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Journal articles on the topic 'Optical image processing driver drowsiness sensors'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

ANNAPOORNA, D. PUNEETH KUMAR BAPU, M. DIVYA, PATIL SOUMYA, and KUMAR H. MUTT THEJESH. "IoT-Powered Technologies and Machine Learning based Driver Drowsiness Detection System." International Journal of Innovative Science and Research Technology 8, no. 1 (2023): 1099–109. https://doi.org/10.5281/zenodo.7601786.

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The integrated strategy for detecting driver drowsiness described in this work makes use of the driver's physical, physiological, and optical cues. A machine learning image processing algorithm that contributes to the visual behaviour analysis is used to combine facial and eye analysis to assess the driver's level of exhaustion. As part of the physical behaviour method, the steering grip of the driver is measured using a human antenna effect-based touch sensing technology. Driver heart rate data is collected using a sensor and evaluated to detect tiredness based on the threshold value.

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2

Sarah, Saadoon Jasim, and Karim Abdul Hassan Alia. "Modern drowsiness detection techniques: a review." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (2022): 2986–95. https://doi.org/10.11591/ijece.v12i3.pp2986-2995.

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According to recent statistics, drowsiness, rather than alcohol, is now responsible for one-quarter of all automobile accidents. As a result, many monitoring systems have been created to reduce and prevent such accidents. However, despite the huge amount of state-of-the-art drowsiness detection systems, it is not clear which one is the most appropriate. The following points will be discussed in this paper: Initial consideration should be given to the many sorts of existing supervised detecting techniques that are now in use and grouped into four types of categories (behavioral, physiological,

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3

Kumar, K. Tulasi Krishna, B. Keerthi, C. SP Vishwak Sen, and T. Karthikeya. "Driver Drowsiness Detection System Using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 1–6. http://dx.doi.org/10.22214/ijraset.2023.50031.

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Abstract: Drowsy driving is one of the major causes of road accidents and death. Hence, detection of driver's fatigue and its indication is an active research area. Most of the conventional methods are either vehicle based, or behavioral based or physiological based. Few methods are intrusive and distract the driver, some require expensive sensors and data handling. Therefore, in my literature survey, a low cost, real time driver's drowsiness detection system is developed with acceptable accuracy. The proposed work mainly focus on a webcam records the video and driver's face is detected in eac

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4

Bawankar, Shruti, Abhishek Bhamare, Somesh Bhamre, Harsh Batheja, and Ganesh Korwar. "Driver Safety System." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (2023): 1224–31. http://dx.doi.org/10.22214/ijraset.2023.56198.

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Abstract: Blind spots in vehicles and driver drowsiness are significant safety concerns that contribute to road accidents. To address these issues, we propose a comprehensive driver drowsiness and blind spot detection system using advanced technologies and image processing algorithms. The blind spot detection system employs ultrasonic sensors and an Arduino microcontroller board to gather real-time information about potential collision objects in the blind spot area. When a risk is detected, an LED alarm alerts the driver, enhancing their awareness and reducing the likelihood of accidents. Add

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5

Walke, Ms K. G. "Survey on Driver Drowsiness Detection System." International Journal for Research in Applied Science and Engineering Technology 9, no. 12 (2021): 1850–54. http://dx.doi.org/10.22214/ijraset.2021.39236.

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Abstract: We proposed to use this system to minimise the frequency of accidents caused by driver exhaustion, hence improving road safety. This device uses optical information and artificial intelligence to identify driver sleepiness automatically. We use Softmax to find, monitor, and analyse the driver's face and eyes in order to calculate PERCLOS (% of eye closure). It will also employ alcohol pulse detection to determine whether or not the person is normal. Due to extended driving durations and boredom in crowded settings, driver weariness is one of the leading causes of traffic accidents, p

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6

Walke, Ms K. G., Harshvardhan Shete, Amjad Mulani, Darshan Asknani, and Rushikesh Gadekar. "Driver Drowsiness Detection System Using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 4306–10. http://dx.doi.org/10.22214/ijraset.2022.43105.

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Abstract: We proposed to use this system to minimise the frequency of accidents caused by driver exhaustion, hence improving road safety. This device uses optical information and artificial intelligence to identify driver sleepiness automatically. We use Softmax to find, monitor, and analyse the driver's face and eyes in order to calculate PERCLOS (% of eye closure). It will also employ alcohol pulse detection to determine whether or not the person is normal. Due to extended driving durations and boredom in crowded settings, driver weariness is one of the leading causes of traffic accidents, p

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7

Chinthalachervu, Rohith, Immaneni Teja, M. Ajay Kumar, N. Sai Harshith, and T. Santosh Kumar. "Driver Drowsiness Detection and Monitoring System using Machine Learning." Journal of Physics: Conference Series 2325, no. 1 (2022): 012057. http://dx.doi.org/10.1088/1742-6596/2325/1/012057.

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Abstract In the present world, lots of road accidents take place due to the lack of attention and alertness of driver. This is termed as driver drowsiness. This leads to a lot of unfortunate situations causing adverse damage to human lives. The main goal of this research is the detection of driver drowsiness and an appropriate response to the detection. There are many methods which are based on the motion of the vehicle or based on the driver’s behavior. One of the methods is the physiological method which helps in distracting the driver from drowsiness and making him alert. And few methods re

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8

Mustafa, Kamel Gatea, Kamel Gharghan Sadik, Khalid Ibrahim Raed, and Hussein Ali Adnan. "A survey on driver drowsiness detection using physiological, vehicular, and behavioral approaches." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1489~1496. https://doi.org/10.11591/eei.v11i3.3098.

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Drowsiness is a significant reason for street mishaps and has huge ramifications for driver safety. A few lethal mishaps can be prohibited if the sleepy drivers are cautioned in time. There are a number of tiredness identification strategies that screen the drivers’ languor state while driving and caution unfocused drivers. Highlights may be gathered from outward appearances (e.g., yawning and eyes and head movement) to determine the degree of laziness. This paper presents a holistic investigation of current strategies for driver laziness discovery and gives an exploration of widelyused

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9

RAJASEKHAR CHOPPELLI and Dr. PANKAJ GUPTA. "SMART DRIVER SAFETY ALERT SYSTEM USING RASPBERRY PI FOR REAL-TIME ROAD HAZARD DETECTION." International Journal of Engineering Research and Science & Technology 12, no. 1 (2016): 10–19. https://doi.org/10.62643/ijerst.2016.v12.i1.pp10-19.

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With road safety becoming an increasing global concern, especially in countries like India with high accident rates, the need for intelligent driver assistance systems is more critical than ever. This research presents a smart driver alert system developed using a Raspberry Pi controller integrated with a suite of sensors including accelerometers, ultrasonic modules, GPS, and a camera module. The system identifies various road hazards such as potholes, foggy zones, drowsiness, alcohol consumption, and sudden impacts. Upon detecting any anomaly, real-time alerts are issued through visual, audio

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10

Kim, Sehyeon, Zhaowei Chen, and Hossein Alisafaee. "Imaging lidar prototype with homography and deep learning ranging methods." Journal of Optics 24, no. 3 (2022): 035701. http://dx.doi.org/10.1088/2040-8986/ac4870.

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Abstract We report on developing a non-scanning laser-based imaging lidar system based on a diffractive optical element with potential applications in advanced driver assistance systems, autonomous vehicles, drone navigation, and mobile devices. Our proposed lidar utilizes image processing, homography, and deep learning. Our emphasis in the design approach is on the compactness and cost of the final system for it to be deployable both as standalone and complementary to existing lidar sensors, enabling fusion sensing in the applications. This work describes the basic elements of the proposed li

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11

Miclea, Răzvan-Cătălin, Vlad-Ilie Ungureanu, Florin-Daniel Sandru, and Ioan Silea. "Visibility Enhancement and Fog Detection: Solutions Presented in Recent Scientific Papers with Potential for Application to Mobile Systems." Sensors 21, no. 10 (2021): 3370. http://dx.doi.org/10.3390/s21103370.

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In mobile systems, fog, rain, snow, haze, and sun glare are natural phenomena that can be very dangerous for drivers. In addition to the visibility problem, the driver must face also the choice of speed while driving. The main effects of fog are a decrease in contrast and a fade of color. Rain and snow cause also high perturbation for the driver while glare caused by the sun or by other traffic participants can be very dangerous even for a short period. In the field of autonomous vehicles, visibility is of the utmost importance. To solve this problem, different researchers have approached and

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12

Dr., Himanshu Monga. "ENERGY EFFICIENT OPTICAL CHARACTER RECOGNITION (OCR) BASED SMART VEHICLE AUTHENTICATION & ACCESS CONTROL SYSTEM." International Journal of Advances in Engineering & Scientific Research 3, no. 4 (2016): 33–42. https://doi.org/10.5281/zenodo.10773961.

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<strong>Abstract: </strong>   The proposed system can heighten supervision as well as proficiency of an Authentication and Access Control System. In today’s world, all individuals utilize diverse forms of security goods in their factories, workplaces and households. For instance, video recorders, cameras, sensors, GSM, and alarm centered security networks. This project can be used at entrance of any secure area where ever we need high security to control the access of confidential vehicles only. The various modules of the project will be webcam installed with PC, Microcontroller uni

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13

Liu, Wei. "Deflection Basin Detection of Pavements Based on Linear Array Charge-Coupled Device (CCD) Photoelectric Sensors." Journal of Nanoelectronics and Optoelectronics 18, no. 12 (2023): 1410–18. http://dx.doi.org/10.1166/jno.2023.3540.

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Deflection is an important indicator of the overall pavement strength, and it is generally detected using the Falling Weight Deflectometer (FWD). In response to the shortcomings of FWD in use, a pavement deflection detection method based on a linear array charge-coupled device (CCD) photoelectric displacement sensor is proposed. Firstly, a detailed description is given of the working principle of the deflection detection photoelectric sensor for the center point of the deflection basin and other points. Secondly, a photoelectric displacement sensor using linear array CCD deflection detection i

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14

Dr.Subba, Reddy Borra, Rao K.Samhitha, K.Jeevitha, and Taruni Meeni. "Drowsy Driver Monitoring System." October 15, 2022. https://doi.org/10.5281/zenodo.7206642.

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One of the leading causes of traffic accidents and fatalities is drowsiness while driving. Driver drowsiness detection and indication is therefore an active research area. Most of the conventional methods are either vehicle based, behavioral based or physiological-based. There are few ways to get in the way and distract the driver, and some require expensive sensors and data processing. Therefore, in this study, a cost-effective real-time driver drowsiness detection system with acceptable accuracy is developed. In the development system, a webcam records the video and uses image processing tec

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15

Sakshi Bhoir, Sahibpreet Singh, Saish Desai, and Sujan Raktade. "Driver Drowsiness Detection." International Journal of Advanced Research in Science, Communication and Technology, May 19, 2022, 855–60. http://dx.doi.org/10.48175/ijarsct-3869.

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Every year many human beings lose their lives because of fatal road injuries round the arena and drowsy driving is one of the number one causes of avenue accidents and demise. Fatigue and micro sleep at the using controls are often the basis reasons of significant injuries. But preliminary signs of fatigue may be detected earlier than a vital scenario arises and therefore, detection of driving force’s fatigue and its indication is an ongoing research subject matter. Most of the conventional strategies to hit upon drowsiness are based on behavioral aspects while some are intrusive and might dis

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16

B.SHIVANI, GOUD B.ROHIT, REDDY E.MAHIDHAR, and RAM M.SAI. "DRIVER DROWSINESS MONITORING SYSTEM USING VISUAL BEHAVIOUR AND MACHINE LEARNING." July 24, 2022. https://doi.org/10.5281/zenodo.6894692.

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<em>Drowsy driving is one of the major causes of road accidents and death. Hence, detection of driver’s fatigue and its indication is an active research area. Most of the conventional methods are either vehicle based, or behavioral based or physiological based. Few methods are intrusive and distract the driver, some require expensive sensors and data handling. Therefore, in this study, a low cost, real time driver’s drowsiness detection system is developed with acceptable accuracy. In the developed system, a webcam records the video and driver’s face is detected in each frame

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17

"DRIVER DROWSINESS DETECTION USING MACHINE LEARNING." International Journal For Innovative Engineering and Management Research, September 27, 2022, 601–12. http://dx.doi.org/10.48047/ijiemr/v11/i06/39.

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Drowsy driving is one of the major causes of road accidents and death. Drivers must keep a close eye on the road, so they can react to sudden events immediately. Driver fatigue often becomes a direct cause of many traffic accidents. Therefore, there is a need to develop the systems that will detect and notify the driver bad psychophysical condition, which could significantly reduce the number of fatigue related car accidents. However, the Development of such systems encounters many difficulties related to fast and proper recognition of a driver’s fatigue symptoms.. Most of the conventional met

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18

Knapik, Mateusz, and Bogusław Cyganek. "Fast eyes detection in thermal images." Multimedia Tools and Applications, September 23, 2020. http://dx.doi.org/10.1007/s11042-020-09403-6.

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Abstract In recent years many methods have been proposed for eye detection. In some cases however, such as driver drowsiness detection, lighting conditions are so challenging that only the thermal imaging is a robust alternative to the visible light sensors. However, thermal images suffer from poor contrast and high noise, which arise due to the physical properties of the long waves processing. In this paper we propose an efficient method for eyes detection based on thermal image processing which can be successfully used in challenging environments. Image pre-processing with novel virtual high

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19

"AI-Powered Road Safety: Detecting Driver Fatigue through Visual Cues." International Journal of Information Systems and Computer Sciences 12, no. 3 (2023): 7–11. http://dx.doi.org/10.30534/ijiscs/2023/011232023.

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Driving when fatigued is among the main causes of road deaths. Consequently, one ongoing research area is how to recognize driver fatigue and how to determine whether it is present. A large percentage of conventional methods are either based on machines, the behavior of people, or physiological processes. Some solutions need expensive sensors and data processing, while others are infiltrating and uncomfortable to the driver. As a consequence, this study creates an accurate, real-time method for identifying driver fatigue. The footage is captured by a camera, and image processing techniques are

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20

Ahangar Darband, Maryam, and Esmaeil Najafiaghdam. "Implementation of a Cost-Effective, Accurate Photoacoustic Imaging SystemBased on High-Power LED Illumination and FPGA-Based Circuitry." Archives of Acoustics, December 5, 2023. https://doi.org/10.24425/aoa.2024.148820.

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Imaging based on the photoacoustic (PA) phenomenon is a type of hybrid imaging approach that combines the advantages of pure optical and pure acoustic imaging, achieving good results. This method, which offers high resolution, suitable contrast, and non-ionizing radiation, is valuable for the early detection of various types of cancer. Recently, multiple studies have focused on improving different components of this imaging system. In this presentation, we implemented a simplest form of a PA imaging system for detecting blood vessels, given that angiogenesis is recognized as a common symptom o

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21

Srinivas, Koppu. "A Survey on Recent Trends in Human-Computer Interaction." September 28, 2012. https://doi.org/10.5121/ijbb.2012.2302.

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International Journal on Bioinformatics & Biosciences (IJBB) Vol.2, No.3, September 2012 DOI : 10.5121/ijbb.2012.2302 13 A Survey on Recent Trends in Human-Computer Interaction Srinivas Koppu1 , V. Madhu Viswanatham2 and Kamalakannan J1 1 School of Information Technology and Engineering, VIT University, Vellore, India srinukoppu@gmail.com and jkamalakannan@vit.ac.in 2 School of computing Science and Engineering VIT University, Vellore, India vmadhuviswanatham@vit.ac.in ABSTRACT This paper identifies the different kinds of methods, which helps human to communicate with computer. Traditional

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