Role of Artificial Intelligence in Wildlife Species Identification

Abstract In modern era of taxonomy, Artificial Intelligence has emerged as powerful taxonomic tool in wildlife conservation and ecological research. Exact identification of species helps in biodiversity monitoring, demographic assessment and biodiversity conservation planning. Conventional methods of species identification mainly includes direct observation, visual examination, physical check are time consuming, tedious and susceptible to human miscalculation. Artificial Intelligence tools such as machine learning and deep learning allows robotic identification of faunal species by photos, videos and sound. These tools survey large dataset collected from different digital tools such as camera trap, drones and auditory sensors for rapid and exact identification of individual species. Artificial Intelligence based tools such as Conventional Neural Network (CNN), You Only Look Once (YOLO), Residual Network (ResNet) improve the efficiency of wildlife monitoring programme. The present research article shows that Artificial Intelligence tools can identify the wildlife species with the help of camera trap images with great accuracy and greatly reducing time required for manual data processing. This paper mainly focus on role of Artificial Intelligence in wildlife species identification, use of tools, implementation in conservation and challenges associated with AI based wildlife monitoring system.