Table of Contents
Abstract
Ever increasing number of traffic accidents within the world are often reduced if modern technology is incorporated within the vehicles to assess the fitness of the driving force at regular intervals during the movement of the vehicle and preventive measures are automatically taken for the security of all concerned entities, both within the vehicle and out of doors the vehicle. The microcontroller controls the capacity of hand-off and along these lines the start. The Raspberry Pi controller constantly records every one of the parameters of car for anticipation and recognition of mishap. In a critical situation many vehicles faces accident, because of this lot of person lost their lives. Some people are often saved at that point , but due to lack of data , time and place it is not be possible, through the mail we can intimate to the hospital.
Keywords: Raspberry pi, microcontroller, data, vehicle accidents.
Introduction
The innovations within the industry over the last hundred years have made our vehicles more powerful, easier to drive and control safer more energy efficient, and more environmentally friendly. Majority of the accidents caused today by cars are mainly thanks to the driving force fatigue. Driving for an extended period of your time causes excessive fatigue and tiredness which successively makes the driving force sleepy or loose awareness. With the rapid increase within the number of accidents seems to be increasing day to day.
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Therefore a requirement arises to style a system that keeps the driving force focused on the road. Data on road accidents in India are collected by Transport Research Wing of Ministry of Road Transport & Highways. The aim of this paper is to develop a prototype of drowsy driver warning system. Our whole focus and concentration are going to be placed on designing the system which will accurately monitor the open and closed state of the driver’s eye in real time and by tilting of head. This detection are often done employing a sequence of images of eyes also as face and head movement using accelerometer module. The observation of eye movements and head movement using accelerometer will be used.
Devices to detect when drivers are falling asleep and to supply warnings to alert them of the danger , or maybe control the vehicle’s movement, are the topic to much research and development. Driver fatigue may be a significant issue leading to many thousands of road accidents annually . It is not currently possible to calculate the precise number of sleep related accidents due to the difficulties in detecting whether fatigue was an element and in assessing the level of fatigue. However research suggests that up to 25% of accidents on monotonous roads in India are fatigue related. Research in other countries also indicates that driver fatigue may be a significant issue . Young male drivers, truck drivers, company car drivers and shift workers are the foremost in danger of falling asleep while driving.
However any driver travelling long distances or once they are tired, it’s at the danger of a sleep related accidents. The early hours of the morning and therefore the middle of the afternoon are the height times for fatigue accidents and long journeys on monotonous roads, particularly motor-ways, are the most likely to end in a driver falling asleep. In this paper the algorithms for face detection and eye tracking have been developed on frontal faces with no restrictions on the background .The proposed method for eye tracking is built into five stages. These include coarse and fine face detection, finding the attention region of maximum probability.
Literature Survey
The problem of vehicle accident detection has been an issue since long time and is of major problems among people. Some already proposed systems in the area are as explained below.
Md. Syedul Amin, Jubayer Jalil and M. B. I. Reaz [1] proposed Accident Detection and Reporting System using GPS, GPRS and GSM Technology. This paper proposes to utilize the capability of a GPS receiver to monitor the speed of a vehicle and detect an accident basing on the monitored speed and send the location and time of the accident from the GPS data processed by a microcontroller by using the GSM network to the Alert Service Center.
Adnan Bin Faiz , Ahmed Imteaj and Mahfuzulhoq Chowdhury [2] proposed Smart Vehicle Accident Detection and Alarming System Using a Smartphone.The researchers have implemented GPS receiver in phone to detect the rapid change of deceleration that occurred at accident time. It also takes the change of pressure from the pressure sensor and the change of tilt from an accelerometer sensor in a Smartphone. By detecting these three conditions as accident detection, this android app send the accident location for emergency help. An emergency switch option also added to this app which provides a chance to driver for sending alert message without checking accident detection condition.
T Kalyani, S Monika, B Naresh, Mahendra Vucha [3] proposed Accident Detection and Alert System .The proposed system will check whether an accident has occurred and notifies to nearest medical centers and registered mobile numbers about the place of accident using GSM and GPS modules. The location can be sent through tracking system to cover the geographical coordinates over the area. The accident can be detected by a vibration sensor which is used as major module in the system
Gas Sensor
Gas sensor is used to detect the presence of a dangerous LPG leak in your car or in a work station , storage tank environment. This unit are often easily incorporated into an alarm unit, to sound an alarm or provides a visual indication of the LPG concentration. The sensor has excellent sensitivity combined with a fast repsonse time. The sensor also can sense iso-butane, propane, LNG and cigarette smoke.
Heart Beat Sensor
Heart beat sensor is supposed to supply digital output of heart beat when a finger is placed on it. When the heart beat detector is functioning , the beat LED flashes in unison with each heart beat. This digital output is connected to microcontroller to analyse the Beats Per Minute (BPM) rate. it’s It is based on the principle of light modulation by blood flow through finger at each pulse.
GPS
The GPS module L10 brings the high performance of the MTK positioning engine to the economic standard. The L10 supports 210 PRN channels. This versatile, stand-alone receiver combines an thorough array of features with flexible connectivity options. Their simple integration leads to fast time-to-market during a wide selection of automotive, consumer and industrial applications.
GSM
Global system for mobile communication (GSM) is a standard for digital cellular communication. GSM provides recommendations, not requirements. The GSM specifications define the functions and interface requirements intimately but don’t address the hardware. The reason for this is often to limit the designers as little as possible but still to form it possible for the operators to get equipment from different suppliers. The GSM network is divided into three systems: the switching system, the base station system, and the operation and support system.
Mems Sensor
The skin may be illuminated with visible (red) or infrared LEDs using transmitted or reflected light for detection. The very small changes in reflectivity or in transmittance caused by the varying blood content of human tissue are almost invisible. Various noise sources may produce disturbance signals with amplitudes equal or even higher than the amplitude of the pulse signal. Valid pulse measurement therefore requires extensive preprocessing of the raw signal.
Load Cell
A load cell is a type of transducer specifically a force transducer. It converts a force such as tension, compression, pressure, or torque into an electrical signal that can be measured and standardized. As the force applied to the load cell increases, the electrical signal changes proportionally. The most common types of load cell used are hydraulic, pneumatic, and strain gauge.
Raspberry Pi
Raspberry Pi board is a miniature marvel, packing considerable computing power into a footprint no larger than a credit card. It’s capable of some amazing things, but there are a few things you’re going to need to know before you plunge head-first into the bramble patch. The processor at the heart of the Raspberry Pi system is a Broadcom BCM2835 system-on-chip (SoC) multimedia processor.
This means that the vast majority of the system’s components, including its central and graphics processing units along with the audio and communications hardware, are built onto that single component hidden beneath the 256 MB memory chip at the centre of the board It’s not just this SoC design that makes the BCM2835 different to the processor found in your desktop or laptop, however. It also uses a different instruction set architecture (ISA), known as ARM.
ARM vs. x86
The BCM2835 SoC, located beneath a Hynix memory chip Developed by Acorn Computers back in the late 1980s, the ARM architecture is a relatively uncommon sight in the desktop world. Where it excels, however, is in mobile devices: the phone in your pocket almost certainly has at least one ARM-based processing core hidden away inside. Its combination of a simple reduced instruction set (RISC) architecture and low power draw make it the perfect choice over desktop chips with high power demands and complex instruction set (CISC) architectures.
The ARM-based BCM2835 is the secret of how the Raspberry Pi is able to operate on just the 5V 1A power supply provided by the onboard micro-USB port. It’s also the reason why you won’t find any heat-sinks on the device: the chip’s low power draw directly translates into very little waste heat, even during complicated processing tasks. It does, however, mean that the Raspberry Pi isn’t compatible with traditional PC software.
The majority of software for desktops and laptops is built with the x86 instruction set architecture in mind, as found in processors from the likes of AMD, Intel and VIA. As a result, it won’t run on the ARM-based Raspberry Pi. The BCM2835 uses a generation of ARM’s processor design known as ARM11, which in turn is designed around a version of the instruction set architecture known as ARMv6.
Softwares Used
OPEN cv
OpenCV [OpenCV] is an open source (see http://opensource.org) computer vision library available from (http://SourceForge.net/projects/opencvlibrary). The e-library has been programmed in C and C++ and runs under Linux, Windows and Mac OS X. There is an active development on interfaces for Python, Ruby, Matlab, and other languages. OpenCV was designed for computational efficiency and with a robust specialise in realtime applications. OpenCV is written in optimized C and may cash in of multicore processors. OpenCV automatically uses the acceptable IPP library at runtime if that library is installed. One of OpenCV’s goals is to supply a simple-to-use computer vision infrastructure that helps people build fairly sophisticated vision applications quickly.
Computer vision
Computer vision is the transformation of knowledge from a still or video camera into either a choice or a replacement representation. All such transformations are finished achieving some particular goal. The input file may include some contextual information like “the camera is mounted during a car” or “laser range fi nder indicates an object is 1 meter away”.The decision could be “there may be a person during this scene” or “there are 14 tumor cells on this slide”.
A new representation might mean turning a color image into a grayscale image or removing camera motion from a picture sequence. Because we are such visual creatures, it’s easy to be fooled into thinking that computer vision tasks are easy. How hard can it’s to seek out , say, a car once you are watching it in an image? Your initial intuitions can be quite misleading. The human brain divides the vision signal into many channels that stream different kinds of information into your brain. Your brain has an attention system that identifies, during a task-dependent way, important parts of an image to seem at while suppressing examination of other areas.
Proposed Work
The Driver accident detection System paper is basically a device proposed in order to save the life of the drivers that are continuously riding the car and are not provided the sufficient sleep due which severe accidents take place especially in the developing countries like India, where the number of running vehicles increases every year. The proposed system safeguards the driver from any accident that take place because of the drowsiness of the driver.
The proposed system is cheap as compared to other systems that are present only in the luxurious car models. Also, due to its high portability, it can be installed in old cars easily as well . This is one of the most important and effective feature of the system that make it practical. It is able to detect if the eye is closed or open and based Whenever vehicle driver lonely closed for the eyes that time water spray flowing to the face and sound alert system also activated.
Conclusion
The Driver accident detection System paper is basically a device proposed in order to save the life of the drivers that are continuously riding the car and are not provided the sufficient sleep due which severe accidents take place especially in the developing countries like India, where the number of running vehicles increases every year. The proposed system safeguards the driver from any accident that take place because of the drowsiness of the driver.
The proposed system is cheap as compared to other systems that are present only in the luxurious car models. Also, due to its high portability, it can be installed in old cars easily as well . This is one of the most important and effective feature of the system that make it practical. It is able to detect if the eye is closed or open and based Whenever vehicle driver lonely closed for the eyes that time water spray flowing to the face and sound alert system also activated.
References
- Peng Wang, Matthew B. Green, Qiang Ji, Automatic Eye Detection and Its Validation, San Jose State University, California, United States of America, 2005
- Singh Himani Parmar, Mehul Jajal, Yadav Priyanka Brijbhan, Drowsy Driver Warning System Using Image Processing ,Gujarat Engineering College, Bharuch, Gujarat, India, International Journal Scientific Engineering and Technology Research , April 2014
- Saad A. Sirohey, Azriel Rosenfeld, Eye detection in a face image using linear and nonlinear filters, University of Maryland, United States of America, Elsevier,2001
- IJEDR(International Journal of Engineering Development And Research Volume 1 Issue3(Dec-2013) Issn: 2321-9939 Pp 78-83 On “Drowsy Driver Warning System Using Image Processing” By Singh Himani Parmar, Mehul Jajal, Yadav Priyanka Brijbhan.
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- Ueno H., Kanda, M. and Tsukino, M. “Development of Drowsiness Detection System”,IEEE Vehicle Navigation andInformation Systems Conference Proceedings,(1994), ppA13,15-20.
- Paul Stephen Rau, National Highway Traffic Safety Administration, United States, Paper Number 05-0192Drowsy Driver Detection and Warning System for Commercial Vehicle Drivers: Field Operational Test Design, Data Analyses and progress.
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- A.Hemlata, Mahesh Motwani, Single Frontal Face Detection by Finding Dark Pixel Group and Comparing Xy-Value of Facial Features, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 2, March – April (2013), pp. 471-481
