Agrimind : Smart Crop and Fertilizer Recommendation System using CoT and ToT

Agrimind: Smart Crop and Fertilizer Recommendation System using CoT and ToT that utilizes Artificial Intelligence (AI) was generated to help farmers and agricultural researchers make accurate, data-driven decisions to help better production and manage resources. Temperature, humidity, rainfall, pH, soil nutrients like N, P, K, and other important agricultural parameters are monitored by this system with a combination of machine learning and deep learning techniques. A Random Forest classifier provides the best fertilizer to increase soil health and yield, while an Artificial Neural Network model predicts the ideal crop for the given environmental conditions. To create an interactive and accessible user experience, the entire model is deployed using the Streamlit framework, allowing users to input data, see and visualize the analytics, and get an instant AI-based recommendation on the web interface easily. In addition, an AI-enabled chatbot using natural language processing assists users by answering general agricultural questions. The model presented incorporates Explainable AI techniques such as "Tree of Thought" and "Chain of Thought", which ensures the interpretation and transparency of the prediction model. Ultimately, this project supports smart, sustainable, technology-based agriculture, combining intelligent prediction, automation, and visualization to enable better-informed farming decisions.