HairVise: A Machine Learning, Augmented Reality and Artificial Intelligence Integrated Personalized Hair Care Recommendation Framework
Sakshi Singh, Himani Mali, Vaibhavee Thakur, Sampada Lovalekar · 2024
HairVise addresses the pervasive and often complex hair care issues faced by consumers worldwide. From treating different hair types to addressing specific concerns such as dryness, frizz or damage, individuals often struggle to find the right products tailored to their individual needs. In response to this challenge, HairVise has evolved into an innovative e-commerce platform that seamlessly integrates cutting-edge technologies to revolutionize the hair care experience. Leveraging React for its smart interface, Node.js for robust server-side logic, and MongoDB for efficient data management, HairVise uses a machine learning-based approach to provide personalized hair care recommendations. Using a comprehensive questionnaire, user data is carefully collected to tailor product suggestions based on individual hair types, concerns and preferences. Additionally, HairVise has a sophisticated customer support chatbot powered by Natural Language Processing (NLP) that increases user engagement and satisfaction. Augmented reality (AR) implementation further enriches the platform, allowing users to visualize potential hair color changes before purchasing. This paper provides a comprehensive overview of the development of HairVise, describing its features, methods and the results achieved through its innovative approach to the hair care trade.