Introduction

This project is about video processing  methods and techniques to detect fire and smoke using surveillance cameras. An overview with practical and thorough details of the State of the art techniques and methods used in fire and smoke domain would be discussed. The improvement in the field of technology in term of computational power and imaging sensor has shifted this domain from traditional based approaches to video based fire and smoke detection for real time applications. The traditional based sensor detection techniques has lot of limitation in term of area, size, location,delay, environment i.e. (indoor / outdoor) and many more. These limitation has shifted focus from traditional based approaches towards visible range cameras, infrared based sensor cameras and time-of-flight cameras. 

Problem Statement

Smoke is a prelude to fire. Detection of smoke and fire using smoke sensor has some limitation i.e. heat of smoke detected by smoke sensor creates propagation delay i.e. the time required for the smoke to reach the sensor and secondly of smoke multidimensional propagation different number of sensors should be used to detect smoke in multiple directions. To overcome this vision based approach is used in which these limitations overcome and the second larger area could be cover using this approach. Fire and smoke location frameworks are a standout among the most essential parts in observation frameworks used to screen structures and condition as a component of an early cautioning instrument that reports ideally the begin of flame i.e. smoke or fire. Along these lines, as anyone might expect, the fire and smoke identification is from a few centuries the subject of research.

Project Objective

Detection of fire and smoke through video is the main area of research nowadays, with its importance to high intuitive, speed and its non jamming capability. This study suggests the fire and smoke detection methods based on video images in recent Video based fire and smoke detection technology is becoming the focal point of research with its advantages of high intuitive, speed and anti-jamming capability. This study suggests the fire and smoke detection methods based on video images in recent years. Through the review, it is clear to see that video based fire and smoke detection technology can be divided into two main areas: the characteristics detection of fire and smoke. 

Applications of Smoke and Fire Detection

This research would contribute for the betterment of our society and environment.  It can be implemented in different fields i.e. for the safety of industries, buildings, homes and for forest fire detection. Fire and smoke is essential and productive to mankind life, yet it likewise causes numerous ecological calamities, making prudent and natural harm, and in addition imperiling individuals' lives. In this way, fire and smoke location frameworks are a standout among the most imperative segments in reconnaissance frameworks used to screen structures and condition as a component of an early cautioning system that reports ideally the early nearness of flame. 

This Research would give a usage and execution assessment of constant based indoor fire and smoke discovery without sensor by video preparing method. The objective of flame and smoke recognition framework is to distinguish smoke and fires before it moves toward becoming wild by giving prior notice through sending message to the competent authority.

Expected Output/Results

This research suggests a better and robust technique for detection of smoke and fire. In this study different behavior of smoke and fire would be analyzed i.e. opaqueness, color, and diffusion. On the basis of different features of smoke and fire there classification would be performed.  

Dataset Used for Smoke and Fire Detection

1. Video Based Smoke and Fire Detection Dataset

• DynTex Dynamic Texture http://dyntex.univ-lr.fr/database.html

• Bilkent VisiFire Prof Dr. A. Enis. Bilkent Signal Processing Group. [Online]. http://signal.ee.bilkent.edu.tr/VisiFire/Demo/SampleClips.html 

• FIRESENSE Zenodo. (2017, July) FIRESENSE database of videos for flame and smoke detection. [Online]. https://zenodo.org/record/836749#.XF87T7nVLIU 

• Video Surveillance Online Repository (ViSOR) R. Cucchiara R. Vezzani. Video Surveillance online Repository. [Online]. http://imagelab.ing.unimore.it/visor/video_categories.asp 

• Furg Fire steffensbola. furg-fire-dataset. [Online]. https://github.com/steffensbola/furg-fire-dataset 

• KMU Fire & Smoke Database KMU CVPR Lab. KMU Fire & Smoke Database. [Online]. https://cvpr.kmu.ac.kr/Dataset/Dataset.htm

2. Image Based Smoke and Fire Detection Dataset

• Durham Collections Toby Breckon Durham University Collections. [Online]. https://collections.durham.ac.uk/collections/r1ww72bb497 

3. Video/Image Based Smoke and Fire Detection Dataset

• SKLFS USTC Qixing Zhang’s. [Online]. http://smoke.ustc.edu.cn/datasets.html 

• Phosphorik Ingemar Rask and Johannes Schmid. (2006) Rendering smoke and fire in real-time ETH Zurich. [Online]. https://cgl.ethz.ch/teaching/former/imagesynthesis_06/miniprojects/p3/index.html 

All rights reserved (c) 2019 Rafaqat Alam Khan

Unpublished work (c) 2019 Rafaqat Alam Khan