The Smart Emotion Recognition and Ayurvedic Recommendation System is designed to recognize human emotions from text-based inputs and offer personalized Ayurvedic remedies based on the detected emotions. The system classifies emotions into six categories: Happiness, Sadness, Fear, Disgust, Anger, and Surprise using text data. Advanced machine learning algorithms, including Support Vector Machine (SVM), Random Forest, and XGBoost, are utilized to process and classify the emotional content of the text. Upon recognizing the user's emotional state, the system provides static Ayurvedic recommendations, suggesting remedies tailored to alleviate the detected emotion. For example, calming methods for anger or anxiety-reducing techniques for fear are provided based on the emotional analysis. A chatbot interface enhances user interaction, ensuring a seamless and informative experience. This project combines modern emotional intelligence with traditional Ayurvedic practices to promote mental wellness through an innovative, text-based approach.

Keywords: Emotion Recognition, Ayurvedic Recommendation, SVM, Random Forest, XGBoost, Machine Learning, Text Analysis, Chatbot, Mental Wellness, Personalized Remedies.