur. Approximately 65% of accidents occur due to human negligence. At the time of Eid 23 August to 7 September 2011, the number of accidents that occur most often …
- 238000001514 detection method 0 title abstract description 67
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/167—Driving aids for lane monitoring, lane changing, e.g. blind spot detection
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal operating condition and not elsewhere provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/06—Alarms for ensuring the safety of persons indicating a condition of sleep, e.g. anti-dozing alarms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Braunagel et al. | Ready for take-over? A new driver assistance system for an automated classification of driver take-over readiness | |
Doshi et al. | On-road prediction of driver's intent with multimodal sensory cues | |
Li et al. | Modeling of driver behavior in real world scenarios using multiple noninvasive sensors | |
Doshi et al. | A comparative exploration of eye gaze and head motion cues for lane change intent prediction | |
Doshi et al. | On the roles of eye gaze and head dynamics in predicting driver's intent to change lanes | |
Dong et al. | Driver inattention monitoring system for intelligent vehicles: A review | |
Doshi et al. | Examining the impact of driving style on the predictability and responsiveness of the driver: Real-world and simulator analysis | |
Costa et al. | Detecting driver’s fatigue, distraction and activity using a non-intrusive ai-based monitoring system | |
Shirazi et al. | Detection of intoxicated drivers using online system identification of steering behavior | |
Rezaei et al. | Simultaneous analysis of driver behaviour and road condition for driver distraction detection | |
Kasneci et al. | Aggregating physiological and eye tracking signals to predict perception in the absence of ground truth | |
Guria et al. | Iot-enabled driver drowsiness detection using machine learning | |
Rusmin et al. | Design and implementation of driver drowsiness detection system on digitalized driver system | |
Lashkov et al. | Ontology-based approach and implementation of ADAS system for mobile device use while driving | |
CN112168190B (en) | Real-time driving pressure monitoring system and method | |
CN117842085A (en) | Driving state detection and early warning method, driving state detection and early warning system, electronic equipment and storage medium | |
Patil et al. | Drowsy driver detection using OpenCV and Raspberry Pi3 | |
US11780458B1 (en) | Automatic car side-view and rear-view mirrors adjustment and drowsy driver detection system | |
Çetinkaya et al. | Driver impairment detection using decision tree based feature selection and classification | |
CN116798189A (en) | State detection method, device and storage medium | |
Ahmad et al. | Machine learning approaches for detecting driver drowsiness: a critical review | |
Malimath et al. | Driver Drowsiness Detection System | |
Shaykha et al. | FEER: Non-intrusive facial expression and emotional recognition for driver's vigilance monitoring | |
Liang et al. | Driver cognitive distraction detection using eye movements | |
Kalisetti et al. | Analysis of driver drowsiness detection methods |