scholarly journals IOT BASED APPROACH FOR REMOTELY MONITORING AND ALARMING A DROWSY DRIVER

2021 ◽  
pp. 76-83
Author(s):  
Mr. Aniket Ashok Bhamani ◽  
Mr. Sanyam Sanjay Mehta
Keyword(s):  
Internet Of Things ◽  
Text Message ◽  
Road Accidents ◽  
Voice Call ◽  
Drowsy Driving ◽  
The Road ◽  
Car Crash ◽  
Falling Asleep ◽  
Commercial Drivers ◽  
Cross Platform

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.

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

2020 ◽  
Vol 9 (5) ◽  
pp. 2409-2412
Keyword(s):  
Network Architecture ◽  
High Speed ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Road Accidents ◽  
Prevention Measures ◽  
Drowsy Driving ◽  
Closure Rate ◽  
The Road ◽  
Eye Closure

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.

Comparative Analysis of Intelligent Driving and Safety Assistance Systems Using YOLO and SSD Model of Deep Learning

2021 ◽  
Vol 12 (1) ◽  
pp. 131-146
Author(s):  
Nidhi Sindhwani ◽  
Shekhar Verma ◽  
Tushar Bajaj ◽  
Rohit Anand
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Deep Learning ◽  
Comparative Analysis ◽  
Internet Of Things ◽  
Road Accidents ◽  
The Road ◽  
The World ◽  
Assistance Systems ◽  
On The Road

Bad road conditions are one of the main causes of road accidents around the world. These kinds of accidents prove to be fatal as many lives are lost in these accidents that are mainly caused by potholes or distress on surface of roads. This paper suggests a system that will not only help in reducing the chances of these accidents by making the driver aware of the upcoming distress/potholes on the road but also saving the location of these potholes which can be sent to respective authorities so that they can be repaired. The authors have used technologies like image processing, computer vision, deep learning, and internet of things (IoT) to make this happen. It uses a camera mounted in front near windshield that will capture the images which will be further be processed to get the location of the potholes and distress on road. These detected potholes can be projected on a heads-up display (HUD) placed near windshield which will notify the driver of the potholes.

scholarly journals Understanding Urban Commercial Vehicle Driver Behaviors and Decision Making

2021 ◽  
pp. 036119812110035
Author(s):  
Giacomo Dalla Chiara ◽  
Klaas Fiete Krutein ◽  
Andisheh Ranjbari ◽  
Anne Goodchild
Keyword(s):  
Commercial Vehicle ◽  
Operating Time ◽  
Common Belief ◽  
Policy Makers ◽  
Factors Affecting ◽  
Urban Freight ◽  
The Road ◽  
Commercial Drivers ◽  
The Common ◽  
Printed Materials

As e-commerce and urban deliveries spike, cities grapple with managing urban freight more actively. To manage urban deliveries effectively, city planners and policy makers need to better understand driver behaviors and the challenges they experience in making deliveries. In this study, we collected data on commercial vehicle (CV) driver behaviors by performing ridealongs with various logistics carriers. Ridealongs were performed in Seattle, Washington, covering a range of vehicles (cars, vans, and trucks), goods (parcels, mail, beverages, and printed materials), and customer types (residential, office, large and small retail). Observers collected qualitative observations and quantitative data on trip and dwell times, while also tracking vehicles with global positioning system devices. The results showed that, on average, urban CVs spent 80% of their daily operating time parked. The study also found that, unlike the common belief, drivers (especially those operating heavier vehicles) parked in authorized parking locations, with only less than 5% of stops occurring in the travel lane. Dwell times associated with authorized parking locations were significantly longer than those of other parking locations, and mail and heavy goods deliveries generally had longer dwell times. We also identified three main criteria CV drivers used for choosing a parking location: avoiding unsafe maneuvers, minimizing conflicts with other users of the road, and competition with other commercial drivers. The results provide estimates for trip times, dwell times, and parking choice types, as well as insights into why those decisions are made and the factors affecting driver choices.

scholarly journals The Golden Hour Trauma Care

2021 ◽  
Author(s):  
Subbiah Venkatesh Babu
Keyword(s):  
Trauma Care ◽  
Initial Treatment ◽  
Road Accidents ◽  
Golden Hour ◽  
The Road ◽  
High Chance ◽  
Great Burden

AbstractGlobally the road accidents had become a great burden and claiming lot of precious lives today. However, the initial treatment within the first hour of the injury indeed had proven the high chance of survival after the trauma. This article updates and signifies the systematic emergency approach and current principles in saving lives after injury.

CHILDREN ROAD SAFETY AWARENESS: DESIGN AND DEVELOPMENT OF A ROAD SAFETY APPLICATION

2015 ◽  
Vol 77 (29) ◽  
Author(s):  
Nassiriah Shaari ◽  
Aeni Zuhana Saidin ◽  
Asmidah Alwi
Keyword(s):  
Road Safety ◽  
Web Application ◽  
Interactive Multimedia ◽  
Road Accidents ◽  
Design And Development ◽  
The Road ◽  
Usability Test ◽  
Safety Awareness ◽  
Safety Application ◽  
On The Road

Road safety campaigns and programs have been extensively introduced and implemented in Malaysia. However, their effectiveness is still being debated. Children especially will become the unfortunate victims of road accidents if they are unaware of the danger and precaution actions to be safe on the road. In response to that, this paper introduces an application as an alternative that inculcates road safety awareness to further support existing related programs and campaigns. Particularly, an interactive web application incorporating interactive multimedia elements has been designed and evaluated. Results on the usability test indicate a promising success and highlight aspects and issues that can be further focused for improvement and enhancement. 

scholarly journals Designing Traffic Signal at an Unsignalized Intersection

2021 ◽  
pp. 90-107
Author(s):  
Prachi Agrawal ◽  
Preeti Kumari ◽  
Dr. Manish Dutta
Keyword(s):  
Programming Language ◽  
Smart City ◽  
Traffic Signal ◽  
Road Accidents ◽  
The Road ◽  
Road Intersections ◽  
Smooth Movement ◽  
On The Road

The increasing number of vehicles on the road intersections has given rise to many problems like road accidents, congestions add conflicts. These problems can only be solved by deigning proper traffic signal at intersections for continuous and smooth movement of vehicles Nagpur- though the smart city- is also facing the same problem. This paper presents the proper designing and simulation of traffic signal at an unsignalized intersection at Nagpur. The paper deals with the simulation of designed signal through a programming language like Python.

PREVENTION OF ADMINISTRATIVE OFFENSES IN THE FIELD OF ROAD TRAFFIC BY THE INTERNAL AFFAIRS BODIES

2021 ◽  
pp. 38-40
Author(s):  
А.Р. Исмагилова
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
The State ◽  
Road Accidents ◽  
The Road ◽  
Internal Affairs ◽  
On The Road

В статье раскрываются полномочия сотрудников подразделений пропаганды Государственной инспекции безопасности дорожного движения в целях профилактики дорожно-транспортных происшествий и травматизма на дороге. The article reveals the powers of the employees of the propaganda units of the State Traffic Safety Inspectorate in order to prevent road accidents and injuries on the road.

Real-Time V2V Communication With a Machine Learning-Based System for Detecting Drowsiness of Drivers

2021 ◽  
Vol 13 (4) ◽  
pp. 35-50
Author(s):  
Ahmed Y. Awad ◽  
Seshadri Mohan
Keyword(s):  
Machine Learning ◽  
Traffic Accidents ◽  
Ad Hoc ◽  
Economic Losses ◽  
Drowsy Driving ◽  
The Road ◽  
V2v Communication ◽  
Physical Injuries ◽  
On The Road ◽  
The U.S

This article applies machine learning to detect whether a driver is drowsy and alert the driver. The drowsiness of a driver can lead to accidents resulting in severe physical injuries, including deaths, and significant economic losses. Driver fatigue resulting from sleep deprivation causes major accidents on today's roads. In 2010, nearly 24 million vehicles were involved in traffic accidents in the U.S., which resulted in more than 33,000 deaths and over 3.9 million injuries, according to the U.S. NHTSA. A significant percentage of traffic accidents can be attributed to drowsy driving. It is therefore imperative that an efficient technique is designed and implemented to detect drowsiness as soon as the driver feels drowsy and to alert and wake up the driver and thereby preventing accidents. The authors apply machine learning to detect eye closures along with yawning of a driver to optimize the system. This paper also implements DSRC to connect vehicles and create an ad hoc vehicular network on the road. When the system detects that a driver is drowsy, drivers of other nearby vehicles are alerted.

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