Download PDFOpen PDF in browser

Natural Disasters and Artificial Intelligence

EasyChair Preprint no. 10634

6 pagesDate: July 29, 2023


    Natural disasters such as floods, earthquakes, and wildfires can cause significant damage and loss of life. In recent years, advances in artificial intelligence (AI) have offered new opportunities for improving disaster response and mitigation. This paper provides an overview of the potential of AI in natural disasters, highlighting its applications in early warning systems, damage assessment, and resource allocation. The paper also discusses the challenges and limitations of AI in natural disasters, such as the need for reliable data, the potential for biases in AI algorithms, and the ethical concerns associated with the use of AI in sensitive contexts. The paper presents several examples of AI-based approaches to natural disasters, including machine learning, deep learning, and natural language processing. The paper concludes by emphasizing the need for continued research and development in the field of natural disasters and AI, and the importance of addressing the challenges and ethical concerns associated with the use of AI in disaster response.

Keyphrases: Artificial Intelligence, machine learning, natural disasters

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Mostafa Hesham},
  title = {Natural Disasters and Artificial Intelligence},
  howpublished = {EasyChair Preprint no. 10634},

  year = {EasyChair, 2023}}
Download PDFOpen PDF in browser