• Hitesh Kumar Pathak
• Shivam Gurjar
• Aditya Jaiswal
• Yashira Shaikh

Agriculture remains the backbone of many economies, yet farmers often face challenges in selecting suitable crops due to limited access to reliable information about climate and soil conditions. This paper presents the design and development of a web-based system that assists users—particularly farmers and agricultural planners—in identifying the most suitable crops, grains, or fruits to cultivate based on their local climate and soil parameters. By allowing users to input key data such as soil type, pH level, temperature, humidity, and rainfall, the system utilizes a rule-based approach enhanced with artificial intelligence (AI) models to recommend optimal produce for a given region. The integration of IoT-enabled sensors is proposed for automated data collection, ensuring real-time and accurate recommendations. This tool aims to support informed decision-making, improve agricultural productivity, and promote sustainable farming practices. Furthermore, the proposed system can serve as a foundation for integrating advanced machine learning algorithms for dynamic and personalized recommendations. The results demonstrate the potential of digital tools in bridging the knowledge gap in agriculture and empowering users with actionable insights.

Crop Recommendation System, Smart Farming, Soil Type, Climate Data, AI in Agriculture, IoT Sensors, Web-based Application, Sustainable Agriculture

"Smart Crop Recommendation System: A Web-Based Application Integrating AI and IoT for Sustainable Agriculture", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.92-96, May-2025, Available :http://www.jetir.org/papers/JETIRGV06014.pdf

"Smart Crop Recommendation System: A Web-Based Application Integrating AI and IoT for Sustainable Agriculture", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. pp92-96, May-2025, Available at : http://www.jetir.org/papers/JETIRGV06014.pdf