Year: 2025
Type: article
Abstract: Wildlife intrusion puts limited regions and agricultural fields at risk, resulting in property destruction and crop damage. In order to overcome this difficulty, a sophisticated System uses deep learning to provide protection and monitoring in real time. The system uses the cutting-edge object identification model YOLOv8 to precisely recognize and categorize animals from real time video feeds using OpenCV. It effectively separates animals from people and other objects by using Convolutional Neural Networks (CNNs), guaranteeing accurate detection. In order to help farm owners make better decisions, each discovered animal is labelled with its matching name and confidence score. The technology automatically sends out email notifications when it detects an animal intrusion, lowering manual surveillance efforts and increasing operational efficiency while enhancing security and facilitating quick response. Because of its flexible and adjustable design, it is a dependable way to protect confined areas and agricultural grounds
Author: Dr. Mallikarjuna A
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4410457237