Author(s):  
Pranav Patil ◽  
Kishor Gangurde ◽  
Aniket Khairnar ◽  
Akash Mule ◽  
P. T. Suradkar

In today’s world as the population increases day by day the numbers of vehicle also increases on the roads and highways. This results in more accident because of rider’s poor behaviors such as speed driving, drunk driving, riding without helmet protection, riding without sufficient sleep etc. In most of the accident cases, the victims loses their lives because of unavailability of medical facilities instantly. The critical time between the accident and getting victim medical help can be the difference between life and death. It is very difficult to know that an accident has occurred and to locate position where it has happened. To solve this problem “Accident Detection and Alert System” is used to save lives by making the medical facilities arriving on time. To resolve this problem we are developing a wireless system using Accelerometer, GPS and GSM for accident detection and reporting. If any accident occurs, this wireless device will send automated message and call the police, family members giving the exact position where the crash had occurred. So they can provide proper help to victim. This system is used to report information related to accident location and personal profile. Personal profile contains name, blood group, address, phone number of family members. So it will be easy to provide help and identify the victim.


Drowsy driving is as dangerous as drunk driving. Many people, especially youth, ignore this and still continue to drive in this state. Drowsiness is the one of the major causes of road accidents, especially at night. Eating certain kinds of food causes the blood sugar levels to plummet which make the driver energy deprived. Many drivers consume alcohol at night which causes dizziness that leads to fatal accidents. Many lives are lost due to accidents caused by drowsiness. There are many papers which studied and found out the exact blink rate for drowsiness detection, but in this paper we will first study the driver’s blink rate, as it may vary from person to person, and then after learning, actions will be taken according to the driver’s learnt blink rate. This paper describes the system that monitors the blinks of the driver which can be used to detect drowsiness and prevent such fatalities. After detecting the drowsiness, we aim to alert the driver about the drowsiness using certain alarm sounds.


2018 ◽  
Vol 181 (25) ◽  
pp. 38-45
Author(s):  
Rajneesh R ◽  
Anudeep Goraya ◽  
Gurmeet Singh

Author(s):  
Sagara Sumathipala ◽  
Danodya Weerasinghe ◽  
Meleeshiya jayakody ◽  
Shashika Eranda ◽  
Thanuja Gunasekara

Several reasons can be sighted for the cause of these road accidents. Few of them include lack of sleep, drunk driving, violation of traffic rules, etc. Amongst them, the state of drowsiness and drunk driving alone contributes to 36% of accidents. Though a number of national schemes and traffic rules have been implemented to avoid these road accidents, it could only bring down the accident rate by 10%. As car accidents are one of the major issues of concern, this paper will be discussing mainly on Drunk driving or drowsiness. In these recent years, various methods have been proposed to implement drowsiness detection based on Hough transforms. Here, in this paper, we have determined a technique to detect drowsiness among car drivers and alert them whenever they tend to sleep. The algorithm is based on eye-blink and yawn frequency. It deals with an eye blink yawn frequency algorithm that uses eye coordinates to keep track of person and determine the open or closed state of the eye and generate an alarm if the driver is drowsy. The yawn count is determined by checking the frequency of yawn count with a minimum threshold value.


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