• JAY FANTIN V P
• MARIA CHRISTY J
• NIKITHA I
• MOHANA PRIYA S
• PRIYADHARSHINI R

The escalating overlap between human activities and wildlife habitats globally has intensified human-wildlife conflict (HWC) and wildlife accidents, posing significant threats to both human well-being and biodiversity conservation. Traditional methods for monitoring wildlife and mitigating these negative interactions often fall short in terms of scalability, real-time responsiveness, and the capacity to process the vast amounts of data required for effective intervention. This paper presents a comprehensive review of the advancements in animal tracking and activity recognition techniques, highlighting the transformative role of artificial intelligence (AI) and computer vision in addressing these challenges. We explore the limitations of conventional approaches and delve into the application of deep learning, edge computing, and multi-sensor data integration for automated wildlife monitoring and the development of AI-powered alert systems. The potential of these technological interventions for proactive conflict mitigation and accident prevention is discussed, emphasizing their significance for fostering human-wildlife coexistence and safeguarding global biodiversity.

"ADVANCEMENTS IN AI-DRIVEN WILDLIFE MONITORING AND CONFLICT MITIGATION: A COMPREHENSIVE REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.h157-h163, May-2025, Available :http://www.jetir.org/papers/JETIR2505817.pdf

"ADVANCEMENTS IN AI-DRIVEN WILDLIFE MONITORING AND CONFLICT MITIGATION: A COMPREHENSIVE REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. pph157-h163, May-2025, Available at : http://www.jetir.org/papers/JETIR2505817.pdf