Advanced Driver Assistance System – ADAS using Raspberry Pi and OpenCV

SKU: PAN_EMB_002 Categories: , Tag:
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Description

OBJECTIVE

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 time’s 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 situation-based local environment recognition-based AI system is proposed.


EXISTING SYSTEM

IR sensor placing on the eye for fatigue detection the problem with the system it 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 detected


DRAWBACKS

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

PROPOSED METHOD:

  • ML 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 assistancePANEMB02 02

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.

BLOCK DIAGRAM:

adas


HARDWARE TOOLS:

  • Raspberry pi
  • Web Camera
  • Ultrasonic SENSOR
  • Seatbelt Sensor
  • Alcohol Sensor
  • Main Processor: 2GHz
  • Ram : 2 GB(min)
  • Hard Disk: 80 GB

SOFTWARE TOOLS:

  • Windows OS
  • ?Python
  • Java language
  • JDK 1.7
  • MySQL
  • NetBeans IDE 7.1.2
  • IDLE
  • OPEN CV

Technology:

  1. NOT
  2. OPEN CV
  3. DATA ANALYSIS

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