Master’s students in Data Science and Big Data at Hassan II University in Casablanca have developed an AI-powered system that predicts wildfire risks and supports smarter agricultural management.
Unveiled at the “AI for All–ESSOR” event, the project uses historical weather data and real-time satellite imagery from NASA’s FIRMS to forecast wildfires. It applies machine learning algorithms such as logistic regression to issue early warnings and help limit environmental and agricultural damage.
Students Salma Salama, Salah Eddine Khouldouni, and Nouhail Hajjaoui designed the system under the supervision of professors Habib Ben Lemhar, Oussama Kaich, and Zakaria Fakir. Future versions aim to integrate IoT sensors for real-time ground data collection.
Beyond wildfire alerts, the system offers AI solutions for crop selection, livestock feed optimization, and yield forecasting. Using algorithms like random forest and LSTM neural networks, the tool helps farmers improve productivity, reduce costs, and prepare for climate impacts.
The project highlights the expanding role of AI in sustainable agriculture and disaster prevention, especially in climate-vulnerable regions like Morocco.
