A DYNAMIC ECHO STRATEGY TO KEEP AN EYE ON DRIVING

M Veera Manikanth, K Sangeet Kumar

Abstract


In this project we're using LPC2148 is primary controller. It is associated with ARM7 architecture. GSM modem is linked to controller through serial interface. IR sensor, alcohol sensor (MQ3), Heartbeat sensors are linked to controller through digital I/O lines. Motor also associated with H-bridge or relay. Assume motor as engine. To begin engine user needs to send SMS from mobile. Accidents mainly occur because of driver negligence. The primary aim would be to provide awareness and safety mechanism for that driver. Primary reason of the accident is a result of drinking and abnormal pulse rate of driving person. Additionally for this thievery recognition, home security system and person level identification is decided. The primary utilization of human level identification technique is to recognize the individual within the vehicle. Passive infrared sensor can be used this detects a person’s level. Within this paper alcohol recognition and heartbeat monitoring system, person level identification system, accident alert, thievery recognition and mobile free auto reply technique is accustomed to avoid any sort of accident. Their simulation output is observed by LABVIEW or MATLAB and also the hardware module is acquired.  Password authentication, calls divert method, pulse level mechanism is processed. Both ways can be used to rectify the negligence from the driver and immediate intimation strategy is produced by utilization of GSM technology. Hardware module for hybrid driver safety product is acquired with three methods namely alcohol recognition, heartbeat monitoring system, person level identification method, eye blink sensor and thievery identification.


Keywords


MQ3 Sensor; IR Sensor; Heart Rate Monitoring System; Passive Infrared Sensor; Password Authentication And Auto Reply SMS GSM;

References


Chin Teng Lin, 2014‘Wireless and Wearable EEG System for Evaluating Driver Vigilance’, IEEE Transactions on biomedical circuits and systems, Vol.15, No.8, pp.230-255.

Chi Zhang, Hong Wang and Rongrong Fu,‘Automated Detection of Driver Fatigue Based on Entropy and Complexity Measures’,IEEE Transaction on intelligent transportation systems.

AartsL. and Schagen, (2005)Driving Speed and the risk of road crashes’, Accident Analysis and Prevention.

Martinez F,Toh, Cano J.C, Calafate C. and Manzoni P, 2010,‘Emergency services in future intelligent transportation systems based on vehicular communication networks’, IEEE Intelligent Transportation Systems Magazine.

Elvi R, Christensen and Amundsen, 2004, ‘Speed and road accidents An evaluation of the Power Model’, Institute of Transport Economics, Oslo.


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