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@article{206584,
        author = {Akshay and Nithesh and Sanjay VP and Pratham Shetty and Ajay Prinston Pinto},
        title = {Smart Poultry Farming System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {25-30},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206584},
        abstract = {Poultry farming represents a crucial agricultural activity yet its effective management becomes challenging because of various issues which include disease outbreaks and poor egg production and insufficient monitoring systems. The current procedures require employees to perform physical inspections that consume excessive time which prevents them from responding to emergencies. The research introduces a Smart Poultry Farming System which applies machine learning and deep learning technologies to enhance farm operations. The system utilizes CNN technology to identify diseases through poultry waste images and it uses image processing techniques to detect cracks in eggs. The system uses LSTM models to analyze historical farm information in order to forecast upcoming production levels and avian health conditions. The web-based dashboard provides clear data display while the notification system informs farmers about essential developments. The system allows farmers to monitor their operations from any location because they can access it using their smartphones. The approach enhances operational productivity while decreasing production losses and it enables farmers to adopt contemporary intelligent agricultural practices.},
        keywords = {Poultry Farming, Smart Agriculture, Deep Learning, CNN, Image Processing, LSTM, Data Analytics},
        month = {July},
        }