Krishi: A Web-Based Smart Farming Assistant for Crop Recommendation and Weather Forecasting
Name: Shyam Bandu Dhone
dept: Computer Science And Engineering
College Name: Anuradha College of Engineering And Technology
Address: Chikhli, India
Name: Swapnil Raju Jogdande
dept: Computer Science And Engineering
College Name: Anuradha College Of Engineering And Technology
Address: Chikhli, India
Name: Jayesh Narendra Bardekar
dept: Computer Science And Engineering
College Name: Anuradha College of Engineering And Technology
Address: Chikhli, India
Name: Dr. P. S. Gawande
dept: Computer Science And Engineering
College Name: Anuradha College Of Engineering And Technology
Address: Chikhli, India
Name: Sushil Gajanan Lahane
dept: Computer Science And Engineering
College Name: Anuradha College of Engineering And Technology
Address: Chikhli, India
Abstract— Agriculture remains the backbone of the Indian economy; however, farmers continue to face challenges related to unpredictable weather conditions, improper crop selection, and limited access to integrated digital tools. With the rapid growth of web technologies, there is a strong opportunity to support farmers through intelligent and accessible platforms. This paper presents Krishi, a web-based smart farming assistant designed to provide real-time weather forecasting and soil-based crop recommendations. The system integrates live weather data, seasonal crop information, and basic soil parameters to assist farmers in making informed agricultural decisions. The proposed solution focuses on simplicity, accessibility, and regional relevance, particularly for farmers in Maharashtra and central India. Krishi aims to reduce dependency on manual decision-making and traditional practices by offering accurate, timely, and user-friendly information through a browser-based interface. Experimental results and practical use cases demonstrate that the system can effectively support farmers in crop planning and agricultural productivity. The platform also lays a foundation for future integration of advanced technologies such as artificial intelligence, multilingual support, and mobile-based services.
Keywords—Smart Farming, Crop Recommendation, Weather Forecasting, Agriculture Technology, Web Application
