Utilizing Artificial Intelligence Techniques to Determine the Predominant Breed of Stray Dogs in the Moroccan Region, with a Focus on the Oujda Area

This research aims to develop a cost-effective method to study the factors influencing canine overpopulation in urban areas using the Dog Scanner application. The Dog Scanner application is a program for iOS or Android devices that quickly processes photos or videos of dogs using an approved database of dog breeds from the International Cynology Federation (ICF). This advanced mechanism is crucial in the methodology that uses sophisticated image processing technology and artificial intelligence to track the growth of the stray dog population by analyzing their lineage, even if they are of mixed descent. Urban life in Africa is characterized by insufficient resources, inadequate treatment within the current legislative framework, and a lack of veterinary programs such as sterilization, castration, and vaccination. This has led to newborns roaming freely in the streets, contributing to the spread of diseases. To promote a harmonious coexistence between dogs and humans and create a coherent society, it is critical to study the ecological dynamics of canine populations and categorize their breeds. In Oujda, Morocco, the rising population of stray dogs is a significant concern for local residents. For effective problem-solving, conducting thorough data analyses is essential to pinpointing the cause of canine overpopulation. These results can identify the responsible factors, determine specific areas of contribution, and develop a cost-effective and efficient management strategy to solve the problem. The methodology employs a sophisticated mechanism to analyze the significant increase in the population of stray dogs based on their lineage, even if they are of mixed descent.