Exploitation of social IoT for recommendation services

Yasir Saleem, Noel Crespi, Mubashir Husain Rehmani, Rebecca Copeland, Dina Hussein, Emmanuel Bertin

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

71 Citations (Scopus)

Abstract

Internet of Things (IoT) applications are generally developed in a vertical manner, i.e., each IoT application is developed for a certain scenario which generally does not share data with IoT applications for recommendation services. This leads to an inefficient exploitation of other IoT service applications. In fact, such recommendation services can be achieved with the help of Social IoT (SIoT) by using data generated by various IoT applications. SIoT builds a profile of objects based on IoT applications data that can be exchanged with SIoT network for accessible to other IoT applications. In this manner, the SIoT network provides recommendation services for reusability of IoT applications' data among various IoT applications, as well as adapting IoT services according to users' needs which improve user experience. Additionally, the profiles built by a SIoT network can also help a single IoT application by looking for similar conditions that have been addressed in the past for the same IoT application. We propose a concept for exploiting the SIoT for recommendation services among various IoT applications with the help of a sample application scenario that highlights how the SIoT can help by providing recommendations. We also provide some implementation challenges for this concept.

Original languageEnglish
Title of host publication2016 IEEE 3rd World Forum on Internet of Things, WF-IoT 2016
PublisherIEEE Press
Pages359-364
Number of pages6
ISBN (Electronic)9781509041305
ISBN (Print)9781509041312
DOIs
Publication statusPublished - 09 Feb 2017
Externally publishedYes

Publication series

Name2016 IEEE 3rd World Forum on Internet of Things, WF-IoT 2016

Keywords

  • Internet of Things
  • Social Internet of Things
  • Recommendation Services
  • Cross-domain applications
  • recommendation services

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