An Integrated Driver Monitoring and Adaptive Assistant Security System


Call for Papers Engineering Research Journal June 2019

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An Integrated Driver Monitoring and Adaptive Assistant Security System

Janani.N1

Embedded Systems, EEE Depart ment Dhanalakshmi Srinivasan Engineering Co llege Pera mbalur, Ta milnadu

jananinece08@g mail.co m

Saranya.N2

Embedded Systems, EEE Depart ment Dhanalakshmi Srinivasan Engineering Co llege,

Pera mbalur, Ta mil Nadu

sarancharuu@gmail.co m

Abstract—- This paper is proposed to implement several related concepts of driver vigilance and driver safety in the field of cognitive vehicles. It provides superior safety by integrating the driver monitoring system into the vehicular control system. The existing system uses eye blink sensor technology alone for driver fatigue detection. Since it has some drawbacks, this paper suggests valuable solution to such problems by employing various features like Mobile Baseband Monitoring, Hands Free Auto Reply S MS , Driver Fatigue Warning, Drunk and Drive Prevention, Collision Pre safe Activation, GS M and GPS Based Accident/Panic Alert. S o it is not only important to develop more active safety features to avoid accidents but it is equally important to develop cost-effective technological solutions that can accurately identify the driving behavior of drivers and to assist them.

Keywords—Short Messaging Service (SMS), Global System for Mobile Communication (GSM), Global Positioning System (GPS).

  1. INTRODUCTION

    According to experimental and real-wo rld study, the root cause of ma jority of accidents can be traced back to the behavior of the one who drives the vehicle, the driver h imself. The e xisting system provides a very narrow solution to this problem of monitoring the behavior of driver. It alerts the driver who is drowsy using eye blink sens ing technology. It uses a wearable eye b lin k sensor which checks the eye blin k of driver and if the count of eye blink decreases, it means that the driver is drowsy and alerts him using buzzer ala rm and locks the ignition system of the vehicle.

    But it has the drawback of pas sing continuous stream of IR signals from eye blin k sensor which may affect the eye sight of driver and it does not prevent the drivers other ma lfunctions such as using mobile phones, consuming alcohol, fee ling drowsy or fatigue while driving wh ich pose danger to his life . So it is vital to develop solution for these problems which is done using the proposed system. It a lso has improved effic iency of ARM Corte x M 3 than ARM 7 in e xisting system.

    This paper [1] presents a low-cost and simp le dis tributed

    force sensor for measuring grip fo rce and hand position on a steering wheel for detecting drivers fatigue, to prevent road accidents. Driver fat igue detection using face recognition [3] has the main disadvantage of variation of face with age and

    the detection in color images are plagued by poor performance in the presence of scale variation, variation in skin color, co mple x backg rounds. The drowsiness warning system using artificia l intelligence [8] involves eye detection by image processing and artificia l techniques like fu zzy logic, but lack of proper light after sunset can cause problems in reading the images where in frared light source could be a better solution. A study on the HRV [14] provides accurate results for driver fatigue detection by obtaining minimu m number of sa mples to obtain valid results that requires a minimu m nu mber of beats. The proposed system avoids using of mobile phones, drunk and driving and has provision for driver fatigue wa rning, collision pre-safe activation, GSM/ GPS based accident/panic alert.

    This paper is organized as follows: Sect ion 1 is an introduction, section 2 exp lains the proposed system, section 3 illustrates design analysis of hardware prototype, section 4 shows the integration and development of software module, section 5 presents the experimental results and section 6 concludes and gives future enhancement.

  2. PROPOSED SYSTEM

    1. Mobile Baseband Monitor Unit

      Any activity in drivers mobile phone such as attending incoming calls, ma king outgoing calls and SMS texting will be monitored using the built in Mobile Baseband Sensor circuit wh ile the vehicle is running and it will be slowed down to a halt by applying the brakes automatica lly if such activity is detected.

      The driver can regain the vehicle control by simply pressing the brake pedal. The Accelerator Pedal Sensor and Bra ke Pedal Sensor along with DC Motor controlled wheel are used to demonstrate a running vehicle.

    2. Hands Free Auto-Reply SMS Mode

      The system has a GSM modem with a SIM card. The driver needs to activate call divert to this number before entering this mode. In this mode, upon receiving an incoming call wh ile d riv ing, the GSM mode m auto matica lly sends an SMS to the calling number with a fixed message indicating that the person is driving. The system has a dashboard

      graphics LCD that can show the calling nu mber. This ma kes the driver 100% hands free.

    3. Driver Fatigue Detection System

      Heart rate variab ility (HRV) and steering-wheel grip pressure are used to estimate the drivers fatigue level.

      Fig.1. Driver Fatigue Detection

      A digital pulse output Heart Rate Sensor measures HRV and an analog output Fle xi Force Pressure Sensor measures the steering-wheel grip force and the warning is issued with buzze r and LED lights. If the driver ignores this warning and continues to drive then the system will apply brakes automatically to slow down and halt the vehicle. Additionally the system can set for periodic wake-up call using keypad buttons and the dashboard graphics LCD. This feature provides a method for detecting the early signs of fatigue/drowsiness during driving.

    4. Drunk and Drive Prevention Mode

      The alcohol detection system involves the ignition circuit of the vehicle being controlled by interfacing a set of sensor, logic c ircu it and a microprocessor. It would instruct the driver to blow air into the sensor unit and checks the alcohol content present in the drivers breathe. If the value has crossed a certain limit the vehicle ignition will be locked wh ich prevents a drunken driver fro m starting the vehicle. An Alcohol Sensor unit is integrated into the system for this purpose.

      Fig.2. HRV of Relaxed Driver

      Fig.3. HRV of Fatigue Driver

    5. Collision Pre-Safe Activation Phase

      It uses pulse output SONAR to detect an imminent crash and has two warning stages in this project. If there is any collision detected by the SONAR, the system enters into first warning stage and produces audible and visual warnings. If first warning is ignored, and if the system pred icts the collision is unavoidable, then it tightens the seatbelt using the inbuilt Servo Motor mechanism provid ing seat belt protection, and automatic applicat ion of brakes to lessen severity of predicted crash.

    6. GPS and GSM Based Accident/Panic Alert System

    Fig.4. Accident Alert System

    During an emergency situation the driver can indicate his location to outside world using a simple panic button.By pressing this button, the driver can send an SMS about his current location information to a pre stored number. Also in the event of a cras h, the system senses that using 3-Axis Dig ital M EMS Accelero meter sensor and will automatica lly generate a simila r SMS to a pre stored number about the crash location information.

  3. DESIGN ANA LYSIS OF HA RDWA RE

    ARM Corte x-M3 (LPC1313) is a mic rocontroller for embedded applications featuring a high level of ntegration and low power consumption. It operates at CPU frequency range of 72 M Hz, containing 32KB of on chip flash me mo ry. It is of low cost and supports download limit of 128 KB.

    In any electric motor, operation is based on simple electro magnetism. A current-carrying conductor generates a magnetic fie ld. When it is then placed in an e xterna l magnetic fie ld, it e xperiences a force proportional to the current in the conductor and to the strength of the externa l magnetic fie ld.

    The internal configuration of a DC motor is designed to harness the magnetic interaction between a current -carry ing conductor and an external magnetic field to generate rotational motion. .In most common DC motors the external magnetic fie ld is produced by high-strength permanent magnets.

    Fig.5. Perfomance Comparison

    GSM is an open, digital cellular technology used for transmitting mobile voice and data services. GSM phones require a sma ll electronic ch ip, called a SIM card, to be inserted into a slot in the handset. GSM is an international roaming and 78% of world market uses GSM .

    Alcohol Sensors operate on the heat transfer princip le to

    measure mass air flow. They consist of micro bridge microe lectronic and micro electro mechanical system (MEM S) with temperature sensitive resistors deposited with thin films of platinu m and silicon nitride. The nitride M EMS sensing die is located in a precise and calculated air flow channel to provide repeatable flow response. A 3.3V dc operating voltage option and low power consumption allo w for use in battery-driven and other portable application.

    Fle xi force pressure sensor is a robust polymer thick film device that exhib its a decrease in resistance with increase in force applied to the surface of sensor. This force sensitivity is optimized for human touch control of electronic devices such as an automotive electronic device. Actuation force is as low as 0.1N and sensitivity range up to 10N. It is simple and easy to integrate.

    A buzze r or beeper is a signaling device, usually electronic, typically used in automobiles. It most commonly consists of a number of switches or sensors connected to a control unit. Initia lly this device was based on an electro mechanical system which was identical to an electric bell without the metal gong (which makes the ringing noise).

    Heart rate can be determined by measuring pulse rate. The pulse rate is the rate at which a series of pressure waves travel within an artery. Heart rate sensor measures the heart rate variability. Each time blood surges from aorta, the elastic walls of blood vessels expand and stretch, causing a pulse.

    Fig.6. Servomotor

    A servomotor (servo) is an electromechanica l device in which an electrical input determines the position of the armature of a motor. Servos are used extensively in robotics and radio-controlled cars, aircrafts and boats. The position of the armature is determined by the duty cycle of a periodic rectangular pulse train.

    Fig.7. Hardware Prototype

  4. DEVELOPM ENT OF SOFTWARE MODULE

    In this project, the program codes are written using embedded c language and it is developed using LPC Xpresso v3.6.3 development tool and simulated using Proteus Design Suite 8.0 platform.

    1. Proteus 8 Professional

      Proteus 8.0 represents over three years continuous development and includes improve ments to every area of the software suite. Major work on the application fra me work together with the introduction of a co mmon database provides a much smoother workflow for users while the rich new feature set saves time and effort in the design lifecycle.

      A demonstration version can be downloaded directly fro m the lab center website and you can then either watch getting started movies from the application home page or access the tutorial documentation for eva luation.

    2. LPC Xpresso

    LPC Xpresso is a new, low-cost development platform available fro m NXP. The software consists of an enhanced, Ec lipse-based IDE, a GNU C co mpiler, linke r, libra ries and an enhanced GDB debugger. The hardware consists of the LPC Xpresso development board which has an LPC -Link debug interface and an NXP LPC ARM based microcontroller target. LPC Xp resso is an end-to-end solution enabling e mbedded engineers to develop their applications fro m init ial evaluation to fina l production.

  5. EXPERIM ENTA L RESULTS

    The running of a vehicle can be understood with the help of a dc motor and motor driver c ircuit. This paper has an important feature of automatic bra ke system. So it is very essential to develop the accelerator and brake system along with the dc motor and driver circuit. The speed of the dc motor can be controlled with the help o f dc motor d rive that has been connected to the accelerator pedal sensor and brake pedal sensor. This module can be demonstrated with the help of nume ric simu lation.6.

    Fig.8. Screenshot of Simulation

  6. CONCLUSION AND FUTURE ENHANCEM ENT Thus the paper proposes an approach for effective

designing and user-friendly for driver vig ilance application especially targets at preventing accidents such as drunk and drive and collision pre-safe. It aims to design an advanced driver safety awareness and assistance system that will monitor the drive r and command the vehicle to take those

vital safety measures in order to overcome the serious problems.

In nume ric simulat ion the working of dc motor along with the function of brake pedal sensor and accelerator pedal sensor has been simulated and the corresponding output can be verified using numeric simu lation of Proteus 8 professional development software. The other modules will be demonstrated using hardware prototype. In future, a more advanced version of this system can also be developed according to the advancements in science and technology.

REFERENCES

  1. Federico Baronti, Francesco Lenzi, Roberto Roncella, Roberto Saletti Distributed Sensor For Steering Wheel Grip Force Measurement In Driver Fatigue Detection Electronics, Informatics T elecomunication University 16, 56122 Pisa, Italy.

  2. G. Scharenbroch, Safety vehicles using adaptive interface technology (SAVE-IT ) (Task 10):Technology review. Delphi electronics and safety systemsT ech. Rep,2005.

  3. Haisong Gu, Qiang Ji, Zhiwei Zhu: Active Facial Tracking for Fatigue Detection. Applications of Computer Vision, 2002 (WACV 2002).

  4. Hang-Bang Kang, Various Approaches for Driver and Driving Behavior Monitoring: A Review, Catholic Univ of Korea, ICCVW 14147905©2013 IEEE.

  5. J.Healey and R.Picard, Detecting stress during real-world driving tasks using physiological sensors, IEEE Trans.Intell.Transp.Syst.vol.6, no.2, June 2005.

  6. K. Rezaee, S.R. Alavi, M. Madanian, M. Rasegh Ghezelbash, H. Khavani, J. Haddadnia, Real-time Intelligent Alarm System of Driver Fatigue Based on Video Sequences,ICROM-978-1-4673-5809- 5©2013 IEEE.

  7. Mahesh M Bundele, ROC Analysis of a Fatigue Classifier for Vehicular Drivers, Department of Computer Science Babasaheb Naik College of Engineering Pusad-445215, (MS) India 978-1-4244-5164-7/10/$26.00

    ©2010 IEEE.

  8. Nidhi Sharma, V.K Banga Drowsiness Warning System Using Artificial Intelligence in World Academy Of Science, Engineering, Technology 43 2010.

  9. P. Jiang, J. Winkly, C.Zhao, P. Munnoch, G. Min, L.T. Yang, An Intelligent Informative Forwarder for Healthcare Bigdata System with Distributed Wearable Sensors, Systems Journal, ©2014 IEEE.

  10. R.Bittner, K.Hiana, L.Pousek, P.Smrka, P.Scherib and P.Vysoky, Detecting of Fatigue States of a Car Driver, ISMDA 2000, LNCS 1933, pp 260-274, 2000.

  11. Rajat Garg, Vikrant Gupta, ieeet Agrawal A Drowsy Driver Detection and Security System Department of Electronics and Communication VIT- University, Vellore- 600014, India {rajatgarg2006, vikrantgupta2006, vineetagraal2006}@ vit.ac.in 9781 -4244-3941- 6/09/$25.00 ©2009 IEEE.

  12. Rajiv Ranjan Singhi, Rahul Banetjee Multi-parametric Analysis of Sensorya Collected from Automotive Driver for Building a Safety- Critical Wearable System Electrical and Electronics Engineering Group, 2 Computer Science Birla Institute of Technology & Science Pilani, Rajasthan,978-1-4244- 6349-7/10/$26.00 ©2010 IEEE.

  13. Song Gao, Yin Zhou, Chen Chen, Research on the Awareness Training Software for Commercial Vehicle Drivers, CECNet @ Yichang, April 2010.

  14. Swapnil V. Deshmukh , Dipeeka P. Radake, Kapil N. Hande Driver Fatigue Detection Using Sensor Network in International Journal Of Engineering Science and Technology(IJEST ), NCICT Special Issue, February 2011.

  15. Y. Jun, X. Yu, An Innovative Non-intrusive Driver Assistance System for Vital Signal Monitoring, Biomedical and Health Informatics, 2168- 2194©2014 IEEE.

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