Sustainable Living Advisor: A Machine Learning-Based Lifestyle Recommendation System

The Sustainable Living Advisor is an intelligent recommendation system powered by AI for processing an individual's lifestyle narratives to provide insights on sustainability through Natural Language Processing (NLP) and Machine Learning (ML) techniques. The system takes in textual data on a person's habits, consumption patterns, and environmental behaviors and predicts a Sustainability Score between 0 and 10. The model checks a range of environmentally positive and negative behaviors using TF-IDF vectorization, sentiment analysis via TextBlob, and keyword- based sustainability indicators. A synthetic dataset of sustainable, unsustainable, and mixed lifestyles was generated to train regression-based models, namely Random Forest, Gradient Boosting, Linear Regression, and Support Vector Regression (SVR). Among these, one is chosen as the best for predicting lifestyle scores and interpreting them based on R² and MSE scores. The suggested system provides a numerical sustainability score along with a detailed analysis of the environmental footprint, which ranks under waste management, transportation, energy consumption, food choices, and general consumption. It gives small eco-friendly recommendations to aid users in more sustainable options. Such associations of environmental sciences and artificial intelligence provide a unique means to promote sustainability from the perspective of personalized data analysis. The Sustainable Living Advisor works towards raising awareness and enabling analytical decision-making for a greener, more responsible lifestyle by analyzing real behavioral reflections in text.