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@article{176069,
        author = {Neelam S Chandolikar and Omkrish Chauhan and Saksham Ovalekar and Omeir Nore and Meet Pabari and Pratik Pachorkar and Rajanee Padwal},
        title = {Machine learning based activity detection in large fields through video surveillance},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {5136-5141},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176069},
        abstract = {Monitoring human and animal activities in large fields and farms is crucial for ensuring crop safety and overall security. This paper presents an intelligent surveillance system designed to automatically detect and classify human and animal activities in agricultural environments. The system is also adaptable for use in various other settings, such as retail shops, banks, and wildlife monitoring. Upon detecting any activity, it immediately sends an automated alert to the user and initiates video recording of the incident. The proposed implementation aims to enhance security, reduce the need for continuous manual monitoring, and optimize storage usage by recording only relevant events.},
        keywords = {Human detection, animal detection and alert system.},
        month = {April},
        }