The city as a personal assistant

Abstract

Conversational agents are increasingly becoming digital partners in our everyday computational experiences. Although rich, and fresh in content, they are oblivious to users’ locality beyond geospatial weather and traffic conditions. We introduce conversational agents that are hyper-local, embedded deeply into the urban infrastructure providing rich, purposeful, detail, and in some cases playful information relevant to a neighborhood. These agents are spatially constrained, and one can only interact with them once she is in close vicinity at street-level granularity. In other words, the city provides personal, stateful, spontaneous service to its citizens through the agents installed in urban landmarks. Drawing lessons from two user studies, we identify the requirements for this system. We then discuss the architecture of these agents that leverage covert communication channels and machine learning algorithms that run on the edge and wearable devices to offer meaningful conversational experience in urban settings.