Design Flow and Implementation of an AI-Enabled Smart Guidance System for Art Galleries

Audio guides are commonly utilized to enrich the experience of art gallery visitors and to fully engage them with the artwork by providing background, contexts, and other information related to the corresponding artists. However, this method may be monotonous to the public and cannot automatically change to the appropriate recording when users move to the next artwork. The traditional operation of audio guides is only enabled by the user’s visual recognition of the artwork to activate appropriate commentaries manually. In this paper, we explore the potential enhancement of the art gallery visitors’ experience by applying Artificial Intelligence (AI), machine learning, and computer vision techniques to recognize the artwork’s main features automatically and provide the corresponding artist and other information to the visitors. We train a model using a Deep Convolutional Neural Network (CNN) and Kaggle’s Painter by Numbers dataset, and host the trained model on a low-power AI accelerator equipped with a camera to recognize the artwork in real-time. The results are then transmitted to a database, which is utilized by a custom Android application on the smartphone to provide updated artworkrelated information on the display or by audio. Our system targets not only the general public for an interactive experience in the art gallery but also visually impaired people for proper guidance with the smartphone’s camera and its voice feedback capabilities.