DNA Fragmentation Pattern Recognition using Neural Networks

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Description

DNA Fragmentation Pattern Recognition using Neural Networks

The main objective of this project is to safety and security with an autonomous region-based automatic car system.

ABSTRACT:

A new approach toward automobile safety and security with an autonomous region-based automatic car system is proposed in this concept. We propose three distinct but closely related concepts viz. a Drowsy Driver Detection system and a traffic detection system with external vehicle intrusion avoidance based concept. In recent times automobile fatigue-related crashes have really magnified. In order to minimize these issues, we have incorporated a driver alert system by monitoring both the driver’s eyes as well as sensing as well as the driver’s situation based on a local environment recognition-based OpenCV system is proposed. DNA Fragmentation Pattern Recognition using Neural Networks


DNA Fragmentation Pattern Recognition using Neural Networks

EXISTING SYSTEM

IR sensor placed on the eye for fatigue detection the problem with the system is having user aiding in complex with placing sensor over the eye directly. The system GPS-based location sharing services when an accident happened with the GSM module. The status of the vehicle is analyzed when the vehicle accident is detected. DNA Fragmentation Pattern Recognition using Neural Networks


DRAWBACKS

  • Performance depends on the compiler
  • Poor code density
  • RISC has a fixed-size instruction format
  • A small number of instructions

PROPOSED METHOD:

  • Image processing is applied for the detection of eye detection and region classification
  • Driver Assistance system with camera
  • External vehicle availability detection
  • Human detection-based attention speech assistance

Advantage

  • Driver Assistance system with cameras focusing user hash free user assistance provided.
  • M2M communication systems.
  • Alcohol Detection System in Cars? provides an automatic safety system for cars and other vehicles as well.

HARDWARE TOOLS:

  • Raspberry pi
  • Web Camera
  • Ultrasonic SENSOR
  • Seatbelt Sensor
  • Alcohol Sensor
  • Sd card

SOFTWARE TOOLS:

  • Raspberry pi OS: Raspbian stretch
  • Programming Platform: python 3 IDLE
  • Programing language: python 3
  • Library: OpenCV

Technology:

  1. NOT
  2. OPEN CV

REFERENCES:

[1] H. Cheng, N. Zheng, X. Zhang, J. Qin, and H. V. D. Wetering,?Interactive road situation analysis for driver assistance and safety warning systems: Framework and algorithms,? IEEE Trans. Intell. Transp. Syst., vol. 8, no. 1, pp. 157? 167, Mar. 2007.

[2] L. Li, J. Song, F.-Y. Wang, W. Niehsen, and N.-N. Zheng,?IVS 05: New developments and research trends for intelligent vehicles,? IEEE Intell. Syst., vol. 20, no. 4, pp. 10?14, Jul. 2005.

[3] R. Labayrade, J. Douret, J. Laneurit, and R. Chapuis, ?A reliable and robust lane detection system based on the parallel use of three algorithms for driving safety assistance,? IEICE Trans. Inf. Syst., vol. 89-D, no. 7, pp. 2092? 2100, 2006.

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