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@article{206124,
        author = {Soham Harkare and Harshal Bagade and J. P. Nawade and Harsh Barbhai},
        title = {An Integrated AI-Based Web Platform for Intelligent Agricultural Decision Support Using Machine Learning and Deep Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {2},
        pages = {427-434},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206124},
        abstract = {Agriculture is fundamental to global food security and economic development, with India being one of the world's largest agricultural producers. However, farmers often face critical challenges in crop selection, plant disease identification, fertilizer management, and market price estimation due to limited access to intelligent decision-support systems. This paper presents a comprehensive machine learning-based Agricultural Assistance System that integrates four intelligent modules: crop recommendation, plant disease detection, fertilizer recommendation, and price prediction. The crop recommendation model utilizes soil nutrients and environmental parameters to recommend the most suitable crop, while the plant disease detection module employs a Convolutional Neural Network (CNN) to identify diseases from leaf images and suggest appropriate treatments. The fertilizer recommendation module provides nutrient-based fertilizer suggestions, whereas the price prediction model estimates future market prices using historical agricultural market data. The proposed system has been deployed as a production-ready web application with secure user authentication, real-time predictions, MySQL database integration, weather information, AI chatbot assistance, Google Maps support, and Google Sheets logging for data persistence. Experimental evaluation demonstrates the practical applicability of the proposed system in supporting farmers with accurate and timely agricultural recommendations. The integrated platform significantly reduces decision-making time while improving farming efficiency, thereby promoting sustainable agriculture and enhancing farmer productivity.},
        keywords = {},
        month = {July},
        }