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HVS-3338. Machine learning based surveillance system for detection of bike riders.
HVS-3338. Machine learning based surveillance system for detection of bike riders.
HVS-3338. Machine learning based surveillance system for detection of bike riders.
HVS-3338. Machine learning based surveillance system for detection of bike riders.

HVS-3338. Machine learning based surveillance system for detection of bike riders.

₹12,500.00

Automation is the most frequently spelled term in the field of electronics. The hunger for automation brought many revolutions in the existing technologies. This project makes use of an onboard computer, which is commonly termed as Raspberry Pi processor. It acts as heart of the project. This onboard computer can efficiently communicate with the output and input modules which are being used. The Raspberry Pi is a credit-card-sized single-board computer developed in the UK by the Raspberry Pi Foundation.

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Automation is the most frequently spelled term in the field of electronics. The hunger for automation brought many revolutions in the existing technologies. This project makes use of an onboard computer, which is commonly termed as Raspberry Pi processor. It acts as heart of the project. This onboard computer can efficiently communicate with the output and input modules which are being used. The Raspberry Pi is a credit-card-sized single-board computer developed in the UK by the Raspberry Pi Foundation. The Raspberry Pi has a Broadcom BCM2835 system on a chip (SoC), which includes an ARM1176JZF-S 700 MHz processor, Video Core IV GPU, and was originally shipped with 256 megabytes of RAM, later upgraded to 512 MB. It does not include a built-in hard disk or solid-state drive, but uses an SD card for booting and long-term storage. The main aim of this project is to design a surveillance system for bike riders using raspberry pi3, pi camera. This system using CNN machine learning and open CV image processing is used to detect the helmet of bike rider and triple ride will be display on LCD module. The main controlling device of the project is raspberry pi3 processor. Pi camera and LCD module is interfaced to the raspberry pi processor. When the user switch on the surveillance system, it will start live streaming and capture the image, if the biker rider doesn’t wear the helmet and if three people on a bike using machine learning and sending these captured images into the mail.      

The objectives of the project are:
  1. Capturing of Person images using pi camera.
  2. Captured image is sent through email.
  3. Using machine learning CNN and open CV image processing to detect the triple ride and helmet.
  4. To achieve this task using Raspberry Pi3 processor.
  The project provides learning’s on the following advancements:
  1. Learn about Image processing and IOT Technology.
  2. Raspberry pi working and programming.
  3. Pi camera interfacing to the raspberry pi.
  The major building blocks of this project are:
  • Power supply.
  • Raspberry pi3.
  • SD card.
  • Pi camera.
  • LCD display.
  Software’s used:  
  • Python language.
  • OpenCV image processing.
  • Linux OS.
  • CNN machine learning.
   

 

Block Diagram:

video:

 

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