Application of AI-powered camera traps for monitoring elusive carnivores in tropical forests

Monitoring elusive carnivores in the dense hill forests of the Seeleru and Sapparla agency regions of Visakhapatnam District presents significant challenges due to rugged terrain, thick vegetation, nocturnal activity, and naturally low population densities. Recent advancements in Artificial Intelligence (AI) have enabled camera traps to autonomously detect, classify, and log wildlife with high precision, even in such remote landscapes. This study evaluates the efficiency of AI-powered camera traps in detecting multiple carnivore species across these agency hill areas. Our results indicate an average species detection accuracy of 92%, with notable improvements in nocturnal monitoring and substantial reductions in manual data processing time. The integration of AI-based camera trapping in such challenging terrains offers transformative potential for regional conservation efforts, enabling continuous, real-time ecological insights and supporting targeted wildlife management interventions.