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HVS-4327. Image Processing Based Fire Detection Using Raspberry pi.
HVS-4327. Image Processing Based Fire Detection Using Raspberry pi.
HVS-4327. Image Processing Based Fire Detection Using Raspberry pi.

HVS-4327. Image Processing Based Fire Detection Using Raspberry pi.

₹13,500.00

This system uses the power of the Raspberry Pi processing system to perform real-time image processing algorithms that analyze video footage looking for signs of fire.

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Image Processing based fire detection using Raspberry Pi is an emerging technology that has the potential to revolutionize fire detection and prevention systems. This system uses the power of the Raspberry Pi processing system to perform real-time image processing algorithms that analyze video footage looking for signs of fire. By comparing successive frames of video, it is possible to identify changes in heat, light, and movement that are indicative of a fire. The proposed system involves capturing an image of the environment using a camera and processing it using the OpenCV computer vision library running on Raspberry Pi. The system is designed to be an affordable, low-power, and low-maintenance solution for fire detection. The Raspberry Pi platform offers a low-cost and versatile solution for real-time image processing, and the use of OpenCV algorithms allows the system to learn from experience and adapt to different environments. The proposed system can be integrated with existing fire detection and alarm systems to provide early warnings and help to minimize damage caused by fires.      

Objectives:  

1. To develop an image processing-based fire detection system using a Raspberry Pi and camera module.

2. To capture and analyze real-time video frames using the OpenCV computer vision library.

3. To detect fire by identifying flame colors, brightness variations, and changes in successive video frames.

4. To provide early fire warnings by detecting potential fire incidents in the monitored environment.

5. To reduce false alarms by distinguishing fire-like patterns from normal environmental conditions.

6. To develop a low-cost, low-power, and reliable fire detection system for continuous monitoring.

7. To integrate the proposed system with an alarm or notification system for timely alerts during fire emergencies.

8. To minimize property damage and improve safety through early fire detection and rapid response.      

The major building blocks of this project are:
  • Power supply.
  • Raspberry pi3.
  • SD card.
  • Pi camera.
  • Buzzer.
       

Software’s used in the project:
  1. Python Programming.
  2. Raspbian OS.
  3. OpenCV Image processing.
  4. Express SCH for Circuit design.
       

   

video:

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