Machine Learning-based Surveillance System for Detection of Bike Riders without Helmets and Triple Rides

Project Code :TEMBMA2733

Objective

A machine learning based surveillance system which can able to detect the persons without helmet and/or people who are going on a triple rides

Abstract

Motorcycle accidents have been rapidly growing through the years in many countries. In India more than 37 million people use two wheelers. Therefore, it is necessary to develop a system for automatic detection of helmet wearing and triple rides for road safety. Therefore, a custom object detection model is created using a Machine learning based algorithm which can detect Motorcycle riders. On the detection of a Helmetless rider and triple rides, if the bike riders didn’t wear helmets and if they are going with triple rides then at that time the License Plate is extracted and the license Plate number is recognized using an Optical Character Recognizer. This Application can be implemented in real-time using a Webcam.

In this project, we can classify the image which consists of three riders using a deep learning process. In this, a CNN based architecture is designed to classify the image. The process of this project is first we train the image taken from the webcam. Then by considering input from the webcam the network will generate the output based on the trained data. This will get an accuracy of 70 %. 

Keywords: Raspberry Pi, MATLAB, WSN, Zigbee, IOT.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Hardware requirements:

  • Raspberry Pi
  • Micro SD card
  • PC
  • 5V Adapter
  • Web cam
  • ZIGBEE transmitter and receiver

Software requirements:

  • Python IDE
  • NOOBS software
  • VNC viewer
  • MATLAB
  • Fritzing
  • Third Party server

Learning Outcomes

  • Raspberry pi Architecture
  • How to install NOOBS Software
  • Basic coding in python
  • Introduction to Serial communication
  • Working of zigbee
  • How to interface zigbee with raspberry pi?
  • Working of 16x2 LCD
  • How to interface 16x2 LCD with Raspberry Pi?
  • Introduction to IOT
  • IOT Architecture and its scope
  • How to send information from Raspberry Pi to an IOT platform?
  • About Project Development Life Cycle:
    • Planning and Requirement Gathering( software’s, Tools, Hardware components, etc.,)
    • Schematic preparation 
    • Code development and debugging
    • Hardware development and debugging
    • Development of the Project and  Output testing
  • Practical exposure to:
    • Hardware and software tools.
    • Solution providing for real time problems.
    • Working with team/ individual.
    • Work on Creative ideas.
  • Project development Skills
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginary skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills

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