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@article{185890,
        author = {Muskan and Sinchana G P and Prarthana B G and Karthik M L and Arjun B C},
        title = {A Comprehensive Survey of AI enabled Techniques for Automated Animal Detection and Classification in Ecological and Real-Time Applications},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {4139-4163},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185890},
        abstract = {Artificial intelligence (AI) is coming to play a fundamental role in responding to ecological issues, especially wildlife conservation. This review consolidates the use of innovative AI methods for the automated detection, classification, and tracking of animals in various environments, i.e., forests, farmland, highways, and poorly lit situations. The work points out key gains in accuracy and real-time processing through these technologies. Principal innovations are techniques for transcending data constraints, combination of AI with IoT devices for distant monitoring, and sophisticated segmentation techniques for improved detection accuracy. The applications of AI go beyond technical innovation to real-world implications like the mitigation of human-wildlife conflict, sustainable agriculture, and ecosystem management. Through combining existing progress and recognizing nascent trends and challenges, this paper presents significant lessons and insights for future studies aimed at utilizing AI in the promotion of ecological sustainability and efficient animal monitoring.},
        keywords = {Animal Detection, Deep Learning, Wildlife Monitoring, Human-Wildlife Conflict, Smart Agriculture},
        month = {November},
        }