Identification of Endangered Animal species of Pakistan using Classical and Ensemble Approach

Animal conservation is one of the key challenges that the biodiversity crisis is facing. One of the important factors in this crisis is climate change and global warming. Humans are interfering with regions with wildlife causing expendable damage. To curb these challenges and perform animal preservation, monitoring animals is important. To smartly utilize resources online endangered species are monitored. This monitoring is not humanly possible due to limitations to the human focus, but machines can help automate this. In this study, classical and ensemble machine learning approaches are used to identify three endangered species in the Pakistan region: Markhor, Asiatic Black Bear, and Snow Leopard. A dataset is developed, and basic machine learning operations are performed. Logistic regression was the best performing algorithm with 93% accuracy. This research tends to open the door to animal monitoring research in Pakistan.