Collaborative Data Mining for Intelligent Home Appliances

Oliviu Matei, Giovanni Di Orio, Javad Jassbi, José Barata, Claudio Cenedese

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

10 Citations (Scopus)


The augmentation of physical devices and resources with electronics, software, sensing elements and network connectivity is a "hot topic" as confirmed also by the several research projects and activities on internet-of-things (IoT) and cyber-physical systems (CPS) research streams. It is obvious that intelligent products are taking more responsibility in future collaborative networks. Recent products are becoming more and more intelligent and connected by using the existing network infrastructure, meaning that products are becoming active agents in networks and valuable data sources that are capable to provide data continuously during their operation. This is leading to a massive amount of data that can be used by product manufacturers to be and remain competitive in market sharing. In this scenario, the application of collaborative data mining techniques, supported by machine learning algorithms, is aimed to enable the analysis of the data provided from multiple and above all distributed data sources in order to discover and extract useful knowledge about the behavior of the users along with the usage patterns of their devices and appliances.
Original languageEnglish
Title of host publicationCollaboration in a Hyperconnected World
EditorsHamideh Afsarmanesh, Luis M. Camarinha-Matos, António Lucas Soares
Place of PublicationCham
PublisherSpringer International Publishing AG
Number of pages11
ISBN (Electronic)978-3-319-45389-7
ISBN (Print)978-3-319-45390-3
Publication statusPublished - 2016
Event17th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2016 - Porto, Portugal
Duration: 3 Oct 20165 Oct 2016

Publication series

NameIFIP Advances in Information and Communication Technology
ISSN (Electronic)1868-4238


Conference17th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2016


  • Collaborative data mining
  • Intelligent home appliance
  • Collaborative network


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