Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{183551,
        author = {Sneha Shivanand Bijjaragi and Mahesh Dixit},
        title = {Real-Time Animal Detection System for Farmland Monitoring Using MobileNet-SSD and OpenCV},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {3},
        pages = {2058-2063},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=183551},
        abstract = {This paper presents a real-time animal detection system tailored for agricultural and farmland security applications. The proposed system leverages the lightweight Mobile Net-SSD deep learning model integrated with OpenCV’s Deep Neural Network (DNN) module to identify the presence of animals such as dogs, cats, cows, and others within farm premises. The project incorporates alert mechanisms including audio alarms and optional SMS notifications to deter animal intrusion and minimize potential damage to crops. This system offers a cost-effective and efficient solution for farm monitoring, requiring minimal computational resources while maintaining high detection accuracy.},
        keywords = {Animal Detection, Mobile Net-SSD, OpenCV, Farmland Monitoring, Deep Learning, Real-Time Detection.},
        month = {August},
        }