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Exposure of fire in jungle through computer vision

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Abstract:

Fire detects using image processing. Here in this project I’m using open CV and python for fire detection. I created a HAAR Cascade Classifier for fire detection using Open CV. It has trainer and detector for train our own cascade classifier, HAAR Cascade is used to detect object for which it has been trained. Lots of positive and negative image samples are need to train classifier. Training of cascade classifier is complex and time consuming process.

 

Introduction:

With the development of economy, the number of large high buildings is increasing. Generally, for the complex application, high load of fire and intensive staff, major property damage and heavy casualties will be easily caused if fire happens in these places, and has a bad social impact. So difficult technical problems of fire detection and alarm are urgently be solved to obtain more valuable time for extinguish and evacuation. In large rooms and high buildings, conventional fire detectors can hardly detect characteristic parameters of fire like smoke, temperature, vapor and flame in the very early time of fire, and cannot meet the demand of early fire detection in these places. Compared to conventional fire detectors, video fire detectors which have many advantages, such as fast response, long distance of detection, large protection area et al, are particularly applicable to large rooms and high buildings. But most of current methods for video fire detection have high rates of false alarms. Researchers all over the world have done a lot of work on this new technique.

 

Existing Method:

  • Arduino Controller
  • Gas Sensor

 

 Disadvantages:

  • More cost is there to implement
  • Hardware connection may loose sometimes

 

Proposed Method:

  • Python libraries
  • Back ground subtraction method
  • Vedio Streaming
  • Optical fiber
  • Fire Algorithm

 

Advantages:

  • No need of any hardware
  • Sound alert by pc

 

 Applications:

  • Military application
  • Home appliances application
  • Shopping malls are heavy loaded go downs

 

 Block Diagram:

Real Time Fire Detection

 

Software Requirements:

  • PYTHON IDLE
  • OPEN CV MODULES

 

Hardware Requirements:

  • WINDOWS OS PC
  • MINIMUM 2GB RAM
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  • Price
    Free
  • Instructor pantech team
  • Duration 15 Hrs
  • Enrolled 1 student
  • Access 3 Months

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