Virtual Personal Shopping Assistant (VSPA)

In recent years, advancements in artificial intelligence (AI) and augmented reality (AR) have led to the development of virtual personal shopping assistants (VPSAs) that enhance the online shopping experience. This paper presents a comprehensive overview of a VPSA that utilizes camera technology for virtual try-ons and clothing recommendations. The system leverages AI algorithms for personalized recommendations, combining user preferences, body measurements, and fashion trends. Through the use of augmented reality, users can virtually try on clothes in real time, allowing them to visualize how items will fit and look without needing to visit a physical store. The VPSA also employs machine learning models to analyze user preferences, past purchases, and social media trends to curate personalized shopping suggestions. The system improves over time by learning from user interactions, providing increasingly accurate recommendations. By merging computer vision, AR, and AI-driven recommendations, the VPSA offers a seamless and immersive shopping experience that can revolutionize online fashion retail. This virtual shopping assistant not only enhances user satisfaction by reducing uncertainty in fit and style but also boosts retailers' conversion rates by minimizing returns and improving customer retention. The integration of such technologies promises a future where the convenience of online shopping matches, or even surpasses, that of traditional brick-and-mortar experiences.