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Author(s):

S. Thirisha | G. Narmatha | K. Kalaiyarasan
Keywords:
Abstract:
Human – Wildlife Conflicts Arising From Habitat Encroachment And Deforestation Have Led To An Alarming Increase In Crop Raiding, Causing Substantial Losses To Farmers And Posing Risks To Human Safety. Conventional Methods, Ranging From Lethal Measures To Non-lethal Deterrents, Have Proven Insufficient, Often Leading To Environmental, High Costs, And Limited Effectiveness. In Response To These Challenges, This Project Proposes Novel Integrated Wildlife Management System That Combines Computer Vision, Leveraging Temporal Convolutional Networks (TCN), For Precise Animal Species Detection And Recognition, With A Targeted Ultrasound Emission Technique For Species -specific Repelling. The System, Driven By Edge Computing, Ensures Real-time Responsiveness To Mitigate Crop Raiding. The Workflow Commences With The Activation Of The Camera By The Edge Computing Device, Triggering The Deployment Of An Advanced Animal Intrusion Detection Model. By Leveraging Cutting-edge Technology, The Proposed Solution Seeks To Strike A Balance Between Protecting Crops And Minimizing Environmental Impact. This Project Contributes To The Ongoing Discourse On Human-wildlife Conflict Resolution And Highlights The Potential Of Technology-driven Solutions In Fostering Coexistence Between Agriculture And Biodiversity.