Final Year Engineering Projects

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ADVANCED OFFICE AUTOMATION SYSTEM USING GSM AND MICROCONTROLLER
ADVANCED OFFICE AUTOMATION SYSTEM USING GSM A

java,embedded c,89x51 family chip


Anti Forensics
Anti Forensics

android application,bootstrap,mysql serv


ANDROID BASED HOME AUTOMATION
ANDROID BASED HOME AUTOMATION

android,java,embedded c,89x51 chip,webba


MASTER SLAVE BASED PWM(PULSE WIDTH MODULATION) OF DC AND AC MOTORS
MASTER SLAVE BASED PWM(PULSE WIDTH MODULATION

pwm,embedded c,89x5x microcontroller

Friend Finder
Friend Finder

android application,mysql server


ANDROID BASED HOME AUTOMATION
ANDROID BASED HOME AUTOMATION

android,java,embedded c,89x51 chip,webba


Domestic Servers
Domestic Servers

android application,mysql server


MASTER SLAVE BASED PWM(PULSE WIDTH MODULATION) OF DC AND AC MOTORS
MASTER SLAVE BASED PWM(PULSE WIDTH MODULATION

pwm,embedded c,89x5x microcontroller

DROWSY DRIVER DETECTION SYSTEM


Project Platform : EMBEDDED C 89X51 CHIP FAMILY


Languages Used : EMBEDDED C


Project Cost : 16000


Description

Driver drowsiness is a major, though elusive, cause of traffic crashes. Scientific support for the feasibility of this countermeasure concept is provided by research showing that:

Drowsy drivers typically do not “drop off’ instantaneously. Instead, there is a Preceding period of measurable performance decrement with associated Psycho physiological   signs. Drowsiness can be detected with reasonable accuracy using driving performance Measures such as “drift-and-jerk” steering and fluctuations in vehicle lateral lane Position.

The use of direct, unobtrusive driver psycho physiological monitoring (e.g., of eye Closure) could potentially enhance drowsiness detection significantly. The use of secondary/subsidiary auditory tasks (e.g., auditory recognition tasks Presented to the driver via recorded voice) could further enhance detection accuracy.

The envisioned vehicle-based driver drowsiness detection system would continuously and unobtrusively monitor driver performance (and “micro-performance” such as minute steering Movements) and driver psycho physiological status (in particular eye closure).The system May be programmed to provide an immediate warning signal when drowsiness is detected with high certainty, or, alternatively, to present a verbal secondary task via recorded voice as a second-stage probe of driver status in situations of possible drowsiness. The key requirements and R&D challenges for a successful countermeasure include low Countermeasure cost, true unobtrusiveness, an acceptably-low false alarm rate, non-disruption of the primary driving task, compatibility and synergy with other IVHS crash avoidance Counter measures, and a warning strategy that truly sustains driver wakefulness or convinces him/her to stop for rest. The IR transmitter is used to transmit the infrared rays in our eye. The IR receiver is used to receive the reflected infrared rays of eye. If the eye is closed means the output of IR receiver is high otherwise the IR receiver output is low. This to know the eye is closing or opening position.  This output is give to logic circuit to indicate the alarm. This project involves controlling accident due to unconscious through Eye blink. Here one eye blink sensor is fixed in vehicle where if anybody looses conscious and indicate through alarm.

 

Description :-

This project involves measure and controls the eye blink using IR sensor. The IR transmitter is used to transmit the infrared rays in our eye. The IR receiver is used to receive the reflected infrared rays of eye. If the eye is closed means the output of IR receiver is high otherwise the IR receiver output is low. This to know the eye is closing or opening position.  This output is give to logic circuit to indicate the alarm. This project involves controlling accident due to unconscious through Eye blink. Here one eye blink sensor is fixed in vehicle where if anybody looses conscious and indicate through alarm. A car simulator study was designed to collect physiological data for validation of this technology. Methodology for analysis of physiological data, independent assessment of driver drowsiness and development of drowsiness detection algorithm by means of sequential fitting and selection of regression models is presented.

 

 System Model

 

The block diagram depicts the total blue print of the proposed project. The total essence and the functioning of the project is represented in a single block diagram. The block diagram mainly consists of 2 parts. They include

  • Transmitter circuit  
  • Receiver circuit

 

Drowsiness Detection System

SnapShots :-

Driver Sleepy Detection  Drowsiness Prevention System

Vehicle Accident PreventiuonSystem  Vehicle Safety System