Leveraging AI for Natural Disaster Management : Takeaways From The Moroccan Earthquake
Léna Néhale Ezzine ⋅ Yoshua Bengio ⋅ Ayoub Atanane ⋅ Ghait Boukachab ⋅ Oussama Boussif ⋅ ⋅ Yassine Yaakoubi ⋅ Loubna Benabbou ⋅ Léonard Boussioux ⋅ Peetak Mitra ⋅ Alexandre Jacquillat ⋅ Dick Den Hertog ⋅ Mehdi Bennis ⋅ Ilham EL BOULOUMI ⋅ Ayoub Loudyi ⋅ Aymane El Firdoussi ⋅ Achraf Sbai ⋅ SANAE ATTAK ⋅ Kaoutar Lakdim ⋅ Yassine Squalli Houssaini ⋅ Firdawse Guerbouzi ⋅ Chaimae Biyaye ⋅ Khadija Bayoud ⋅ Ikram Belmadani ⋅ Charles Bricout ⋅ Reyad OUAHI ⋅ Alex Maggioni ⋅ B.V. Alaka ⋅ Kiruthika Subramani ⋅ Tariq Daouda ⋅ Redouane Lguensat ⋅ Khaoula Chehbouni ⋅ Afaf Taik ⋅ Kanishk Jain ⋅ Hamza Ghernati ⋅ Lamia Salhi ⋅ Laila Salhi ⋅ Jules Lambert ⋅ Jeremy Pinto ⋅ Victor Schmidt ⋅ Zhor KHADIR ⋅ Nouamane Tazi ⋅ Yuyan Chen ⋅ Nikhil Reddy Pottanigari ⋅ Santhoshi Ravichandran ⋅ Ashwini Rajaram ⋅ Alex Hernandez-Garcia ⋅ Reda Snaiki ⋅ Laurent Barcelo ⋅ Salim Chemlal ⋅ Omar El Housni ⋅ AJ Dhimine ⋅ Abderrahim Khalifa ⋅
2023 Oral
in
Workshop: 6th Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response
in
Workshop: 6th Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response
Abstract
The devastating 6.8-magnitude earthquake in Al Haouz, Morocco in 2023 prompted critical reflections on global disaster management strategies, resulting in a post-disaster hackathon, using artificial intelligence (AI) to improve disaster preparedness, response, and recovery. This paper provides (i) a comprehensive literature review, (ii) an overview of winning projects, (iii) key insights and challenges, namely real-time open-source data, data scarcity, and interdisciplinary collaboration barriers, and (iv) a community-call for further action.
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