Smartphones have become our daily companions and
support us in almost any situation of our daily life. We use them
for communication, gaming, news reading, watching movies,
payment, mobile banking and many others. The way we use
smartphones is correlated with individuals’ needs, interests,
habits, and personality. Custom-tailored content like
recommendations, advertisement, personalized prices and
search results can be presented to consumers, based on
observed activities on their devices.
From the perspective of IoT, smartphones are becoming
increasingly important because they are used as hubs between
the physical objects and Internet. For instance, smartphones
provide dashboards to manage our smart home appliance (like
heating system, light-bulb, key, TV) as well as retrieving and
presenting data from our smart gadgets (like pedometers, body
sensors). Since there is no method to automatically get a list of
individuals’ physical objects, offering fitting recommendations
in IoT is difficult.
– A Novel Recommender System in IoT (Remo Manuel Frey, Runhua Xu, Alexander Ilic)
This pretty much explains the basis of Recommender Systems on IoT devices. This paper discusses about a simple Recommender system that gathers data from mobile devices of users, feeds it to a server and then their proposed system sorts the data and personalizes everything according to user profiles. This concept can be used as a base for all things recommender systems I think..