Using AI for agriculture crops prediction and crops diseases prediction - Chouikh, Anfal; Bouakkaz, Mustapha, Directeur de thèse (Laghouat : Université Amar Telidji - Département d'informatique, 2024)
In recent years, the significant effects of climate change on agriculture have become increasingly apparent. Rising temperatures, erratic weather patterns, and shifting climatic conditions have introduced challenges for agriculture which threaten crop yields due to altered rainfall patterns, heat stress, and increased occurrences of extreme weather events such as droughts, floods, and storms. Such disruptions not only impact crop productivity but also pose substantial risks to global food security and livelihoods,to address these challenges, our work focuses on leveraging AI and machine learning techniques for two critical applications: predicting suitable crops and detecting plant diseases. By using these advanced technologies, we aim to assist farmers in making well-informed decisions about crop selection, optimal planting times. Additionally, detecting plant diseases early can help mitigate their impact, ensuring more resilient and sustainable food production in the face of climate change.