Exploring the Potential of Machine Learning Approaches in Fire Detection: A Case Study in Marmara and Kocaeli Region

Fires pose a risk that seriously threatens our daily lives. Nowadays, early fire detection has become important to minimize the damage caused by fires. In this paper, the performances of machine learning approaches in fire detection have been examined using MODIS and VIIRS remote sensing datasets. The experiments have been carried out in Kocaeli and Marmara region. Experimental results show that learning-based approaches can enable classification performance up to 97% in fire detection.

• Publication year

  2024

• Venue

  2024 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)

• Publication date

  2024-05-23

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/HORA61326.2024.10550458
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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