Throughout history, humans and wolves have had a complex and conflictive love-hate relationship. On the one hand, wolves are often blamed for damage or attacks on livestock, generating tension with farmers and landowners, while on the other hand the dog, their domesticated relative, is culturally considered a member of the family. Due to attacks on livestock, tensions with rural populations have increased over the years. Unfortunately, the Autonomous Community of Castilla y León is one of the areas of the country most affected by wolf attacks, with Ávila being one of the areas that accumulates the most damage. The objectives of this line of research are to use artificial intelligence algorithms to model and study the impact of the wolf in the province of Ávila. Using spatial data, statistical approaches of Geographic Information Systems (GIS) and computational learning algorithms, we hope to present a new perspective for the study of wolf activities and their attacks on local livestock in the peninsula.the advantages of artificial intelligence are multiple. These algorithms are able to predict with high accuracy where and when a new attack is most likely to occur. Similarly, additional research can highlight which livestock are most likely to be attacked. This data can benefit local livestock communities, helping to protect their animals and alleviate the stresses generated by attacks, which may in turn help to better protect the wolf from extinction.
