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Context-Aware Reasoning Framework for Multi-user Recommendations in Smart Home

  • Nisha PahalEmail author
  • Parul Jain
  • Ruchika Saxena
  • Abhinesh Srivastava
  • Santanu Chaudhury
  • Brejesh Lall
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11942)

Abstract

This paper introduces a context-aware reasoning framework that adapts to the needs and preferences of inhabitants continuously to provide contextually relevant recommendations to the group of users in a smart home environment. User’s activity and mobility plays a crucial role in defining various contexts in and around the home. The observation data acquired from disparate sensors, called user’s context, is interpreted semantically to implicitly disambiguate the users that are being recommended to. The recommendations are provided based on the relationship that exist among multiple users and the decision is made as per the preference or priority. The proposed approach makes extensive use of multimedia ontology in the life cycle of situation recognition to explicitly model and represent user’s context in smart home. Further, dynamic reasoning is exploited to facilitate context-aware situation tracking and intelligently recommending appropriate actions which suit the situation. We illustrate use of the proposed framework for Smart Home use-case.

Keywords

Context-aware Multimedia ontology Dynamic Bayesian Network (DBN) Internet of Things (IoT) Recommendations 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Nisha Pahal
    • 1
    Email author
  • Parul Jain
    • 1
  • Ruchika Saxena
    • 2
  • Abhinesh Srivastava
    • 2
  • Santanu Chaudhury
    • 1
  • Brejesh Lall
    • 1
  1. 1.Indian Institute of TechnologyNew DelhiIndia
  2. 2.Samsung Research InstituteDelhiIndia

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