Social Appliances for Sustainable Smart Homes

Abstract: We discuss a Cloud-based Collective Intelligence model and its in-progress implementation to direct users toward an optimal usage of their home appliances as a way of getting both personal advantage and an overall reduction of pollution and energy consumption.

In this model sustainability is considered with respect to two types of resources: natural ones, to be mostly preserved, as indicated above, and brain resources, in terms of intention and knowledge, to be convoyed to a common target. Having the first aspect for a given, in this paper we focus on the secondby examining three distinct factors: user experience, knowledge achievement and business model.

Our service paradigm is rooted on a Social Networks of Facts that requires experts’ know, like that owned by the appliance manufacturer, but exploits it in an autonomous way so as to comply with the specific intentions of the individual users.

While cloud architectural and communication aspects are solved in a standard, though advanced, way, the interplay between user and expertsisconsidered variously within a range of business models.

As the success of these models is related to the network population, here we discuss some preliminary simulations based on an effectively implemented infrastructure and on the extrapolation of early collected data.

Key words: social appliances; green social network; machine learning; collective intelligence

JEL Code: C81