Smart Agriculture Advisory System using Django for Real-Time Farming Guidance

Sahni Sumith Kumar, S. Manjunath Reddy

Smart Agriculture; Django Framework; Crop Advisory; Web Application; Keyword-Based AI; Farmer Support System.

Agriculture plays a vital role in the economic development of countries like India, yet farmers often face challenges due to limited access to timely and accurate agricultural advisory services. Traditional knowledge-sharing methods are constrained by geographic, temporal, and resource limitations, leading to inefficiencies in farming practices. This paper presents a Smart Agriculture Advisory System, a web-based platform designed to bridge the gap between agricultural expertise and farmers through a centralized digital solution. The system is developed using a full-stack architecture with a frontend built using HTML, CSS, Bootstrap, and JavaScript, ensuring a responsive and user-friendly interface. The backend is implemented using Python and the Django framework, which manages application logic, user authentication, and database operations. SQLite3 is used as the database for storing farmer profiles, crop information, and query records. The platform consists of two main components: a Farmer Portal and an Admin Portal. Farmers can submit queries related to crop cultivation, fertilizers, pest management, and irrigation, while administrators manage crop data and advisory content. A keyword-based intelligent query processing engine generates real-time responses to farmer queries. The system improves accessibility to agricultural knowledge, enhances decision-making efficiency, and demonstrates the potential of web technologies in empowering rural communities.

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