Deep Learning-Based Fire Detection System

@article{1707989,
      author = {Utkarsha Sanjay Pandharkar, Dipali Adhyapak},
      title = {Deep Learning-Based Fire Detection System},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {10},
      pages = {933-939},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1707989.pdf},
      abstract = {In emergency situations like fire accidents fire causes environmental disaster, economic losses and deep damages to humans. To detect fire earlier and to avoid damages caused by fire we have built a project which is deep learning-based fire detection system. With the help of deep learning algorithms such as CNN we have developed this fire detection system. In this project we have introduced a system which is trained by using images as a dataset and with the help of CNN algorithm module is trained to detect fire from provided video. Input is provided in video format the input video is converted into images with the help of CNN layers. The trained module detects fire which is trained and working with the help of coding. The deep learning-based fire detection gives output in text format as ?fire detected? and alert is given to the nearest fire station or owner of the system is alerted by sending messages. This system results into early and accurate detection of fire through video or surveillance camera. This is efficient to early detection and fire is avoided by spreading. With this approach, fire detection systems are likely to become far more precise and effective.},
      keywords = {Automated Fire Detection, Convolutional Neural Network (CNN), Early Fire Detection, Fire Prevention, Pattern Recognition, Neural Networks},
      month = {April},
  }