Personalised recommendations for daily automations controlled by mobile augmented reality

Internet of Things-enabled home automation is starting to significantly transform our daily lives. Users must be able to configure and coordinate the connected objects in their dwellings to personalise and fully benefit from their potentialities. Trigger-action programming is one relevant approach to enable users to create useful automations. However, current approaches mainly based on visual Web or mobile interfaces have limitations, such as the difficulty in finding and selecting the correct object and associated services. Mobile augmented reality is an interaction modality that can support more direct and usable automation control. In this perspective, the support of a recommendation system can facilitate users in creating personalised automations. This paper presents a system for generating personalised daily automations recommendations and presenting them in a mobile augmented reality solution in order to facilitate their monitoring and creation. Seven classification approaches were assessed on different datasets to determine their ability to provide personalised and context-aware recommendations. We also report a user study (N = 16) showing that the personalised recommendation system improves user performance when creating automations in a trigger action format with a mobile augmented reality editing environment.