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@article{182482,
        author = {Subhash Gautam and Hitesh Badgujar and Shruti Hatkar and Mansi Pawar and Kajal Nandanwar},
        title = {Smart Farm Advisor : AI-Powered End-to-End Farming Advisor for Sustainable and Accessible Agriculture},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {2126-2142},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182482},
        abstract = {Agriculture continues to be the cornerstone of India's economy, providing livelihoods to over 50% of the nation’s workforce. However, farmers across the country face numerous challenges including plant diseases, unpredictable weather patterns, poor market price transparency, and limited access to modern technological tools. In recent years, technologies such as Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) have begun transforming agricultural practices globally. However, in India, the disparity between cutting-edge technology and small- to medium-scale farmers is still large.
This paper introduces KrishiMitra, a comprehensive AI-powered smart assistant developed to address the multifaceted problems faced by Indian farmers. KrishiMitra integrates intelligent components such as a convolutional neural network (CNN) for leaf disease detection, real-time weather updates via API, crop price tracking using government data, and a mobile-friendly interface with multilingual support.
The system is designed to be scalable, offline-accessible, and user-friendly, even for digitally illiterate users. By combining AI models with cloud computing and public APIs, KrishiMitra provides farmers with real-time, actionable insights on their smartphones. It also addresses regional diversity by supporting various crops and languages, ensuring inclusivity and localization.
The implementation of KrishiMitra was evaluated using both simulated and real-world test cases. A field study among farmers in rural Maharashtra showed significant improvement in early disease diagnosis and market awareness. This paper discusses the architecture, training process, data sources, performance, and future scalability of KrishiMitra as a holistic AgriTech platform.},
        keywords = {Agriculture, Artificial Intelligence, Leaf Disease Detection, CNN, Weather Forecast API, Crop Market Price API, Farmer Assistant, AI for Rural Development, AgriTech, Smart Farming, KrishiMitra, Machine Learning in Agriculture, Indian Farming System},
        month = {July},
        }