Affiliations 

  • 1 Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia. mhrehman@siswa.um.edu.my
  • 2 Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia. csliew@um.edu.my
  • 3 Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia. tehyw@um.edu.my
  • 4 Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia. junaidshuja@siswa.um.edu.my
  • 5 Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia. babak@um.edu.my
Sensors (Basel), 2015 Feb 13;15(2):4430-69.
PMID: 25688592 DOI: 10.3390/s150204430

Abstract

The staggering growth in smartphone and wearable device use has led to a massive scale generation of personal (user-specific) data. To explore, analyze, and extract useful information and knowledge from the deluge of personal data, one has to leverage these devices as the data-mining platforms in ubiquitous, pervasive, and big data environments. This study presents the personal ecosystem where all computational resources, communication facilities, storage and knowledge management systems are available in user proximity. An extensive review on recent literature has been conducted and a detailed taxonomy is presented. The performance evaluation metrics and their empirical evidences are sorted out in this paper. Finally, we have highlighted some future research directions and potentially emerging application areas for personal data mining using smartphones and wearable devices.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.