Butler-ising HomeManager: A Pervasive Multi-Agent System for Home Intelligence

Home Manager is an agent-based application for the control of an intelligent home, where the house is seen as an intelligent environment made of independent devices that participate to an agent society. The society is governed by a coordination infrastructure aimed at satisfying the users goals and preferences (lighting, temperature, etc.) while achieving the global house policies and objectives (e.g. energy saving) in a highly- configurable way. In the existing prototype, designed mostly to prove the feasibility and effectiveness of the above approach, the testbed house was kept intentionally simple, with a limited number of rooms, user types, control devices and policies, and the infrastructure implementation lacked some features. The recent, widespread adoption of smart mobile devices (smartphones, tablets) enabling mobile connectivity has dramatically changed the reference scenario: users now expect at least to be able to monitor, and possibly control, their home devices in mobility, and in fact all major vendors now offer some app for this purpose. Yet, this is just the basic step: exploiting the situated connectivity enabled by GPS and the other geo-localisation techniques embedded in today’s smartphones, novel pervasive scenarios can be devised that could not even be imagined in the past years. This aspect is developed in the Butlers architecture, which provides a general framework and reference model for intelligent home management where the smart home is managed by an intelligent butler and interacts with its inhabitants taking into account their habits, behavior, location, prefer- ences and any other sort of information to anticipate their needs and support their goals. In this context, this paper presents the novel “Butler-ised” Home Manager, that evolves the previous system in the Butlers perspective: the new prototype not only supports the remote control of the house appliances via an Android app, but exploits the user position, tracked via geo-localisation, to anticipate the user’s needs in a simple, yet significant, scenario – namely, autonomously switching the house oven on when discovering that the user has just bought a take-away pizza in his/her way back home.