scholarly journals An Effective Model to Alert a Drowsy Driver using Eye Closure Rate

Transportation plays a major role in today’s world. To move from one place to another place (long distances) which cannot be covered by walk, we use vehicles which consumes less time to reach destination. According to statistics, by 2050 the urban population will increase by 68% which leads to an increase in transportation that causes pollution and increase in the rate of road accidents. There are many methods and prevention measures to control pollution. The road accidents are caused due to distracted driving, high speed, drowsy driving and disobeying traffic rules. Among these, drowsy driving has been a cause for 20% of road accidents which is because of fatigue driving. In this article, a model is proposed based on image processing technique which is segmentation and a deep convolutional neural network architecture to improve the performance of the model when compared to the existing models. The proposed model works with better performance in different lighting conditions.

Author(s):  
Mr. Aniket Ashok Bhamani ◽  
Mr. Sanyam Sanjay Mehta

There are a lot of road accidents that occur due to drowsy driving. Drowsy driving is when the driver of a vehicle is found to be sleepy and probable to get into a car crash because of the same. Being drowsy might cause the driver to lose concentration from the road, and also reduce the reaction time. Statistics suggest how thousands of deaths and crashes happen every year due to it. Major victims of such crashes tend to be the commercial drivers who need to drive long distances overnight. Our project intends to propose a solution to this problem by providing an Internet of Things based approach. This approach monitors the driver’s face while he or she is driving the vehicle and in case if the driver is to be found falling asleep, an instant voice call is made to the driver’s registered phone number. Additionally, a text message is also sent to the driver’s emergency contact which will get him/her notified and provide the driver with quick assistance if needed. This approach is unique and different in its own way as it provides cross platform support and remote monitoring of the driver. Additionally, it also makes drowsy-detection ‘device independent’. It offers a simplified mechanism to derive real time accurate results and readings with reduced complexities. This project does have a lot of scope, especially considering that there is a lack of methodologies currently being implemented to prevent road accidents due to drowsy driving. KEYWORDS- Drowsy Driving, Monitoring, Machine Learning, Internet of Things, Remote, Algorithm, Eye Aspect Ratio, Python.


2020 ◽  
Vol 10 (13) ◽  
pp. 4490 ◽  
Author(s):  
Sunil Kumar Sharma ◽  
Haidang Phan ◽  
Jaesun Lee

Road surface monitoring is an essential problem in providing smooth road infrastructure to commuters. This paper proposed an efficient road surface monitoring using an ultrasonic sensor and image processing technique. A novel cost-effective system, which includes ultrasonic sensors sensing with GPS for the detection of the road surface conditions, was designed and proposed. Dynamic time warping (DTW) technique was incorporated with ultrasonic sensors to improve the classification and accuracy of road surface detecting conditions. A new algorithm, HANUMAN, was proposed for automatic recognition and calculation of pothole and speed bumps. Manual inspection was performed and comparison was undertaken to validate the results. The proposed system showed better efficiency than the previous systems with a 95.50% detection rate for various road surface irregularities. The novel framework will not only identify the road irregularities, but also help in decreasing the number of accidents by alerting drivers.


Author(s):  
María T. Valecillos ◽  
Carlos H. Romero ◽  
María A. Márquez ◽  
Sissi D. Vergara

Two-phase slug flow pattern is one of the most common flow patterns present in many industries, therefore its study becomes relevant. The aim of this work was to develop an automated computational program to determine the bubble gas velocity associated to gas-liquid two-phase slug flow by using video digital image processing technique. In order to obtain the images for the analysis, experiments were carried out using a pipe bench for air-water two-phase flow. The experimental facility is located in Simon Bolivar University, in Venezuela. The system has three pipes with different internal diameters and can be rotated around its axis and fixed at any inclination angle from horizontal to vertical flow. The tests were run in a horizontal pipeline of 0.03175m of internal pipe diameter and 8m long. For slug flow visualization a high speed camera Kodak Ektapro 4540mx imager was used. The camera was located in an x/D relation corresponding to 249 from the pipe inlet, ensuring the complete development of the flow. The camera allowed a maximum acquisition velocity of 4500 frames per second. The superficial velocity range was 0.16–1.79m/s and 0.16–1.26m/s for air and water, respectively. To summarize, 165 tests were performed and 1320000 images were analyzed with 20 flow rate combinations. The computational application was validated by comparing it with the velocities measured manually over selected images. Results obtained were compared to several correlations such as Bendiksen [1], Cook & Behnia [2] and Wang et al. [3].


Author(s):  
Özden Ağra ◽  
Hakan Demir ◽  
Ş. Özgür Atayılmaz ◽  
Ahmet Yurtseven ◽  
A. Selim Dalkılıç ◽  
...  

In this paper, the void fraction of alternative refrigerant R600a flowing inside horizontal tube is determined by means of an experimental technique, well known correlations in the literature and a generalized neural network analysis. The horizontal tube is made from smooth glass tubing of 4 mm inner diameter. The test runs are done at average saturated condensing temperatures between 30 and 40 °C while the average qualities and the mass fluxes are between 0.45–0.91 and 68.5–138.1 kg m-2s-1 respectively. The flow regime determination inside the tube is performed by means of sight glasses placed at the inlet and outlet sections of the test section, used for in-tube condensation tests, virtually. An image processing technique, performed by means of a high speed camera, is used to determine the void fractions of stratified and annular condensing flow of R600a experimentally. The void fractions are determined using relevant measured data together with 11 different void fraction models and correlations reported in the open literature analytically. Artificial neural network (ANN) analysis is developed to determine the void fractions numerically. For this aim, mass flow rate, average vapor quality, saturation temperature, liquid and vapor densities, liquid and vapor dynamic viscosities and surface tension are selected as the input parameters, while the void fraction is selected as the output. Three-layer network is used for predicting the void fraction. The number of the neurons in the hidden layer was determined by a trial and error process evaluating the performance of the network and standard sensitivity analysis. The measured void fraction values are found to be in good agreement with those from ANN analysis and correlations in the literature. It is also seen that the trained network are more predictive on the determination of void fraction than most of the investigated correlations.


Research aim is to establish the history of the first road accidents involving cars in Kharkiv in the early twentieth century. Research methodology. The article discusses the road accidents involving cars as one of the aspects of the emergence and development of new vehicles and ways of communication "traffic" in Kharkov in the early twentieth century from the point of view of the concept of modernization of urban space. Scientific novelty. For the first time in the historiography the history ofthe road accidents involving cars in Kharkov in the early twentieth century was the subject of special research. The publications from the newspapers «Yuzhnyj Kraj» («South Land») and «Utro» («Morning») newspapers revealed a number of testimonies of the first car accidents involving cars in Kharkiv in the early 20th century. The typical causes, circumstances, course and consequences of such incidents are established. Conclusions. It was found that the first car accidents were caused primarily by the unusualness of the new vehicle for traditional road users in time pedestrians, carriages and, especially, horses, which frightened the unusual view and high speed of automatic crews, the roar of their previous engines, known as time of movement of smoke and smoke, loud exhausts, internal combustion engines and various horns and even «sirens». Factors such as the poor quality of driver training and / or the irresponsibility of individual drivers when driving on city streets also played an important role in some cases. The most known example of dangerous behavior on the road was the case of a nobleman O. L. Samoilov (owner and driver of the infamous newspaper «Red Car»), who regularly consciously ensures the safety of road users. This has led to frequent road accidents involving schoolchildren of varying severity from other road users  people, animals (horses, dogs) and vehicles. At the same place on carriages and features of pedestrians who are accustomed to traffic on city streets. For a long time, they did not report the changes caused by the appearance of dozens of cars on the streets of Kharkiv and neglected their own safety, behaving carelessly.


2013 ◽  
Vol 655-657 ◽  
pp. 859-867
Author(s):  
Bin Luo ◽  
Wei Liu ◽  
Yun Luo

Aiming at the problems such as slow speed and low measuring accuracy existing in measuring length precision of pin parts in mass production, a new approach of high speed and precise measurement is proposed based on the research of the length measuring methods such as parallel laser length measuring method and area array CCD measuring method, etc. Application of (machine vision system and computer measurement & control technology) digital image processing technology can perform automatic high speed measurement and separation of workpiece effectively and accurately. The experimental results show that the machine speed could reach 4-5 pieces/second, with length measuring accuracy of around 10 microns, indicating that the approach proposed in this paper has important practical value.


2015 ◽  
Vol 16 (1) ◽  
pp. 136
Author(s):  
Behrouz Memarzadeh ◽  
Mohammad Ali Mohammadi

Vision-based flame detection has drawn significant attention in the past decade with camera surveillance systems becoming ubiquitous. This paper proposes a multi criterion method to detect fire or flames by processing the video data generated by a high speed camera. Since flame images are special class of images, some of the unique features of a flame may be used to identify flame. There are some differences between flame images and other general images. By using these features we are able to detect fire correctly with least false alarm. In this paper we present an algorithm which can detect fire and reduce number of false alarms by counting number of identified pixels. In the algorithm, we preprocess the images to have better results. So first we adjust the gray level of a flame image according to its statistical distribution to have better processing. After that we try to extract fire features in images. First by using color characteristics, the ratio of red to green, we can identify probable fire-like or fire like pixels. Second, to highlight the regions with high gray level contrast at their edges, we use the extended prewitt filter. We use AND operation on two above processing images to remove unrelated pixels, at last by using flicker frequency, the oscillating change in the number of identified pixels over time is transformed into the frequency domain to complete detection algorithm. Simulation proves the algorithm ability to detect fire in different situations in video sequences.


2015 ◽  
Vol 813-814 ◽  
pp. 1018-1022
Author(s):  
S. Naveen ◽  
T. Sriram ◽  
S. Prithvi Raj ◽  
M. Venkatesan

The study of bubble column reactors has its significance in applications such as multiphase reactors, aerators and in industrial waste-water treatment. Extensive works has been done in studying the hydrodynamics of a single gas bubble flowing through stationary liquid phase. The natural breakup of bubble during its motion has been studied in the past. In the Part I of the present work, hydrodynamics of an air bubble after its artificial splitting using a stainless steel mesh is experimentally studied using image processing and high speed photography. The significance of bubble splitting is that it increases the surface area of contact between stationery and moving fluid which in turn increases the rate of reaction desired during the process. The motion of the bubble is captured during its release and after splitting using High-Speed Camera. The velocity, area and diameter of the bubble before and after splitting are calculated by applying Image processing technique on the high speed photograph. The splitting of the bubble is found to vary with the superficial gaseous velocity. The splitting of bubbles into two bubbles of nearly equal size is considered and its hydrodynamic characteristics are studied.


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