Towards an Ambient Smart City: Using Augmented Reality to Geospatially Filter the Right Airbnb via Artificial Intelligence

Abstract

We investigate an augmented reality (AR) based method to help the user filter their preferred Airbnb home via artificial intelligence (AI) on a 3-dimensional street view style map in the context of a smart home and smart city ambient scenario. We are motivated by seeking to provide users a 3-dimensional AR interface that: provides equal representation of all data points and allows visual filtration of all filter dimensions directly on the map. We introduce a novel way of visually filtering information geospatially on an AR map by adding information instead of removing it called filtration by inclusion. We introduce the interface in its environmental context in terms of strategic locations for embedding it around the city. We demonstrate how a neural network model can be applied to our filtration technique to act as a human and make filtration decisions. We enforce how technology should enable, not limit the user and discuss how our system does not filter out a home if it does not match the filter criteria, but rather provides the visual information for the user to be able to make that decision on their own as human choices are fluid. We expand upon some limitations of our system and discuss future work on this technology. Our work has implications for user experience design in AI at its intersection with AR big data and situational interaction used most specifically for the context of smart communities and smart cities.

S. Chopra—Work in Petrotranz at the time of publication.