MEMS Accelerometer And GPS Tracking For Accidental Monitoring Of Vehicles

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MEMS Accelerometer And GPS Tracking For Accidental Monitoring Of Vehicles

SKU: MEMS Accelerometer, GPS Tracking-Accidental Monitoring Category:

Description

ABSTRACT

In a critical situation many vehicles faces accident, due to this lot of person lost their lives. Some people can be saved at that time, but because of lack of information, time and place it may not be possible. Our project will provide an optimum solution to that draw back.

An accelerometer can be used in a car alarm application; Dangerous driving can be detected with an accelerometer. It can be used as a crash recorder of the vehicle movements before, during and after a crash. With signals from an accelerometer, a severe accident can be recognized.

According to this project when a vehicle met with an accident immediately the vehicle number and persons contact number will be transferred to police control room or a rescue team. So the police can immediately trace the location from where the message came. Then after conforming the location necessary action will be taken.

In second application on an uncertain situation many of vehicle that has center locking system, Such as door locking system faces many problem due to automatic locking system. At that situation there is no way to open the lock. Our project will provide a suitable solution for this situation. This can be done by using wireless or GSM Technology.

PROBLEM STATEMENT

  • Post-Accident Detection Systems.
  • Lack of Intelligence in the detection systems.
  • Fails to track the collision and pre-damage status.

PROPOSED SYSTEM

  • Pre accident detection
  • Tracking of collision
  • Intelligent system

BLOCK DIAGRAM

          MEMS_Accelerometer_And_GPS_Tracking_For_Accidental_Monitoring_Of_Vehicles

WORKING AND OPERATION 

Vehicle section is the most important section of this entire project. The vehicle section includes

  • Microcontroller unit
  • MEMS
  • GPS
  • GSM/GPRS
  • Serial communication
  • Indicator
  • Amplifying circuit

The MCU controls the entire operation of this section.ARM (Automatic RISC Machine) is the controller that we are using in this ambulance section. The sensors fixed vehicle collects the vibration to the amplifying circuit. The amplifying circuit will amplify the obtaining vibrations and given to the MEMS. MEMS are able to store the factors such as vibration, speed, humidity, temperature etc. It is connected with the accelerometer hence if the speed of the vehicle is at a high rate it will give a warning alarm (indicator) to the driver. If the driver continues the driving with the same speed and accident occurs, the MEMS can detect weather it is a linear (only x axis) or nonlinear (x, y, z directions). Also it can store all the data of the vehicle with the cause of accident.

The GPS and GSM are connected to this system. The communication for the GPS and GSM can be done through serial communication. The serial communication creates an interface through which it covert CMOS to TTL logic. The GPS is used to locate the position (longitude and latitude) of the vehicle.

The GSM in the black box can sent a message to the ambulance section and GSM of the family member. The message includes the location, time and other details regarding the accident. This message helps the ambulance section and the family member about the accident and ambulance section can collect the patient from the accident spot to the hospital.The indicator for warning alarm can be done with the help of buzzer. This section has a direct power supply for entire unit will get from battery fixed in the vehicle. The power supply can be given directly to the microcontroller unit since it controls the entire unit.

HARDWARE REQUIREMENTS

  • ARM LPC 2148
  • MEMS  Sensor
  • Vibration Sensor
  • GSM
  • GPS                                                                            

SOFTWARE REQUIREMENTS

  • Keil C compiler
  • Orcad circuit Design
  • Programming Language: Embedded C
  • Flash Magic

APPLICATIONS

  • Anti-theft systems
  • Crash recorders
  • Event recorders
  • Dead reckoning

CONCLUSION

In a critical situation many vehicles faces accident, due to this lot of person lost their lives. Some people can be saved at that time, but because of lack of information, time and place it may not be possible. Using the vehicle black box concept the accident happened can be detected with the help of GPS and GSM systems. The victim can be admitted in the hospital by the ambulance section as soon as possible by controlling the traffic signals. Therefore the black box concept can provide road safety hence its creates a safe driving for the driver and give security for the life and property of the public.

REFERENCE

[1]. BergasaL. M, J. Nuevo, M. A. Sotelo, R. Barea, and M. E. Lopez,(Mar. 2006) “Realtime system for monitoring driver vigilance,”IEEE Trans. Intell. Transp.Syst., vol. 7, no. 1, pp. 63–77,
[2]. Chung-ChengChiu, Min-YuKu, Hung-Tsung, Chen Nat,(June  2007) “Motorcycle Detection and Tracking System with Occlusion Segmentation,” Image Analysis for Multimedia Interactive Services.  Santorini, vol. 2,  pp. 32-32,
[3]. Devi M. S and P. R. Bajaj,(Jul. 2008) “Driver fatigue detection based on eye tracking,” in Proc. IEEE ICETET, Nagpur, Maharashtra, India,pp. 649–652.
[4]. Gang Xiong,Senior Member, IEEE, XisongDong,Member, IEEE, Dong Fan,FenghuaZhu,Member, IEEE, Kunfeng Wang, and YishengLv, (march 2013)“Parallel Traffic Management System and ItsApplication to the 2010 Asian Games,”IEEE Trans.,vol. 14, no. 1,
[5]. Lu .M, W. chen,  X. Shen, H.C. Lam and J. Liu,(August 2007)  “Positioning and tracking construction vehicle in highly dense urban areas and building construction sites,”  Automation in  Construction, vol. 16,  issue5.pp.647-656,
[6]. Manuel Fogue,PiedadGarrido,Francisco J.Martinez, Juan-Carlos Cano,Carlos T. Calafate, and Pietro Manzoni,(Sep 2012)”Auttomatic Accident Detection,”IEEE Vehicular Tech. Magazine,
[7]. Rigas.G, C. D. Katsis, P. Bougia, and D. I. Fotiadis,(Jun. 2008) “A reasoning based framework for car driver’s stress prediction,” inProc. Med. Control Autom. Conf., Ajaccio, France, pp. 627–632

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Additional information

Weight 1.000000 kg

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